1 00:00:00,520 --> 00:00:03,120 This episode of The Doctors Running Podcast is sponsored by 2 00:00:03,120 --> 00:00:04,360 her friends at Running Warehouse. 3 00:00:04,640 --> 00:00:07,160 Make sure you head over to their YouTube page to catch the second 4 00:00:07,160 --> 00:00:09,920 episode of their new series Test Run, where they put the team 5 00:00:09,920 --> 00:00:12,400 through a series of challenges to help showcase what kind of 6 00:00:12,400 --> 00:00:14,400 activities each shoe is best suited for. 7 00:00:15,000 --> 00:00:17,040 Their latest episode is all about versatility. 8 00:00:17,280 --> 00:00:19,520 Connor and the team brought out some fan favorite trainers of 9 00:00:19,520 --> 00:00:22,480 the past year including the Soccer Endorphin Speed A6, Nova 10 00:00:22,480 --> 00:00:25,640 Blast Three, Poca Clifton 9 and New Balance Rebel V3 to see 11 00:00:25,640 --> 00:00:28,150 where each shoe excelled. Check out the results of their 12 00:00:28,150 --> 00:00:30,630 tests by heading over to Running Warehouses channel on YouTube 13 00:00:30,630 --> 00:00:40,310 today. Hey everyone, welcome to the 14 00:00:40,310 --> 00:00:43,590 Doctors Running Podcast where we, a group of doctors physical 15 00:00:43,590 --> 00:00:46,150 therapy talk about the art and the science of the things we're 16 00:00:46,150 --> 00:00:49,190 putting on our feet. Today we have a fellow physio 17 00:00:49,190 --> 00:00:53,510 and amazing entrepreneur and I. We got to go through all your 18 00:00:53,510 --> 00:00:56,310 titles man. Doctor Jeff Moreno is joining us 19 00:00:56,310 --> 00:00:58,470 and we have talked before, but I thought it was really important 20 00:00:58,470 --> 00:01:00,430 to get him on the podcast to talk a little bit more about 21 00:01:00,430 --> 00:01:04,349 what he does because I don't. Well, I know a lot of companies 22 00:01:04,349 --> 00:01:05,950 know. I think it's really helpful to 23 00:01:05,950 --> 00:01:08,230 know all the amazing thing that you're contributing. 24 00:01:08,430 --> 00:01:10,950 So Jeff, thanks for being on. I really really appreciate it. 25 00:01:11,600 --> 00:01:13,280 Yeah, man, I'm. I'm super excited. 26 00:01:13,800 --> 00:01:17,160 Yeah, you know, we had a great conversation last time and it's 27 00:01:17,160 --> 00:01:19,800 good to just dive in deep a little bit more great to dive 28 00:01:19,800 --> 00:01:22,440 in. So you are both a doctor, have a 29 00:01:22,440 --> 00:01:24,760 doctorate in physical therapy from University of Southern 30 00:01:24,760 --> 00:01:26,320 California. You're a board certified 31 00:01:26,320 --> 00:01:28,680 orthopedic clinical specialist back in 2006. 32 00:01:28,920 --> 00:01:31,520 You have a wide variety of interest and you've done a lot 33 00:01:31,520 --> 00:01:33,960 of really cool things. Let me actually throw it to you 34 00:01:33,960 --> 00:01:36,680 to say, can you introduce your background a little bit, help 35 00:01:36,680 --> 00:01:39,320 our listeners learn a little bit more about you. 36 00:01:40,120 --> 00:01:44,280 Yeah, well, I think, you know, we both have a probably distinct 37 00:01:44,280 --> 00:01:47,800 passion for running. And so, yeah, you know, I spent 38 00:01:47,800 --> 00:01:51,560 most of my career and the high performance in, you know, 39 00:01:51,560 --> 00:01:58,200 working with, you know, people from 800 meters to the marathon 40 00:01:58,240 --> 00:02:00,920 trying to do their best and make it to the next level, which 41 00:02:00,920 --> 00:02:02,560 usually is the Olympic Games, right. 42 00:02:02,560 --> 00:02:08,590 And so so. With you know that I think that 43 00:02:08,590 --> 00:02:12,710 kind of connects the dots from kind of our expertise as it 44 00:02:12,710 --> 00:02:16,110 relates to running. But I always tell people I'm I'm 45 00:02:16,110 --> 00:02:21,990 an extremely confused physio. And the reason that I'm confused 46 00:02:22,030 --> 00:02:28,590 is because I I never quite fit in the, the, the confines of of 47 00:02:28,590 --> 00:02:31,790 the four walls of the basic physio practice, right And so. 48 00:02:32,680 --> 00:02:35,640 I had a background in strength and conditioning and obviously I 49 00:02:35,640 --> 00:02:38,640 went to school to become a physio and and I wanted to do 50 00:02:38,640 --> 00:02:44,320 that since I was 16 years old and but I also have this like 51 00:02:45,000 --> 00:02:49,240 deep sports science research interest and and then I have 52 00:02:49,240 --> 00:02:54,800 also this coaching component as well stems out of just like a 53 00:02:54,800 --> 00:02:58,480 deep love for pedagogy and learning and teaching how to 54 00:02:58,480 --> 00:03:02,050 learn. But what isn't confused and what 55 00:03:02,050 --> 00:03:04,530 I'm never confused about, which sits right in the middle, which 56 00:03:04,530 --> 00:03:07,170 is the the actual human themselves. 57 00:03:07,170 --> 00:03:11,330 And so that is always the thing that ties all those things 58 00:03:11,330 --> 00:03:14,490 together. And so being interested in all 59 00:03:14,490 --> 00:03:19,690 those things and connecting dots from all those things I guess 60 00:03:19,690 --> 00:03:22,010 led me on a really interesting journey. 61 00:03:22,650 --> 00:03:26,810 And so that journey happened to be starting or cofounding a 62 00:03:26,810 --> 00:03:30,420 company and then? And then doing what we're doing 63 00:03:30,420 --> 00:03:32,380 now, which I guess we'll we'll chat about. 64 00:03:32,740 --> 00:03:38,100 Yeah, so extensive background as runner, treating runners, being 65 00:03:38,300 --> 00:03:42,100 someone who doesn't let a career or a title define them, which is 66 00:03:42,100 --> 00:03:44,340 awesome because at the end of the day, we are human beings 67 00:03:44,660 --> 00:03:47,300 constantly striving and evolving over time. 68 00:03:47,300 --> 00:03:50,340 So that's not this is awesome, but it kind of going into what 69 00:03:50,340 --> 00:03:53,100 you mentioned at the end there is that it sounds like you were 70 00:03:53,100 --> 00:03:56,900 treating and then ultra marathoner and of course injured 71 00:03:56,900 --> 00:04:00,940 runner as fifty over almost 50% of us become every year. 72 00:04:01,820 --> 00:04:04,860 Adam came to see you for treatments and you started to 73 00:04:04,860 --> 00:04:07,660 see some challenge. Both of you saw some challenges 74 00:04:08,100 --> 00:04:11,540 and ended up creating something really cool. 75 00:04:11,540 --> 00:04:14,260 Could you go into that a little? Bit, yeah. 76 00:04:14,260 --> 00:04:18,940 So these challenges were something that I was seeing for 77 00:04:18,940 --> 00:04:22,450 quite some time and. There's this back story to that 78 00:04:22,450 --> 00:04:26,810 that I and there's a specific individual that came into my 79 00:04:27,290 --> 00:04:33,090 clinic at the time that I was working that really changed my 80 00:04:33,090 --> 00:04:35,250 life And it he happened to be not a runner. 81 00:04:35,250 --> 00:04:39,730 He happened to be a very young kid and this kid was very 82 00:04:39,730 --> 00:04:42,490 dysfunctional as it relates to his movement. 83 00:04:43,410 --> 00:04:47,650 And I've been seeing this not only in the youth space, but 84 00:04:47,650 --> 00:04:49,490 also in the high performance space and. 85 00:04:51,200 --> 00:04:56,320 And I said, like, it was so bad, I actually thought he had a 86 00:04:56,320 --> 00:04:58,600 neurological disorder. That's how bad it was. 87 00:04:59,400 --> 00:05:02,800 And, you know, I actually asked colleagues, hey, tell me what's 88 00:05:02,800 --> 00:05:05,040 wrong with this, this kid, They're like, oh, he has some 89 00:05:05,040 --> 00:05:07,600 sort of, you know, neurological issue. 90 00:05:07,600 --> 00:05:09,520 And I'm like, no, there's actually nothing wrong with 91 00:05:09,520 --> 00:05:13,040 this, this kid. He just hadn't, you know. 92 00:05:13,850 --> 00:05:16,490 Lived in an environment that was conducive to the normal 93 00:05:16,490 --> 00:05:19,890 development of his being, right, not only from a physical 94 00:05:19,890 --> 00:05:22,130 standpoint, from but from a social standpoint. 95 00:05:23,170 --> 00:05:26,530 And so I kind of went on this sabbatical and this sabbatical 96 00:05:26,530 --> 00:05:33,210 kind of led me to actually meeting Adam through another 97 00:05:33,210 --> 00:05:37,690 colleague and and you know, treating Adam and etcetera. 98 00:05:37,690 --> 00:05:41,010 And as we were going through this process, I just started 99 00:05:41,010 --> 00:05:44,280 explaining to him. This problem that I was seeing 100 00:05:44,280 --> 00:05:52,880 and this problem was, is that, you know, as a physio, we have 101 00:05:52,880 --> 00:05:56,160 access to these individuals for a very, very short amount of 102 00:05:56,160 --> 00:05:59,640 time, right? And you know, they come to our 103 00:05:59,640 --> 00:06:04,000 office or we come to the field or they're traveling or whatever 104 00:06:04,000 --> 00:06:08,520 it may be, however your space works, but when they're not with 105 00:06:08,520 --> 00:06:10,880 you actually don't know what's going on, right? 106 00:06:10,880 --> 00:06:14,190 You don't. Know what their story is, so to 107 00:06:14,190 --> 00:06:17,550 speak. And so talking at him, I was 108 00:06:17,550 --> 00:06:21,070 like, man, He had a data science background. 109 00:06:21,070 --> 00:06:25,670 He was a behavioral economist working at Google and then 110 00:06:25,670 --> 00:06:27,150 working at another place at the time. 111 00:06:27,150 --> 00:06:35,110 And I'm like, man, I just want to deeply understand the the 112 00:06:35,150 --> 00:06:40,830 individual story outside of the confines of my walls. 113 00:06:41,890 --> 00:06:46,930 And and how can we do this with a data lens, right? 114 00:06:46,930 --> 00:06:50,970 Like at the time, you know, GPS watches were becoming more and 115 00:06:50,970 --> 00:06:55,410 more popular, becoming more and more ubiquitous across the the 116 00:06:55,410 --> 00:06:58,530 running space as well as other wearable devices. 117 00:06:59,530 --> 00:07:04,210 This thing that we have in our pocket, you know, is I think 118 00:07:04,450 --> 00:07:08,450 Apple, there's like 900 million people, you know, using these 119 00:07:08,450 --> 00:07:10,890 and then, you know, worldwide there's billions, right? 120 00:07:10,890 --> 00:07:13,620 And so. How do we take this data, 121 00:07:13,620 --> 00:07:17,500 exhaust that everybody's producing, capture it in a way 122 00:07:18,220 --> 00:07:24,300 and utilize that information to allow individuals or for us to 123 00:07:24,300 --> 00:07:27,140 listen and allow individuals to tell their story. 124 00:07:28,180 --> 00:07:31,060 And and that's really kind of how it began. 125 00:07:32,860 --> 00:07:34,700 And he said, well, I I think I can help. 126 00:07:34,740 --> 00:07:38,060 Like, I think I let's play around like I let me take. 127 00:07:38,980 --> 00:07:44,220 You know a CSV file from my Garmin watch and pull that off 128 00:07:44,220 --> 00:07:47,060 and like let me start playing with what things I can get from 129 00:07:47,060 --> 00:07:52,100 it etc. And and that led eventually to 130 00:07:52,100 --> 00:07:54,740 the creation of a company called Power Lab. 131 00:07:55,780 --> 00:08:01,540 And so Power Lab's initial mission and that's was a 132 00:08:01,540 --> 00:08:06,540 consumer application that we created a consumer app was to 133 00:08:06,540 --> 00:08:08,700 really take the kind of the current. 134 00:08:08,950 --> 00:08:12,550 Sports science literature as it relates to injury risk in in 135 00:08:12,550 --> 00:08:16,270 running related injuries, which wasn't great, but we were going 136 00:08:16,270 --> 00:08:21,990 to try to do this anyway and make connect to people's data in 137 00:08:21,990 --> 00:08:26,030 a way where we can kind of give them some awareness around 138 00:08:26,030 --> 00:08:28,710 potential potential susceptibility to running 139 00:08:28,710 --> 00:08:30,990 related injuries as it relates to risk of injury. 140 00:08:32,950 --> 00:08:37,710 And so we did that and we spent a ton of money and and it was 141 00:08:37,870 --> 00:08:40,510 super hard and we had another person helping. 142 00:08:40,510 --> 00:08:45,030 And then another person came on and you know it went from one 143 00:08:45,030 --> 00:08:51,790 thing to another. And all the while a shoe company 144 00:08:51,790 --> 00:08:56,190 came sniffing around and they said we want nothing to do with 145 00:08:56,190 --> 00:08:59,310 your app. Actually we don't like it. 146 00:08:59,310 --> 00:09:02,760 Like, like we don't like. And I I don't know if they said 147 00:09:02,760 --> 00:09:06,080 that we don't like it. It was just like that's not what 148 00:09:06,080 --> 00:09:10,320 we're interested in. But what we are interested in is 149 00:09:10,320 --> 00:09:15,160 that you've you guys have managed to connect to multiple 150 00:09:15,160 --> 00:09:21,160 devices that everybody's using on a daily basis and you're able 151 00:09:21,160 --> 00:09:26,480 to connect in a way that's first party and and we we would love 152 00:09:26,480 --> 00:09:29,320 to figure out how to connect those individuals in a first 153 00:09:29,320 --> 00:09:33,640 party way to our. R&D or innovation team in order 154 00:09:33,640 --> 00:09:37,000 for them to better understand humans in the wild so we can 155 00:09:37,000 --> 00:09:40,200 better serve them through eventually product 156 00:09:40,200 --> 00:09:43,680 personalization, personalization of product and experiences and 157 00:09:43,680 --> 00:09:46,880 services that matter that they that matter to them. 158 00:09:47,800 --> 00:09:50,440 And we're like, no, we don't want to do that. 159 00:09:50,440 --> 00:09:53,880 That's not who we are. Like, we're we're we're running 160 00:09:53,880 --> 00:09:56,920 nerds that just want to, like, figure this problem out, right? 161 00:09:58,600 --> 00:10:02,960 But we got really interesting signals and those signals were 162 00:10:02,960 --> 00:10:09,760 that like if people weren't hurt they didn't care about their 163 00:10:09,760 --> 00:10:11,720 risk, right. They're like that's we don't 164 00:10:11,720 --> 00:10:16,480 live in a society that is really proactive in one's health, 165 00:10:16,480 --> 00:10:18,360 right. We're we're very much a reactive 166 00:10:18,360 --> 00:10:20,280 society based on our healthcare etcetera. 167 00:10:21,720 --> 00:10:26,080 And and so eventually we came to the conclusion that, man, maybe 168 00:10:26,080 --> 00:10:28,550 we. Maybe we should listen to this 169 00:10:28,550 --> 00:10:32,550 company and maybe we should change from a consumer 170 00:10:32,550 --> 00:10:36,470 application to direct to business model where we can 171 00:10:36,470 --> 00:10:41,670 actually serve these individuals and still be true to our core 172 00:10:41,670 --> 00:10:48,390 DNA, which will never change. And so that's how LX was born. 173 00:10:48,710 --> 00:10:51,950 Yeah, that's awesome. So what I'm hearing is by the 174 00:10:51,950 --> 00:10:56,820 way, so our subjective for those listening is as Jeff mentioned, 175 00:10:56,820 --> 00:10:59,420 there is tons of data at our fingertips, right. 176 00:10:59,420 --> 00:11:03,140 So whether you have a Garmin Corros watch or you just have 177 00:11:03,140 --> 00:11:05,860 your phone, these our phones are like there's you don't really 178 00:11:05,860 --> 00:11:07,540 realize now these things are supercomputers. 179 00:11:07,860 --> 00:11:11,980 So they tell Ted, I mean not to get Big Brother on us, but they 180 00:11:11,980 --> 00:11:14,420 have tons of information. So the our big suggestion 181 00:11:14,420 --> 00:11:18,500 question is how do you use the data given to you by the various 182 00:11:18,500 --> 00:11:22,700 devices you use a watch right phone that kind of stuff or do 183 00:11:22,700 --> 00:11:25,090 you even use it? Because that's what I'm hearing 184 00:11:25,090 --> 00:11:28,090 and I think I think the title of this episode should be we'll see 185 00:11:28,090 --> 00:11:31,210 if if BJ Bach and Nathan agree with you. 186 00:11:31,210 --> 00:11:34,970 But I like to detecting signals in the wild because like you hit 187 00:11:34,970 --> 00:11:36,890 on this, you hit on this perfectly that one of the 188 00:11:36,890 --> 00:11:40,170 biggest challenges as a clinician is you are really 189 00:11:40,170 --> 00:11:43,170 taking a snapshot of the whole person. 190 00:11:43,450 --> 00:11:45,970 And that's why I'm sure you were trained the same the way I was 191 00:11:45,970 --> 00:11:49,050 trained the way I trained my students is that your subjective 192 00:11:49,050 --> 00:11:51,090 is one of the most important things. 193 00:11:51,810 --> 00:11:55,330 But the problem is people aren't always very good historians and 194 00:11:55,330 --> 00:11:57,370 you may not get a full picture and then you'll do some 195 00:11:57,370 --> 00:11:59,570 objective testing. You'll look at how they run, you 196 00:11:59,570 --> 00:12:02,370 look at some mobility stuff like that, but you're still only 197 00:12:02,370 --> 00:12:04,410 getting a fraction of what they do. 198 00:12:04,410 --> 00:12:07,050 And we know that definitely there's good evidence that 199 00:12:07,090 --> 00:12:10,410 injuries a lot of the fatigue issues see are accumulated 200 00:12:10,410 --> 00:12:14,930 problems and not usually like this just random acute thing. 201 00:12:15,010 --> 00:12:17,650 Those happen. But it's typically more of these 202 00:12:17,650 --> 00:12:20,670 overuse type stuff, which is challenging because not just in 203 00:12:20,670 --> 00:12:23,870 this country but worldwide, all the research, it's the same way. 204 00:12:23,870 --> 00:12:28,510 It's all reactive, proactive injury predictive studies are 205 00:12:28,510 --> 00:12:30,910 extremely rare because a, they're of huge, they're 206 00:12:30,910 --> 00:12:34,510 extremely difficult to do and people want to know more about 207 00:12:34,510 --> 00:12:37,150 what happened afterwards rather than go, how do we prevent this? 208 00:12:37,150 --> 00:12:39,870 Like I remember what I was, you probably know we've talked about 209 00:12:40,270 --> 00:12:42,390 Chris, Dr. Chris Powers before. I remember I said the word 210 00:12:42,390 --> 00:12:43,510 prevention. He's like, don't say that's a 211 00:12:43,510 --> 00:12:45,390 bad word, It's like a dirty word research. 212 00:12:45,390 --> 00:12:48,390 And I'm like, and later now I'm like, oh, that's why you said 213 00:12:48,390 --> 00:12:49,790 that, because it's so hard to do. 214 00:12:50,190 --> 00:12:51,190 That makes sense. Super hard. 215 00:12:51,470 --> 00:12:53,710 Yeah. I mean what you said there's, 216 00:12:53,710 --> 00:12:56,310 there's so many rich things in that and one is the signals and 217 00:12:56,310 --> 00:13:00,150 we'll get to that in a second because that's a very important 218 00:13:00,150 --> 00:13:05,110 part of our technology. But, but I also want to bring 219 00:13:05,110 --> 00:13:10,390 come back to also what you said because there's being a young 220 00:13:10,390 --> 00:13:18,830 clinician or being even now part of what we're trying to somewhat 221 00:13:18,830 --> 00:13:22,700 decode. Is that time that you go into 222 00:13:22,700 --> 00:13:25,700 your doc's office or your physio's office and you sit 223 00:13:25,700 --> 00:13:31,780 there and you have this really intimate kind of vulnerable 224 00:13:31,780 --> 00:13:35,780 conversation at times, right. That's very back and forth and 225 00:13:35,900 --> 00:13:41,980 and to be honest with you that's the most important part of my 226 00:13:41,980 --> 00:13:49,750 exam and and I I call it like. You know I come in the room and 227 00:13:49,750 --> 00:13:53,390 and it's very broad as you know and it's like tell me a story 228 00:13:53,390 --> 00:13:54,750 and they're like what do you mean? 229 00:13:54,750 --> 00:13:57,110 I'm like I want to know everything about your life. 230 00:13:57,110 --> 00:13:59,950 Just we have plenty of time I'm not going anywhere. 231 00:13:59,950 --> 00:14:02,790 I I've been blessed with the opportunity to spend as much 232 00:14:02,790 --> 00:14:04,910 time with my clients. I know that's not always the 233 00:14:04,910 --> 00:14:10,030 case but and so I say tell me a story and and we go through this 234 00:14:10,030 --> 00:14:13,780 discovery process right and. And there's a ton of questioning 235 00:14:13,780 --> 00:14:16,940 that goes on and there's a ton of historical information that I 236 00:14:16,940 --> 00:14:18,420 want to know that's related to running. 237 00:14:18,420 --> 00:14:21,220 But even that they may think is not related to running, that 238 00:14:21,220 --> 00:14:25,580 matters, right. And and I think of this category 239 00:14:25,580 --> 00:14:29,180 that we're creating, which we call lived experiences, is 240 00:14:29,180 --> 00:14:31,860 really the same. And and the lived experience of 241 00:14:31,860 --> 00:14:34,980 a human is literally their physical experiences. 242 00:14:35,620 --> 00:14:40,620 And it's our job as a company to translate in that and digitize 243 00:14:40,620 --> 00:14:45,180 that. And provide that to individuals 244 00:14:45,220 --> 00:14:50,500 or brands that they love that they can benefit from, right? 245 00:14:50,620 --> 00:14:55,740 And with permission. The data that comes out of that 246 00:14:56,900 --> 00:15:04,300 are like words in my subjective and those words come together to 247 00:15:04,300 --> 00:15:07,540 create sentences and those sentences create paragraphs and 248 00:15:07,540 --> 00:15:09,860 those paragraphs create chapters. 249 00:15:11,040 --> 00:15:15,640 And if you get enough of those lived experience, data words 250 00:15:15,720 --> 00:15:22,520 together over time the you start to have a very clear picture of 251 00:15:22,520 --> 00:15:26,600 this human living in their physical world outside the 252 00:15:26,600 --> 00:15:32,320 confines of the innovation team of a brand or my clinic or 253 00:15:32,320 --> 00:15:36,040 anywhere for that matter. And and that's really exciting 254 00:15:36,040 --> 00:15:38,560 to me because as a as a young clinician, I. 255 00:15:39,310 --> 00:15:42,950 I just didn't get it. I was like, you can only come to 256 00:15:42,950 --> 00:15:46,390 me when you're hurt. I only get to see you this 257 00:15:46,390 --> 00:15:50,270 amount of time and then just when things are getting good, I 258 00:15:50,270 --> 00:15:54,310 can't see you anymore. I'm like, this makes no sense to 259 00:15:54,310 --> 00:15:58,630 me and you can't talk to me unless you are hurt or have a 260 00:15:58,630 --> 00:16:00,470 prescription because you're hurt. 261 00:16:01,750 --> 00:16:09,230 And so I actually see the. The the the change of this is 262 00:16:09,230 --> 00:16:11,750 actually not going to come from healthcare right. 263 00:16:11,750 --> 00:16:14,150 It's going to come from things like outside of healthcare that 264 00:16:14,150 --> 00:16:21,030 have bigger influence and our DNA is very pure and and it 265 00:16:21,030 --> 00:16:25,150 probably comes from this the physios that you and I are and 266 00:16:25,750 --> 00:16:29,030 and every physio loves movement and we we want to promote 267 00:16:29,030 --> 00:16:32,430 movement and we want to empowers people people's ability to 268 00:16:32,430 --> 00:16:35,470 thrive and. Ours just happens to be we're 269 00:16:35,470 --> 00:16:38,630 going to do that in ways where we can maximize data or we can 270 00:16:38,630 --> 00:16:41,150 use the data to maximize their well-being, right. 271 00:16:42,430 --> 00:16:47,430 And so if we can do that through a brand that has influence in a 272 00:16:47,430 --> 00:16:51,590 positive way and and really start to shift the narrative of 273 00:16:51,590 --> 00:16:56,430 what this like funky thing called prevention is or like 274 00:16:56,710 --> 00:16:59,710 taking care of a human in a unique way at a very personal 275 00:16:59,710 --> 00:17:03,190 level. It's totally worth the stress 276 00:17:03,190 --> 00:17:06,869 that I have every day. That makes sense. 277 00:17:06,869 --> 00:17:10,310 And so, yeah, yeah. So it's interesting because I 278 00:17:10,310 --> 00:17:12,750 think we've talked about this before, but I want to reiterate 279 00:17:12,750 --> 00:17:16,390 this just for the listeners is that you mentioned something 280 00:17:16,390 --> 00:17:18,790 that, that is a core and something that I'm starting to 281 00:17:18,790 --> 00:17:20,150 realize. And obviously, we all keep 282 00:17:20,150 --> 00:17:23,069 fighting it. But a lot of the innovation and 283 00:17:23,069 --> 00:17:26,910 like the ability to make changes don't always come from these 284 00:17:27,369 --> 00:17:29,370 large industries like healthcare, right? 285 00:17:29,370 --> 00:17:31,770 They're kind of like these big machines that kind of have so 286 00:17:31,770 --> 00:17:33,770 many variables going on. They influence that. 287 00:17:34,170 --> 00:17:37,610 So, you know, I remember when I was in PT school over a decade 288 00:17:37,610 --> 00:17:39,650 ago, you remember Shirley Sarmon. 289 00:17:39,730 --> 00:17:42,490 And for those who don't know if she is like a God, like a like a 290 00:17:43,170 --> 00:17:46,010 legend with the field as of quite a bit, yeah, she's 291 00:17:46,050 --> 00:17:48,620 phenomenal. For any of the PTS out there 292 00:17:48,620 --> 00:17:51,420 while she's still alive, please go to one of her conferences and 293 00:17:51,420 --> 00:17:54,220 please get made fun of personally by her. 294 00:17:54,220 --> 00:17:55,500 It is an experience. Sure. 295 00:17:55,740 --> 00:17:58,700 And really, really encourage that she didn't like. 296 00:17:58,780 --> 00:18:00,900 I think like is she's still in her 90s and she's still 297 00:18:00,900 --> 00:18:03,860 teaching. Yeah, I mean, she's amazing. 298 00:18:03,940 --> 00:18:06,740 She's amazing, but I remember her talking about like, I think 299 00:18:06,740 --> 00:18:10,290 the future of where help not just physical therapy but 300 00:18:10,290 --> 00:18:14,010 Healthcare is being able to be the movement experts but also go 301 00:18:14,090 --> 00:18:16,250 how do we start doing prevention right. 302 00:18:16,250 --> 00:18:18,970 We know some of these things, we need to get more evidence on 303 00:18:18,970 --> 00:18:22,810 them, but we know there's certain patterns or lack thereof 304 00:18:23,210 --> 00:18:25,730 that might influence stuff. So why wouldn't people come 305 00:18:25,730 --> 00:18:27,610 visit us? You know, like just the same way 306 00:18:27,610 --> 00:18:30,850 you get a physical is come check in make sure everything's good 307 00:18:31,130 --> 00:18:35,690 so that you don't need to spend 8 to 12 weeks having to rehab 308 00:18:35,690 --> 00:18:38,050 something. But it sounds like you realized 309 00:18:38,700 --> 00:18:40,260 I'm not going to get this done in healthcare. 310 00:18:40,260 --> 00:18:42,420 I'm going to need to be more efficient and go to go to 311 00:18:42,420 --> 00:18:45,740 somewhere where a large company has influence and is going to be 312 00:18:45,740 --> 00:18:48,180 able to use this data to influence a product that 313 00:18:48,340 --> 00:18:51,180 everyone, especially the ones that we're passionate about, are 314 00:18:51,180 --> 00:18:52,460 using. Right. 315 00:18:52,460 --> 00:18:54,460 Yeah. And this is starting to happen. 316 00:18:54,460 --> 00:19:00,780 And and people like Gin and and Brooks and people like Christian 317 00:19:00,780 --> 00:19:03,860 died and Adidas and Andrea Sakhany and all these 318 00:19:03,860 --> 00:19:06,860 individuals that we know really well, you know, they're 319 00:19:06,860 --> 00:19:10,760 starting. To understand like the the 320 00:19:10,760 --> 00:19:14,680 bigger picture and and it's individuals like that that are 321 00:19:14,680 --> 00:19:18,160 actually going to kind of make this change and and the change 322 00:19:18,160 --> 00:19:23,440 really is is pretty simple to me and they'll say the same too is 323 00:19:23,440 --> 00:19:33,360 that if if they want to sell shoes it behooves them to have a 324 00:19:33,360 --> 00:19:36,050 human. That actually is going to want 325 00:19:36,050 --> 00:19:40,170 to use the shoes because they're healthy enough to use the shoes, 326 00:19:40,170 --> 00:19:46,010 right? If a human isn't active or able 327 00:19:46,010 --> 00:19:50,170 to run, I mean, why do they need to hop on the Internet or the 328 00:19:50,170 --> 00:19:53,530 site and buy the next best shoe? They're not going to do that, 329 00:19:53,530 --> 00:19:56,210 right? Matter of fact, we know the data 330 00:19:56,210 --> 00:19:59,650 says that. The dropout rates or the return 331 00:19:59,650 --> 00:20:04,250 to run rates for someone who has had it running, running related 332 00:20:04,250 --> 00:20:10,210 injury is really bad, right? So there's there's a, there's a 333 00:20:10,450 --> 00:20:15,650 paradigm shift occurring and it's at a very large scale and 334 00:20:15,650 --> 00:20:21,810 I'm super excited about that. And so what's the big change? 335 00:20:21,810 --> 00:20:27,260 Well, the big change comes from. How do we take this data that 336 00:20:27,260 --> 00:20:31,940 everybody's producing, this lived experience data from their 337 00:20:31,940 --> 00:20:35,180 Garmin watch, from their Polar, from their apple, from their 338 00:20:35,180 --> 00:20:41,700 chorus or their Sumto or whatever they have and provide a 339 00:20:41,700 --> 00:20:45,660 pipeline or connection point to a brand that they love and get 340 00:20:45,660 --> 00:20:52,170 value from that, right. And so instead of you know them 341 00:20:52,410 --> 00:20:57,370 taking data from the website, clicks or impression like no, 342 00:20:57,370 --> 00:21:02,010 you like, you asked them nicely for it, you've invited you, the 343 00:21:02,010 --> 00:21:05,330 brand has invited them into their innovation lab. 344 00:21:06,210 --> 00:21:09,130 You're going to get something for it potentially or you're 345 00:21:09,130 --> 00:21:12,410 going to be a part of a community like like for example 346 00:21:12,530 --> 00:21:17,080 the Brooks Run Club. And then with that we're going 347 00:21:17,080 --> 00:21:23,680 to utilize your data for XY&Z. And it's with a purpose that not 348 00:21:23,680 --> 00:21:27,440 only starts to create this really interesting community 349 00:21:27,440 --> 00:21:31,080 effect or flywheel, but it also builds trust. 350 00:21:31,520 --> 00:21:35,560 And you and I know as physios like the number one thing that 351 00:21:35,560 --> 00:21:38,760 can happen on our, the most important thing that can happen 352 00:21:38,760 --> 00:21:42,080 on our first visit is to create this level of trust. 353 00:21:42,900 --> 00:21:47,340 And once you have that, you're like things are pretty golden. 354 00:21:47,700 --> 00:21:51,540 But if you don't establish that, it's really, really challenging, 355 00:21:51,540 --> 00:21:55,820 right. And so we're on that path to 356 00:21:55,820 --> 00:22:00,140 facilitating that. And it's a it's a pretty amazing 357 00:22:00,140 --> 00:22:03,740 path. And you got to be really upfront 358 00:22:03,740 --> 00:22:06,940 because I know there's good evidence that people form trust. 359 00:22:07,320 --> 00:22:10,320 Within the 1st 10 seconds of meeting someone. 360 00:22:10,320 --> 00:22:12,720 So you have to make a really good first impression and 361 00:22:12,720 --> 00:22:14,120 maintain that. Yeah. 362 00:22:14,200 --> 00:22:16,080 So especially when you take somebody's data and you're like, 363 00:22:16,080 --> 00:22:18,040 like, hey, would you please share this where we've got 364 00:22:18,040 --> 00:22:19,760 something to offer you? Yeah. 365 00:22:19,760 --> 00:22:21,640 And it's just being authentic, right. 366 00:22:21,640 --> 00:22:26,360 Like we ask the brands to be extremely authentic and upfront. 367 00:22:26,400 --> 00:22:31,400 We ask them to say why they're using this information and then 368 00:22:31,760 --> 00:22:34,880 actually go about doing what they say, right. 369 00:22:35,240 --> 00:22:38,880 And so whether that's a research project that they're doing with 370 00:22:38,880 --> 00:22:44,560 a specific amount of people on a specific shoe or like a 371 00:22:44,560 --> 00:22:47,720 university utilizing the information to actually do 372 00:22:47,720 --> 00:22:51,360 research on running related injuries or a feasibility study 373 00:22:51,360 --> 00:22:57,720 on using our data to facilitate that, it's just all about 374 00:22:57,720 --> 00:23:01,680 authenticity, right? And people can sniff that out 375 00:23:01,760 --> 00:23:06,080 really quickly nowadays, right, because they're always being hit 376 00:23:06,080 --> 00:23:10,760 with something. And usually if you're like me 377 00:23:10,760 --> 00:23:13,960 and I get that in an e-mail form that has no form of 378 00:23:13,960 --> 00:23:16,240 personalization to it, I just delete it, right? 379 00:23:16,640 --> 00:23:18,800 It's just not worth my time, right? 380 00:23:18,800 --> 00:23:23,000 And so that's the change that's occurring. 381 00:23:24,710 --> 00:23:27,870 And once that change has occurred and they're 382 00:23:27,870 --> 00:23:31,750 facilitating that, then then we can really start to do really 383 00:23:31,750 --> 00:23:34,070 cool things and brands can really start to do really cool 384 00:23:34,070 --> 00:23:36,630 things. So from a data perspective, 385 00:23:36,630 --> 00:23:39,670 well, what kind of data is this? That's usually the question, 386 00:23:39,670 --> 00:23:44,390 right? If I break it down into buckets, 387 00:23:45,150 --> 00:23:48,910 there's data that comes from you as the human, right? 388 00:23:48,910 --> 00:23:51,550 So there's your user demographics. 389 00:23:51,550 --> 00:23:59,410 And so as the physio, Matt, if if I like, gave you a profile of 390 00:23:59,410 --> 00:24:06,250 a human, you have a 55 year old masters runner who has a history 391 00:24:06,250 --> 00:24:11,090 of X issue, right? Let's say a calf problem, a 392 00:24:11,090 --> 00:24:14,770 history of calf issues. Or, you know, in their 30s, they 393 00:24:14,770 --> 00:24:18,890 might have had Achilles, tendinopathy, never knee pain, 394 00:24:19,410 --> 00:24:24,250 usually in the lower leg, you know, they they run three to 395 00:24:24,250 --> 00:24:28,050 four days a week. They're getting slower, but 396 00:24:28,050 --> 00:24:32,690 occasionally they'll run fast. You know, they're this weight, 397 00:24:32,930 --> 00:24:38,010 they're this height, they run on this specific terrain, they run 398 00:24:38,010 --> 00:24:40,890 at this specific time in the morning, every morning. 399 00:24:41,650 --> 00:24:43,650 And this is usually these distances. 400 00:24:43,650 --> 00:24:46,930 But then you get a signal that you're like, oh, you you ran 401 00:24:46,930 --> 00:24:55,430 significantly more over the last two days, you know, so that user 402 00:24:55,430 --> 00:24:58,990 demographic, you have environmental data, you know, 403 00:24:59,110 --> 00:25:01,590 terrain profiling, elevation changes. 404 00:25:02,870 --> 00:25:09,270 You have other forms of data like speed, spatial temporal 405 00:25:09,270 --> 00:25:14,270 characteristics, like, you know, your basic cadence, stride 406 00:25:14,270 --> 00:25:15,910 length. And then we have other 407 00:25:15,910 --> 00:25:21,760 proprietary algorithms that we've created that looks at or 408 00:25:21,760 --> 00:25:25,360 or connects people's stride characteristics to kind of 409 00:25:25,560 --> 00:25:27,600 understand their specific running style. 410 00:25:27,600 --> 00:25:30,960 And that a lot of that was based out of Bin Van Oren's work 411 00:25:31,600 --> 00:25:35,840 looking at running styles. And so we take all that stuff 412 00:25:36,600 --> 00:25:39,240 and then it creates a unique picture, right. 413 00:25:39,240 --> 00:25:44,560 And and so then the next question we would ask or we're 414 00:25:44,560 --> 00:25:49,960 getting brands to ask is like OK, if I have changes in 415 00:25:49,960 --> 00:25:53,320 elevation, I have had, I have changes in velocity which can be 416 00:25:53,320 --> 00:26:00,840 a proxy for internal load of the bone or at the calf itself or 417 00:26:00,840 --> 00:26:03,640 the Achilles tendon based on some of the work that we know, 418 00:26:03,760 --> 00:26:08,360 right, mechanical fatigue work from Bryn Edwards, we can start 419 00:26:08,360 --> 00:26:12,600 to like think ah, you know this is, this is kind of interesting, 420 00:26:12,600 --> 00:26:16,200 right. And if I knew this stuff, and I 421 00:26:16,200 --> 00:26:21,040 knew their past injury history, and I'm having a continuous 422 00:26:21,040 --> 00:26:28,000 conversation with them through a triggered survey when necessary, 423 00:26:29,200 --> 00:26:33,400 then you know, I can start to think about, well, what type of 424 00:26:33,400 --> 00:26:37,720 shoe made this person benefit more from than another, right? 425 00:26:38,320 --> 00:26:41,680 If I if they all these shoes were on a spectrum and let's say 426 00:26:41,680 --> 00:26:45,720 the spectrum was like a triangle and there's A at the top of the 427 00:26:45,720 --> 00:26:50,050 triangle there's a more minimal shoe and at the other edge of 428 00:26:50,050 --> 00:26:55,610 the triangle there is a more elastic shoe and that the other 429 00:26:55,610 --> 00:26:58,330 one there's a more cushion shoe like. 430 00:26:58,450 --> 00:27:03,250 Then we can start to hypothesize based on these signals that I'm 431 00:27:03,250 --> 00:27:07,490 getting from this human, what would I put this person in? 432 00:27:07,490 --> 00:27:13,330 Potentially knowing that the shoe is like, to us it's just a 433 00:27:13,330 --> 00:27:20,370 load manipulation tool, right? And so then we can go from there 434 00:27:20,530 --> 00:27:24,170 and even dig deeper. And this is where it gets super 435 00:27:24,170 --> 00:27:27,170 uncomfortable for brands right now, to be honest. 436 00:27:27,690 --> 00:27:30,130 But not me. I'm like, let's do this. 437 00:27:30,130 --> 00:27:37,130 I'm totally into this. Like, OK, if we potentially can 438 00:27:37,130 --> 00:27:41,970 hypothesize about a better shoe, we're not saying perfect, but 439 00:27:41,970 --> 00:27:46,290 better shoe potentially then can. 440 00:27:46,290 --> 00:27:51,650 Can't we also potentially hypothesize about maybe some of 441 00:27:51,650 --> 00:27:56,530 the physical things from a capacity standpoint that this 442 00:27:56,530 --> 00:27:59,090 individual might want to work on? 443 00:28:01,250 --> 00:28:05,730 If we only give them three things, let's just give them 444 00:28:05,730 --> 00:28:09,050 three simple things. But how cool would it if they 445 00:28:09,050 --> 00:28:14,450 got a text saying, hey, I noticed this, we we we find that 446 00:28:14,450 --> 00:28:19,850 when these things match up that it's really beneficial to do 447 00:28:19,850 --> 00:28:26,370 this thing in the gym, you know, or this type of a movement thing 448 00:28:30,210 --> 00:28:35,570 that's uncomfortable for people because they're used to waiting 449 00:28:35,770 --> 00:28:40,990 until that guy has a calf string or Achilles tendinopathy from 450 00:28:41,110 --> 00:28:43,550 running too fast. Because he hasn't run fast. 451 00:28:43,590 --> 00:28:46,430 He's 55 years old and he hasn't run fast in a year. 452 00:28:46,430 --> 00:28:50,270 But he did a race randomly and all of a sudden he spin spun 453 00:28:50,270 --> 00:28:53,390 those wheels and now his Achilles hurts because its 454 00:28:53,390 --> 00:28:58,430 capacity of his lower leg is really low and the elasticity 455 00:28:58,430 --> 00:29:01,230 within the tendon is less than it used to be. 456 00:29:01,950 --> 00:29:04,790 Kind of we we kind of know those things, right, Matt So. 457 00:29:05,030 --> 00:29:07,140 So. It's likely what my dissertation 458 00:29:07,140 --> 00:29:08,700 is on. So yeah, you're you're preaching 459 00:29:08,700 --> 00:29:10,500 to the choir. I'm like, did you choose this 460 00:29:10,500 --> 00:29:12,860 just because I'm doing Achilles cap stuff and Master Strutters? 461 00:29:12,900 --> 00:29:15,540 But yeah, it's true. It's totally true. 462 00:29:15,540 --> 00:29:19,580 And you got all, like, the data is basically that an insanely 463 00:29:19,580 --> 00:29:22,460 accurate part of your subjective objective exam. 464 00:29:22,460 --> 00:29:24,620 And that's, I don't think that's uncomfortable at all. 465 00:29:24,620 --> 00:29:26,420 I think it's great. But I understand why they may 466 00:29:26,420 --> 00:29:28,190 not be uncomfortable. Yeah. 467 00:29:28,190 --> 00:29:31,790 So, like, yeah, so like, you can't use words like 468 00:29:31,790 --> 00:29:35,270 prescribing, which is probably good, but that's fair. 469 00:29:35,310 --> 00:29:38,150 You know, you can recommend things that I think are fair, 470 00:29:38,150 --> 00:29:42,430 but how cool would it be for a human outside of the confines of 471 00:29:42,430 --> 00:29:44,590 us or outside of the confines of a brand? 472 00:29:44,590 --> 00:29:47,510 But it would connect to the brand to get a text from a brand 473 00:29:47,510 --> 00:29:52,030 saying, man, you're doing great, I loved your run today. 474 00:29:52,390 --> 00:29:56,470 You know you ran 6.5 miles at this pace. 475 00:29:57,000 --> 00:29:59,160 You had this much of elevation change. 476 00:29:59,160 --> 00:30:02,560 You're rocking it. Hey, I think based on what 477 00:30:02,560 --> 00:30:05,280 you're currently doing I know you bought this shoe, but you 478 00:30:05,360 --> 00:30:09,880 you might really enjoy this one it when when that other shoes 479 00:30:09,880 --> 00:30:11,160 done. Check this one out. 480 00:30:12,560 --> 00:30:17,120 And by the way, try these, try these things, and here's why 481 00:30:19,310 --> 00:30:22,950 that would be so amazing, right? It would because a you got you 482 00:30:22,950 --> 00:30:25,470 got a couple components. You a building a relationship 483 00:30:25,510 --> 00:30:28,110 and you know yeah life is hard, right. 484 00:30:28,190 --> 00:30:30,190 Yeah. And not to talk down about this 485 00:30:30,230 --> 00:30:32,590 everybody you know social meat we're on our phones so much. 486 00:30:32,790 --> 00:30:34,470 There's a lot of negativity out there. 487 00:30:34,470 --> 00:30:37,150 There's very good evidence that being on social media actually 488 00:30:37,150 --> 00:30:41,390 has impact on your psychological and your mental health and we. 489 00:30:41,390 --> 00:30:43,070 So we know that. So to get some positively going. 490 00:30:43,070 --> 00:30:45,270 Hey you doing great. We're looking out for you. 491 00:30:45,270 --> 00:30:47,030 We're not just we're not trying to sell your product. 492 00:30:47,030 --> 00:30:48,910 We're just saying hey, when you're interested. 493 00:30:49,280 --> 00:30:51,760 This might be a good option because we know that varying 494 00:30:51,760 --> 00:30:54,640 your shoe choice is one of the few things that reduces injury. 495 00:30:55,000 --> 00:30:58,600 But then going, hey, we're not going to say it like this, but 496 00:30:58,600 --> 00:31:02,000 we know almost 50% of runners get injured every single year, 497 00:31:02,160 --> 00:31:04,280 right? Sure, we don't want that, right? 498 00:31:04,280 --> 00:31:07,160 Because like you said then people don't run the dropout 499 00:31:07,160 --> 00:31:09,560 rates really high, which this is where I mean, I won't go off on 500 00:31:09,560 --> 00:31:11,750 this tangent, but. For masters runners, This is why 501 00:31:11,750 --> 00:31:14,830 I was interested in my population for my study. 502 00:31:14,830 --> 00:31:17,830 Because as we get older and things get more challenging, the 503 00:31:17,830 --> 00:31:21,910 dropout rate tends to increase. So that we need to start 504 00:31:21,910 --> 00:31:25,470 figuring out how do we either help people get back faster or 505 00:31:25,470 --> 00:31:27,390 how do we try to prevent injuries in the 1st place or 506 00:31:27,390 --> 00:31:30,150 reduce them. And if you can do that through, 507 00:31:30,150 --> 00:31:32,950 hey, you know, and all clinicians have had that 508 00:31:32,950 --> 00:31:35,070 experience going, you know, what if you just did this like one 509 00:31:35,070 --> 00:31:38,190 thing or got a notification? Education. 510 00:31:38,190 --> 00:31:41,230 Yeah, a large part of our interventions is education. 511 00:31:41,230 --> 00:31:44,790 So what if we can give that to people beforehand and teach them 512 00:31:44,790 --> 00:31:47,030 these things so that they can figure out, oh, you know what, 513 00:31:47,470 --> 00:31:49,510 there was a little too much elevation today. 514 00:31:49,710 --> 00:31:51,950 I'm going to need to back this off because I know I got a great 515 00:31:51,950 --> 00:31:53,110 benefit. It's a great run. 516 00:31:53,430 --> 00:31:56,670 But I know based on my history, I need to modify this. 517 00:31:56,670 --> 00:31:58,230 Then I'll get back to it like that. 518 00:31:58,590 --> 00:32:01,790 The education and the prevention is key. 519 00:32:02,430 --> 00:32:04,070 Yeah, it doesn't have to be prescribed. 520 00:32:04,190 --> 00:32:06,150 It could be. This might be a good thing for 521 00:32:06,150 --> 00:32:09,870 your movement health, right? Or your proficiency. 522 00:32:10,350 --> 00:32:13,030 Yeah, totally. And just having we call it from 523 00:32:13,030 --> 00:32:15,190 a self determination theory, right? 524 00:32:15,190 --> 00:32:19,470 We call that relatedness. Like people, you know, besides 525 00:32:19,470 --> 00:32:22,430 wanting competence and autonomy, they also want someone on their 526 00:32:22,430 --> 00:32:24,270 shoulder looking after them, right and right. 527 00:32:24,990 --> 00:32:32,750 And I think using lived experience data and in capturing 528 00:32:32,750 --> 00:32:36,830 specific signals that and then can in turn trigger actions, 529 00:32:36,830 --> 00:32:42,630 whether it's from an external motivation standpoint, putting 530 00:32:42,630 --> 00:32:47,710 them into something that may potentially feel better for them 531 00:32:48,110 --> 00:32:51,990 based on capturing a bunch of information over time and 532 00:32:51,990 --> 00:32:54,150 learning more about those things. 533 00:32:54,990 --> 00:32:59,240 I think is the next wave of how people are going to be taken 534 00:32:59,240 --> 00:33:02,440 care of. And it's really one brand told 535 00:33:02,440 --> 00:33:05,760 me last week, They're really like going and this was a 536 00:33:05,760 --> 00:33:09,800 massive, massive shoe company and I almost fell out of my 537 00:33:09,800 --> 00:33:13,480 chair. They're like, yeah, we're really 538 00:33:13,480 --> 00:33:17,760 going away from just this idea of like, you know, shoving shoes 539 00:33:17,760 --> 00:33:20,120 down people. And we just like, really want to 540 00:33:20,120 --> 00:33:25,380 be known as the caretaker brand. We just want to take care of 541 00:33:25,380 --> 00:33:29,820 these individuals because if we know, if we do that, like all 542 00:33:29,820 --> 00:33:34,660 the other stuff from selling shoes to, you know, people being 543 00:33:34,660 --> 00:33:37,620 invested in and brand, it'll just kind of take care of 544 00:33:37,620 --> 00:33:39,420 itself. And I'm like, Oh my. 545 00:33:39,500 --> 00:33:41,940 Gosh, you're so you're so right. Please do that. 546 00:33:43,180 --> 00:33:45,340 Finally moving. Yeah, finally moving from like 547 00:33:45,340 --> 00:33:46,980 shortterm sell as much as possible. 548 00:33:47,140 --> 00:33:50,900 Yeah, Longterm, if somebody's going to come to us and choose 549 00:33:50,900 --> 00:33:54,540 us as a brand. It's how do we like show our 550 00:33:54,540 --> 00:33:58,380 appreciation and make sure we tear care of you equally, right? 551 00:33:58,380 --> 00:34:00,340 That's awesome. Yeah. 552 00:34:00,340 --> 00:34:06,300 And then, you know, I think I love all the gadgets, right? 553 00:34:06,300 --> 00:34:09,460 Like you're you're in the lab right now you like you. 554 00:34:09,500 --> 00:34:12,540 You know we have force plates and we have 3 dimensional you 555 00:34:12,540 --> 00:34:17,260 know Viacom systems that can that we can all nerd out on. 556 00:34:19,130 --> 00:34:23,170 But also sometimes the simplest things are like usually the most 557 00:34:23,170 --> 00:34:26,370 effective things. And so how do we take, how do we 558 00:34:26,370 --> 00:34:33,370 take a very complex process and and capture low friction data 559 00:34:33,370 --> 00:34:36,010 that can like create simplicity around this. 560 00:34:36,690 --> 00:34:40,850 And understanding all the craziness is important because 561 00:34:40,850 --> 00:34:45,690 then you can use that to facilitate proxies that in turn 562 00:34:45,929 --> 00:34:51,750 kind of tell you similar things. And so that's what people in the 563 00:34:51,750 --> 00:34:55,030 labs are doing right now with this data, is that they're 564 00:34:55,030 --> 00:35:00,350 taking the connection of the environment, the human, and the 565 00:35:00,350 --> 00:35:04,590 task of the running itself and combining these data sets 566 00:35:04,590 --> 00:35:10,070 together to really answer what real runners want, right, Real 567 00:35:10,070 --> 00:35:11,790 runners. And you know this and This is 568 00:35:11,790 --> 00:35:15,750 why you have an amazing podcast and do shoe reviews, because 569 00:35:15,750 --> 00:35:19,470 what do runners want? They want to know, like, there's 570 00:35:19,470 --> 00:35:23,590 a 5 billion shoes out there, and I have no clue what shoe to buy. 571 00:35:23,590 --> 00:35:29,670 Just tell me what shoe to get and I'll buy three of them, 572 00:35:30,550 --> 00:35:33,310 right? Like, you know, how are they 573 00:35:33,310 --> 00:35:35,470 supposed to know? It's like, crazy, right? 574 00:35:35,470 --> 00:35:40,410 And so people are trying to kind of understand that and make that 575 00:35:40,410 --> 00:35:42,570 more accessible. The other thing and you know 576 00:35:42,570 --> 00:35:45,010 this because you just had the podcast is they're trying to 577 00:35:45,010 --> 00:35:47,250 understand durability of the mid sole. 578 00:35:47,370 --> 00:35:50,930 So like people can figure out well when do I replace my shoes. 579 00:35:51,730 --> 00:35:55,770 And in doing so you learn more well like maybe the durability 580 00:35:55,770 --> 00:35:58,890 of the mid sole is a lot greater than we thought it was, but we 581 00:35:58,890 --> 00:36:02,690 still have the out sole and the upper to deal with and that's 582 00:36:02,690 --> 00:36:06,890 probably going to wear down quicker than the mid sole 583 00:36:06,890 --> 00:36:10,830 itself. And then it depends on the type 584 00:36:10,830 --> 00:36:14,670 of runner, right. One of the guys you talk to has 585 00:36:14,670 --> 00:36:21,790 a crazy stride is so and it's really long and like he wears 586 00:36:21,790 --> 00:36:27,430 down shoes different than my myself and so so it's different, 587 00:36:27,430 --> 00:36:29,870 right? And the rest of his team calls 588 00:36:29,870 --> 00:36:32,990 him the Destroyer. Yeah, yeah, pretty much, pretty 589 00:36:32,990 --> 00:36:34,910 much. He runs through shoes like 590 00:36:34,910 --> 00:36:36,850 crazy. That's why he started his shoe 591 00:36:36,850 --> 00:36:38,370 website, hoping he could. Yeah, deal with it. 592 00:36:38,370 --> 00:36:41,210 Yeah, I'm just kidding. For those listening to speak, by 593 00:36:41,250 --> 00:36:45,930 the way, they're ruined shoes. But so yeah, so I mean, there's 594 00:36:45,930 --> 00:36:48,290 really cool things. And then the basic things like 595 00:36:50,330 --> 00:36:53,210 it does come back to injury risk too. 596 00:36:55,220 --> 00:36:59,620 When we started this and we started connecting to lived 597 00:36:59,620 --> 00:37:04,580 experience data to brands, they really didn't want to touch 598 00:37:04,580 --> 00:37:06,860 that. Like it was just a big no no for 599 00:37:06,860 --> 00:37:09,420 the brand, right. There was just a lot of 600 00:37:10,740 --> 00:37:14,500 difficulty legally having to deal with verbiage and language. 601 00:37:14,500 --> 00:37:17,060 And, you know, you're talking about injuries, and that's not 602 00:37:17,060 --> 00:37:19,300 our domain, right. And how do we deal with this? 603 00:37:20,780 --> 00:37:25,080 But, you know, 3 weeks ago, I get a, I get an e-mail from 604 00:37:25,080 --> 00:37:27,440 someone. They're like, hey, if we were to 605 00:37:27,440 --> 00:37:31,840 do this, what would, what would this look like? 606 00:37:31,840 --> 00:37:34,720 And I'm. I'm just like, yes, finally. 607 00:37:34,840 --> 00:37:36,520 Yes. Yes, finally. 608 00:37:37,040 --> 00:37:39,320 Yeah. So I'm like, OK, let's do this 609 00:37:39,320 --> 00:37:40,960 really carefully. And we're going to do this 610 00:37:40,960 --> 00:37:42,840 really slowly. And we're going to be super 611 00:37:42,840 --> 00:37:45,680 methodical about it. We're going to be really simple 612 00:37:46,360 --> 00:37:48,760 because it, I don't think it needs to be complex. 613 00:37:48,760 --> 00:37:53,670 Right, so. It's a weird question, weird 614 00:37:53,670 --> 00:37:56,710 question for you. So you've had this vision and I 615 00:37:56,710 --> 00:37:58,990 think a lot of especially in the like clinical have been like, 616 00:37:59,190 --> 00:38:01,550 you know, if we could just like figure out how to use you, you 617 00:38:01,550 --> 00:38:03,710 pioneer, right? Like how do we use this data? 618 00:38:04,110 --> 00:38:05,590 What do you think? And you may have already 619 00:38:05,590 --> 00:38:07,150 mentioned it, but I'm just curious what do you think the 620 00:38:07,150 --> 00:38:09,630 turning point was for a lot of these companies finally go 621 00:38:10,190 --> 00:38:14,630 actually I think this, you know, yeah, let's take this. 622 00:38:14,630 --> 00:38:16,110 What do you think the turning point was? 623 00:38:16,350 --> 00:38:18,230 Yeah. Because I think there is, 624 00:38:20,600 --> 00:38:25,760 there's a big disconnect between what they're capturing in the 625 00:38:25,760 --> 00:38:28,480 lab and then what they're what actually is occurring in the 626 00:38:28,480 --> 00:38:31,920 wild, right. And we know this to be true from 627 00:38:32,040 --> 00:38:36,640 what people say is often very different than what people do, 628 00:38:36,640 --> 00:38:39,280 right. And so they're capturing a lot 629 00:38:39,280 --> 00:38:42,400 of information and a lot of that's done qualitatively 630 00:38:42,400 --> 00:38:47,260 through subjective surveys, but they get the shoe back and it'd 631 00:38:47,260 --> 00:38:50,940 be like hardly worn, but you know, they said they ran 500 632 00:38:50,940 --> 00:38:54,580 miles on and they're like, like how is that going to help me 633 00:38:54,820 --> 00:38:58,380 building a better shoe for a greater population, right. 634 00:38:59,940 --> 00:39:05,780 And so I think it it always starts, it's easier to start in 635 00:39:05,780 --> 00:39:10,380 the innovation and R&D departments within these brands 636 00:39:10,380 --> 00:39:15,570 because you're not always scared of the of lots of big data, 637 00:39:15,570 --> 00:39:17,250 right. They like are used to using 638 00:39:17,250 --> 00:39:21,410 numbers and and like having a little bit of chaos as you know 639 00:39:21,410 --> 00:39:25,330 in your PhD work like in dealing with like the uncertainty of 640 00:39:26,090 --> 00:39:29,530 what you're trying to study and like how things just don't 641 00:39:29,610 --> 00:39:31,970 always go right. They're okay with like that 642 00:39:31,970 --> 00:39:35,910 stuff, right. So that was the turning point 643 00:39:35,910 --> 00:39:39,350 was like, hey, we need to figure out actually what's going on out 644 00:39:39,350 --> 00:39:41,430 there. And like we need to be able to 645 00:39:41,630 --> 00:39:45,350 communicate better with the the people that we're trying to 646 00:39:46,230 --> 00:39:48,230 bring into our brand and take care of. 647 00:39:48,230 --> 00:39:51,630 And the only way to do that is actually to capture their lived 648 00:39:51,630 --> 00:39:57,990 experience data in a way that is authentic and, you know, 649 00:39:57,990 --> 00:40:02,100 personal, so that that. It it's been it's takes it's 650 00:40:02,100 --> 00:40:05,260 taken a while and it's still like an educational process for 651 00:40:05,260 --> 00:40:08,300 these brands because it's so different than the the status 652 00:40:08,300 --> 00:40:11,980 quo right. And so but I'm I'm very 653 00:40:13,500 --> 00:40:20,740 thankful. I'm honestly like you know just 654 00:40:20,740 --> 00:40:24,300 giddy every time I get to hang out with these individuals and 655 00:40:24,380 --> 00:40:27,340 and all these different brands to get like a little peek 656 00:40:27,340 --> 00:40:31,880 underneath the hood of what's going on and what's potentially 657 00:40:31,880 --> 00:40:36,640 happening in the future, right? And and it's it's just super 658 00:40:36,640 --> 00:40:40,240 exciting one just because I'm a running nerd and like what 659 00:40:40,240 --> 00:40:44,600 better thing for a running nerd to just hang out with people in 660 00:40:44,600 --> 00:40:46,280 these brands right. And talk shop. 661 00:40:46,920 --> 00:40:49,680 Yeah, it is super. It's also really great that like 662 00:40:49,680 --> 00:40:52,040 just like yourself, all these people are actually really 663 00:40:52,040 --> 00:40:55,080 awesome human beings. Having had them on the podcast 664 00:40:55,400 --> 00:40:57,960 been 4 shifted, beat a couple of them in person, like they're 665 00:40:57,960 --> 00:40:59,920 really cool. So it's it's not surprising to 666 00:40:59,920 --> 00:41:03,360 me at all that yourself and a lot of these wonderful people 667 00:41:03,360 --> 00:41:05,160 are like coming up with the sibling, How do we just 668 00:41:05,160 --> 00:41:06,840 basically at the end of the day is how do we make the world a 669 00:41:06,840 --> 00:41:09,200 better place, right? We get people more active. 670 00:41:09,520 --> 00:41:12,790 We keep them active. But it's the challenges like you 671 00:41:12,790 --> 00:41:15,150 know that engagement figuring out what to do. 672 00:41:15,470 --> 00:41:17,750 I'm this is slightly off topic. I'm laughing when you're 673 00:41:17,750 --> 00:41:21,230 mentioning like the chaos and learning to write that as 674 00:41:21,230 --> 00:41:24,950 someone who I would I should track my heart rate metrics 675 00:41:24,950 --> 00:41:27,550 while I'm testing people as I'm panicking and trying to keep a 676 00:41:27,550 --> 00:41:29,550 straight face as something's crashing and I'm trying to 677 00:41:29,550 --> 00:41:31,670 manage that at the same time. Sure, nobody told me this is 678 00:41:31,670 --> 00:41:33,910 going to be this stressful, like oh you just collect this data 679 00:41:33,910 --> 00:41:36,990 and not like oh, Qualis is Our motion capture has crashed for 680 00:41:36,990 --> 00:41:41,130 the 8th time today and the. The AMT, I start connecting 681 00:41:41,530 --> 00:41:45,410 because they're having a temper tent, it's like so yeah it's 682 00:41:45,410 --> 00:41:49,210 learning to ride that chaos which I think having that data, 683 00:41:49,210 --> 00:41:52,930 right the chaos of either a brand or a clinician talking to 684 00:41:52,930 --> 00:41:55,850 somebody going how like you got so much going on in your life, 685 00:41:55,850 --> 00:41:59,130 how do we start organizing this. And I think that's kind of what 686 00:41:59,130 --> 00:42:00,810 I see. So you're organizing this into 687 00:42:00,810 --> 00:42:04,450 bite size chunks. You can go, oh, we can do ice, 688 00:42:04,450 --> 00:42:09,000 we see this, we see this. Here's what we as a team team, 689 00:42:09,000 --> 00:42:12,120 including the person that's providing the data, can go, hey, 690 00:42:12,120 --> 00:42:14,080 this is what we might be able to do with this, which is really 691 00:42:14,080 --> 00:42:15,320 cool. Yeah. 692 00:42:15,720 --> 00:42:20,730 I, I some, yeah. That can get dangerous because I 693 00:42:20,730 --> 00:42:24,170 usually in the run wanted to like go down those rabbit holes 694 00:42:24,210 --> 00:42:27,610 because you there's so much that's possible, right. 695 00:42:27,930 --> 00:42:31,850 But then I have to step back and say, OK, let's let's just keep 696 00:42:31,850 --> 00:42:34,850 this simple. That's like let's walk, run, you 697 00:42:35,330 --> 00:42:39,970 know, that's crawl, walk and run in that in that order and you 698 00:42:39,970 --> 00:42:43,560 know so. But yeah it is, it is pretty, 699 00:42:43,880 --> 00:42:46,400 pretty exciting. We're learning as a brand though 700 00:42:46,400 --> 00:42:53,040 that we actually need to make it the process of this simple 701 00:42:53,040 --> 00:43:00,200 because you throw sample level data on the table of someone or 702 00:43:00,200 --> 00:43:04,080 workout level or a thing called we call it snapshots which is 703 00:43:04,080 --> 00:43:09,410 like a snapshot of someone's yeah, three month history and 704 00:43:09,410 --> 00:43:13,370 it's overwhelming, right. And so we've learned to like 705 00:43:13,370 --> 00:43:17,250 step back and say hey what are you guys trying to do? 706 00:43:18,290 --> 00:43:22,010 Let let us figure out kind of the best way for you guys And 707 00:43:22,010 --> 00:43:26,770 then we'll like serve it on a platter and and we'll take that 708 00:43:26,770 --> 00:43:31,170 to the very end because they like, you know how it's like 709 00:43:31,170 --> 00:43:34,450 today for you is crazy, right. If I said, hey, I'm going to 710 00:43:34,450 --> 00:43:39,210 dump off like, you know, a million points of data on your 711 00:43:40,370 --> 00:43:42,930 in your computer and you're going, you're going to pull it 712 00:43:42,930 --> 00:43:47,210 from our API and like that's just more work for you. 713 00:43:48,570 --> 00:43:52,490 So it's like, it's these problems that I didn't even 714 00:43:52,490 --> 00:43:54,210 consider. I was like, Oh yeah, we just do 715 00:43:54,210 --> 00:43:56,330 this and like, boom, and here's a shoe. 716 00:43:57,530 --> 00:44:02,170 It's like or like here's you do this and like, OK, you push a 717 00:44:02,170 --> 00:44:06,540 button and then oh, you tell them, hey, I need you to do some 718 00:44:06,660 --> 00:44:09,300 calf capacity. Your soleus is super weak or I'm 719 00:44:09,300 --> 00:44:12,500 hypothesizing that you're so because everybody's is right. 720 00:44:12,500 --> 00:44:17,900 So, you know, like it just it's a lot harder than that. 721 00:44:18,020 --> 00:44:21,180 I'm learning, but that's why I have amazing people under my 722 00:44:21,180 --> 00:44:22,700 team that are way smarter than me. 723 00:44:22,700 --> 00:44:27,220 So, so, so they could do that. I just get to talk to people 724 00:44:27,220 --> 00:44:29,780 like you, which is more fun. It is fun, but I. 725 00:44:30,490 --> 00:44:32,610 It's interesting what you mentioned because I what I heard 726 00:44:32,610 --> 00:44:35,090 was there's so many possibilities of things to do 727 00:44:35,410 --> 00:44:38,610 and you got this point, we're like you let the brands tell you 728 00:44:38,610 --> 00:44:41,850 what they need, also probably the individuals what they need, 729 00:44:41,850 --> 00:44:43,570 right. And that that is the hallmark of 730 00:44:43,570 --> 00:44:46,450 a master clinician is when you're younger you generally 731 00:44:46,450 --> 00:44:50,050 tell people what they need. As you get older and you have 732 00:44:50,050 --> 00:44:52,690 more experience, you go. I got all this stuff. 733 00:44:53,050 --> 00:44:56,570 What are your goals? You tell me, you guide me where 734 00:44:56,570 --> 00:44:59,410 do you want to go? And I've seen that that parallel 735 00:44:59,410 --> 00:45:02,450 here, yeah. And this is something that we 736 00:45:02,450 --> 00:45:05,050 also learned very painfully is yes. 737 00:45:05,290 --> 00:45:06,970 And this was with the Power Lab thing. 738 00:45:07,770 --> 00:45:14,650 We were considering that or under the impression that people 739 00:45:14,650 --> 00:45:22,330 wanted to be healthy proactively or but they actually didn't or 740 00:45:22,570 --> 00:45:26,290 want it right like we're we are actually under depression. 741 00:45:26,290 --> 00:45:29,450 They needed it at which they did but they didn't want it. 742 00:45:30,530 --> 00:45:31,850 Like that's not what they wanted. 743 00:45:31,970 --> 00:45:35,370 They they just they didn't. They don't know. 744 00:45:35,410 --> 00:45:37,570 That just isn't part of their vocabulary. 745 00:45:37,650 --> 00:45:40,970 You know right. Based on how society works for 746 00:45:40,970 --> 00:45:41,570 us. So. 747 00:45:43,440 --> 00:45:46,680 So stepping back and transitioning to, you know, 748 00:45:46,680 --> 00:45:48,920 working directly with the brand, it's like okay. 749 00:45:49,680 --> 00:45:56,320 You know, I got to understand that, you know, my needs are not 750 00:45:56,320 --> 00:45:59,480 always the same as their wants or their needs. 751 00:45:59,480 --> 00:46:03,720 My idea of their needs isn't always the same as their wants, 752 00:46:03,720 --> 00:46:06,520 right. So I think that was a very 753 00:46:06,520 --> 00:46:08,440 important thing and it's something that I'm still 754 00:46:08,440 --> 00:46:12,670 learning that I have to just step back and say, okay, I want 755 00:46:12,670 --> 00:46:17,150 to take you here because I think it's important for humanity. 756 00:46:18,670 --> 00:46:20,830 But but that's not maybe where you're at. 757 00:46:20,830 --> 00:46:23,270 And that's OK, but we'll get there at some point. 758 00:46:23,270 --> 00:46:26,270 So let's just let's just deal with what you want right now. 759 00:46:27,710 --> 00:46:29,950 And that films from just asking the right questions. 760 00:46:29,950 --> 00:46:32,470 So it's both you're having to ask the right questions, the 761 00:46:32,470 --> 00:46:34,670 brands are also having to ask the right questions of the 762 00:46:34,670 --> 00:46:36,510 consumer going what do you want, right. 763 00:46:36,510 --> 00:46:38,670 That's where we're testing, that's where all these surveys. 764 00:46:39,170 --> 00:46:42,170 Outreach focus groups come in and going what do they want? 765 00:46:42,170 --> 00:46:46,250 So that's interesting. So a couple quick questions on 766 00:46:46,250 --> 00:46:48,410 that. So if we, if we start at the 767 00:46:48,410 --> 00:46:53,130 individual level, what kind of thing, what kind of metrics have 768 00:46:53,130 --> 00:46:56,490 people wanted and is there anything that they might want 769 00:46:56,490 --> 00:46:58,890 that they don't even know is actually readily available to 770 00:46:58,890 --> 00:47:02,090 them data wise? That's a broad question. 771 00:47:02,720 --> 00:47:05,400 Yeah, that's a really are you you're talking on the consumer 772 00:47:05,600 --> 00:47:06,600 side? Yeah. 773 00:47:06,880 --> 00:47:09,200 Figure let's start with the individual first before we go up 774 00:47:09,240 --> 00:47:12,120 to like for the individual. It's really simple to me. 775 00:47:12,400 --> 00:47:16,080 Yeah, like for the individual. And I hear this all the time and 776 00:47:16,080 --> 00:47:19,320 I know you hear it if you're working with runners, right? 777 00:47:19,320 --> 00:47:24,800 They're like and for us as a clinician usually this is on the 778 00:47:24,800 --> 00:47:27,080 top of the list. Why did I get hurt? 779 00:47:28,920 --> 00:47:33,160 Like what's wrong with me? Tell me the diagnosis, which 780 00:47:33,160 --> 00:47:35,400 doesn't really matter to me, to be honest with you. 781 00:47:36,800 --> 00:47:41,600 And then how do how, How can I make sure that this doesn't 782 00:47:41,600 --> 00:47:44,000 happen again? Unfortunately, that's at the 783 00:47:44,000 --> 00:47:47,560 end. It's not the first thing. 784 00:47:48,640 --> 00:47:53,770 And then close second to that is like, again, tell me that the 785 00:47:53,770 --> 00:47:56,690 best shoe, how many, how many times you have a runner come in 786 00:47:56,690 --> 00:48:01,810 just like, hey, they bring 15 pairs of their their shoes all 787 00:48:01,810 --> 00:48:03,730 in a bag. They throw them on the floor and 788 00:48:03,730 --> 00:48:06,730 they're like, one, can you look at them and I'm like, OK, cool. 789 00:48:07,130 --> 00:48:10,610 And then two, tell me which one, what should I get right. 790 00:48:10,610 --> 00:48:12,490 Like what? What do I need right. 791 00:48:12,490 --> 00:48:15,090 And that's that's kind of a loaded question because there's 792 00:48:15,090 --> 00:48:17,690 a lot into that. But we're starting to see 793 00:48:17,690 --> 00:48:20,210 patterns. We're starting to see patterns 794 00:48:20,210 --> 00:48:25,250 with, you know, shoes that have greater longitudinal bending 795 00:48:25,250 --> 00:48:26,450 stiffness. That's a problem. 796 00:48:26,450 --> 00:48:28,610 We're starting to see patterns with shoes that have higher 797 00:48:28,610 --> 00:48:32,290 stack heights and that are very with very compliant foams, 798 00:48:32,290 --> 00:48:34,450 right. And we're starting to see, you 799 00:48:34,450 --> 00:48:37,850 know, and we've seen patterns with, you know these low profile 800 00:48:37,850 --> 00:48:39,410 shoes for quite some time, right. 801 00:48:39,410 --> 00:48:44,600 And so you're starting like we're starting to kind of see 802 00:48:44,600 --> 00:48:46,920 these things and they're not causative. 803 00:48:46,920 --> 00:48:51,840 But there there's correlation to specific types of injuries and 804 00:48:51,840 --> 00:48:54,920 there's also correlations to specific types of patterns of 805 00:48:54,920 --> 00:48:58,880 movement that that these individuals come to the table 806 00:48:58,880 --> 00:49:04,760 with that are not always easily modifiable based on their motor 807 00:49:04,760 --> 00:49:06,960 patterns and their, their habits, right. 808 00:49:06,960 --> 00:49:10,400 And so, but that to me is super exciting. 809 00:49:10,400 --> 00:49:16,610 And I think that is kind of the future of where this is as an 810 00:49:16,610 --> 00:49:20,050 experience or a service that the shoe company can provide is 811 00:49:20,050 --> 00:49:25,170 like, hey, we noticed and I'm going to tell you, one we 812 00:49:25,170 --> 00:49:29,450 noticed that you have this specific pattern when you run. 813 00:49:29,570 --> 00:49:32,690 And that pattern is, is that you spend a ton of time on the 814 00:49:32,690 --> 00:49:37,010 ground and when you do accelerate, you get longer 815 00:49:37,010 --> 00:49:43,760 instead of of turning over more. And with that specific pattern 816 00:49:44,040 --> 00:49:49,360 and at these specific speeds that you run at, we see more 817 00:49:50,240 --> 00:49:53,240 individuals with Patella femoral pain. 818 00:49:53,760 --> 00:49:56,160 Have you had knee pain? You're like, yes, I'm, I have 819 00:49:56,160 --> 00:49:58,840 knee pain. It starts here and sometimes 820 00:49:58,840 --> 00:50:01,360 it's on the outside of my knee and sometimes it's in the front 821 00:50:01,360 --> 00:50:07,440 of my knee and it's a real pain. And I'm like, yeah, it is a real 822 00:50:07,440 --> 00:50:12,100 pain. And and so we're capturing these 823 00:50:12,100 --> 00:50:14,700 signals uniquely. There's also some signals in the 824 00:50:14,700 --> 00:50:19,580 lower leg that that are starting to like we've seen some 825 00:50:19,580 --> 00:50:24,140 correlations to individuals with bone stress injuries or Achille 826 00:50:24,140 --> 00:50:28,620 sinopathy. And a lot of this work just like 827 00:50:29,220 --> 00:50:32,340 was hypotheses that I had. And then you connect them to 828 00:50:32,340 --> 00:50:35,420 what it says in the literature and then you're like, okay, can 829 00:50:35,420 --> 00:50:39,540 I capture this with this data? Can I capture those signals? 830 00:50:40,010 --> 00:50:43,730 And then with that signal, is it possible to trigger something? 831 00:50:43,730 --> 00:50:45,970 And it is. It's totally is. 832 00:50:46,290 --> 00:50:47,890 There needs to be a lot of work around that. 833 00:50:47,890 --> 00:50:54,170 But one of the biggest aha moments I had as a clinician was 834 00:50:54,170 --> 00:50:58,290 like, you know, everybody told me for the longest time that 835 00:50:58,290 --> 00:51:01,530 like the most common really related injury is knee pain. 836 00:51:02,010 --> 00:51:06,090 You know, like anterior knee pain, you know, in a specific 837 00:51:06,090 --> 00:51:10,790 population. And I was like, I don't know. 838 00:51:10,790 --> 00:51:13,670 I haven't seen a person with Patella femoral pain in five 839 00:51:13,670 --> 00:51:18,110 years. And I was like, and I see that's 840 00:51:18,150 --> 00:51:21,870 my, that's the only, I only see runners. 841 00:51:21,870 --> 00:51:24,830 Like, I don't see anything else but runners. 842 00:51:25,830 --> 00:51:29,830 And I'm like, why is that? And it was like slapped me in 843 00:51:29,830 --> 00:51:33,870 the face. I'm like like all my runners are 844 00:51:33,870 --> 00:51:39,890 like super fast, right? And so when they hit the ground, 845 00:51:39,890 --> 00:51:45,930 they there's very little knee flexion that occurs at at the 846 00:51:45,930 --> 00:51:50,290 tibio femoral joint, right? The loading as a result of that 847 00:51:50,290 --> 00:51:54,090 at the Patello femoral joint is actually quite a bit lower than 848 00:51:54,090 --> 00:51:58,370 someone who's flexing excessively during load during, 849 00:52:00,810 --> 00:52:02,970 you know, loading phase or mid stance. 850 00:52:02,970 --> 00:52:05,530 Right. And I was like, Oh my gosh. 851 00:52:05,530 --> 00:52:08,930 But you know what I do see all the time, bone stress injuries, 852 00:52:09,090 --> 00:52:12,330 Achilles tendonopathy, like everything you can imagine at 853 00:52:12,330 --> 00:52:15,370 the foot, right. And that was like my biggest aha 854 00:52:15,450 --> 00:52:20,690 moment and it was like whoa, can I see this pattern? 855 00:52:20,730 --> 00:52:27,250 Can I take data and see that pattern, capture that signal and 856 00:52:27,450 --> 00:52:29,290 then do something with it proactively? 857 00:52:29,290 --> 00:52:31,690 And I was like, I think I can, like, I think I can. 858 00:52:32,890 --> 00:52:36,820 And now I just need to get these other people who have influence 859 00:52:36,900 --> 00:52:41,580 that other than me is the end of 1 to like do something. 860 00:52:41,580 --> 00:52:43,460 But that's super exciting to me, man. 861 00:52:43,460 --> 00:52:46,500 And like because it isn't rocket science, right? 862 00:52:46,500 --> 00:52:49,900 Like we see it every day. Yeah, it's trying. 863 00:52:49,900 --> 00:52:52,740 It is translating it. Yeah, it's translating it to not 864 00:52:52,740 --> 00:52:55,180 only the world, but like companies and other people 865 00:52:55,180 --> 00:52:57,940 because you know, we're very lucky to have the jobs we do. 866 00:52:57,940 --> 00:53:01,380 We it's we're super awesome. The thing is we always will have 867 00:53:01,380 --> 00:53:02,740 patience. People are always going to get 868 00:53:02,740 --> 00:53:04,180 injured if we can. Always. 869 00:53:04,840 --> 00:53:09,080 If we can cut that down and keep people healthier, that's part of 870 00:53:09,080 --> 00:53:11,280 the prevention part, which I think is really important within 871 00:53:11,280 --> 00:53:14,280 our profession. Even if we reduce the injuries 872 00:53:14,280 --> 00:53:18,000 to like 510%, people are still going to need us, but if we can 873 00:53:18,040 --> 00:53:20,280 help people stay healthier longer. 874 00:53:20,770 --> 00:53:23,090 It's the longterm effect of keeping them act, because the 875 00:53:23,090 --> 00:53:25,730 worst thing people can do is you get over an injury and then you 876 00:53:25,730 --> 00:53:28,730 just stop moving and then you start getting all your other 877 00:53:29,090 --> 00:53:32,890 core mobilities, your high blood pressure, your like diabetes. 878 00:53:32,890 --> 00:53:34,850 So it's like that. And once you go down that road, 879 00:53:34,850 --> 00:53:38,090 it's really hard to dig out. So prevention wise, this makes 880 00:53:38,090 --> 00:53:40,410 total sense to me. Yeah. 881 00:53:40,450 --> 00:53:44,290 So, yeah, So and then you have other components like marketing 882 00:53:44,290 --> 00:53:50,020 and you know which you know is it like it starts to spread but 883 00:53:50,540 --> 00:53:53,780 just more authentically and naturally I think in a like a a 884 00:53:54,900 --> 00:53:58,700 better way, a better way. I like to think of it as a 885 00:53:58,700 --> 00:53:59,980 better way. Yeah, so. 886 00:54:01,260 --> 00:54:04,780 You talked about this a little bit, but so footwear companies 887 00:54:04,780 --> 00:54:08,900 are not only using this to get an understanding of who, who the 888 00:54:08,900 --> 00:54:11,540 the population they're serving right, they're creating product 889 00:54:11,540 --> 00:54:15,820 for, but there's also some talk of going how can we modify this? 890 00:54:16,170 --> 00:54:19,690 To make footwear that better matches people, correct. 891 00:54:19,690 --> 00:54:22,170 Is there anything else that they're they're utilizing this 892 00:54:22,170 --> 00:54:23,970 for in terms of benefiting the consumer? 893 00:54:24,010 --> 00:54:27,490 Yeah. So again you know that we call 894 00:54:27,490 --> 00:54:31,130 that Finder tech and companies are really interested in that, 895 00:54:31,250 --> 00:54:34,210 right. Is like in a in a scalable way. 896 00:54:34,250 --> 00:54:39,210 We're not talking putting someone in a shoes foot scan or 897 00:54:39,210 --> 00:54:42,810 like pressure and soles like that's just not accessible to 898 00:54:42,810 --> 00:54:47,680 the normal individual, right. But but one major company was 899 00:54:47,680 --> 00:54:52,680 just like we're just tired of getting like our customer 900 00:54:52,680 --> 00:54:56,120 service just like getting hammered right now because 901 00:54:56,400 --> 00:54:59,000 people are calling in and they love the brand And you would 902 00:54:59,000 --> 00:55:02,080 know this brand people, it's like a up and coming really cool 903 00:55:02,080 --> 00:55:05,880 brand. But they're like the reason that 904 00:55:05,880 --> 00:55:09,960 we got contact is because their customer service is so fed up 905 00:55:09,960 --> 00:55:13,440 with being asked like, I just, I want to buy a shoe. 906 00:55:13,440 --> 00:55:15,240 I just don't know what shoe to buy, right? 907 00:55:15,240 --> 00:55:19,390 And so I can tell you, one company and this blew me out of 908 00:55:19,390 --> 00:55:21,910 the water, like, I literally almost fell out of my seat. 909 00:55:21,990 --> 00:55:26,390 They're like, man, if we can do this, this and this. 910 00:55:27,150 --> 00:55:34,190 Like if we can, like be able to potentially hypothesize about a 911 00:55:34,190 --> 00:55:39,190 susceptibility to something or a signal that is like, man, they 912 00:55:39,190 --> 00:55:43,560 haven't haven't run in a month. Like can we, you know, could we 913 00:55:43,560 --> 00:55:45,960 send them a survey and say, hey, are you injured right now? 914 00:55:47,320 --> 00:55:51,880 They actually said if we can do that man, then maybe we can 915 00:55:51,880 --> 00:55:54,960 refer them to a physical therapist in the area. 916 00:55:55,720 --> 00:55:57,480 And I almost like, fell out of my chair. 917 00:55:57,480 --> 00:56:02,840 I was like whoa, like a major, major billion dollar brand is 918 00:56:02,840 --> 00:56:06,600 telling me that they want to send their customers to physical 919 00:56:06,600 --> 00:56:11,480 therapy because that is probably good for the brand. 920 00:56:11,520 --> 00:56:15,720 If, you know, I was like the world is changing for the better 921 00:56:15,720 --> 00:56:19,120 and I'm, I'm super excited to be a part of this process. 922 00:56:20,200 --> 00:56:22,760 I've just never heard anything like that before. 923 00:56:22,760 --> 00:56:24,640 I was like. Which it makes sense. 924 00:56:24,640 --> 00:56:26,320 You got to take care. You got to, if you're going to 925 00:56:26,320 --> 00:56:28,320 create a community, you got to take care of your members, 926 00:56:28,320 --> 00:56:29,760 right. And so if they can't run their 927 00:56:29,760 --> 00:56:31,920 injured, right, that they're not going to be happy, right. 928 00:56:31,920 --> 00:56:34,280 So I mean, from a business standpoint, obviously they're 929 00:56:34,280 --> 00:56:36,240 not going to continue running. They're not going to purchase 930 00:56:36,240 --> 00:56:37,890 product. So it makes sense going all 931 00:56:37,890 --> 00:56:40,810 right, how do we keep you healthy and go, Yes, sometimes 932 00:56:40,810 --> 00:56:43,770 people do need help, right? People need to be have self 933 00:56:43,770 --> 00:56:45,810 efficacy, but sometimes they just need that like you said the 934 00:56:45,810 --> 00:56:47,730 hand on the shoulder to go, hey, you know what? 935 00:56:47,770 --> 00:56:50,860 I know this is rough. You are going to get through 936 00:56:50,860 --> 00:56:53,980 this and if you need a little bit of help, here's someone that 937 00:56:53,980 --> 00:56:56,860 might be helpful for you. Like, that's awesome, right? 938 00:56:57,020 --> 00:56:57,860 Yeah. About support. 939 00:56:57,860 --> 00:56:58,700 Totally. Yeah. 940 00:56:58,740 --> 00:57:01,180 So they would, they would call that a service, right. 941 00:57:01,180 --> 00:57:04,420 And so you have product personalization as one piece of 942 00:57:04,420 --> 00:57:05,740 what brands you're looking to do. 943 00:57:05,740 --> 00:57:08,260 And then you have another piece would be a service. 944 00:57:08,260 --> 00:57:12,330 So that would be a service. And then you have the third 945 00:57:12,330 --> 00:57:15,210 piece, which would be like creating experiences, right? 946 00:57:15,210 --> 00:57:19,130 And so like from a community standpoint, how do I, how do I 947 00:57:19,130 --> 00:57:25,970 get people that are of like mind and and like I guess physical 948 00:57:27,330 --> 00:57:32,610 ability and put them together in an opportunity where like 949 00:57:32,610 --> 00:57:34,890 they're probably going to just enjoy each other's company, 950 00:57:34,890 --> 00:57:40,720 right. I often say that you know like 951 00:57:41,160 --> 00:57:44,280 all sports are made-up of movement but not all movement 952 00:57:44,280 --> 00:57:47,680 needs to be sport, right. And and so if I translate that 953 00:57:47,680 --> 00:57:52,640 to the running world is like all runners run but not all runners 954 00:57:52,640 --> 00:57:54,960 need to be Boston Marathoners right. 955 00:57:55,080 --> 00:58:02,560 And so I really have a even though I work with kind of some 956 00:58:02,920 --> 00:58:07,360 the higher end, you know runner like I really have a heart for 957 00:58:07,480 --> 00:58:13,230 just people who you know use running to feel better and and 958 00:58:13,270 --> 00:58:17,510 reduce stress. And because it in theory that's 959 00:58:17,510 --> 00:58:20,270 like the majority of runners, right. 960 00:58:20,270 --> 00:58:24,750 Like, if you look at the Boston Marathoners like, it's such a 961 00:58:24,750 --> 00:58:30,510 small sliver of the actual population that that utilizes 962 00:58:30,510 --> 00:58:33,110 their shoes. Even though, you know, we're 963 00:58:33,110 --> 00:58:36,860 interested in the the bouncy, foamy, resilient things that are 964 00:58:36,860 --> 00:58:43,380 stiff and do cool things for people, you know, most people 965 00:58:43,380 --> 00:58:44,980 shouldn't probably buy those shoes. 966 00:58:45,740 --> 00:58:48,140 I'm happy to hear that. I know we get super excited 967 00:58:48,140 --> 00:58:51,300 about those, but we know there's always appropriate. 968 00:58:51,300 --> 00:58:53,940 So and it's it reminds me when I was talking to Jen from Brooks, 969 00:58:53,940 --> 00:58:56,580 we had her on here and she was awesome and it was like, yes, 970 00:58:56,580 --> 00:58:58,700 you know, we get a lot of focus on the elite runners and there's 971 00:58:58,700 --> 00:59:00,460 nothing wrong with that. We have to realize that the 972 00:59:00,460 --> 00:59:02,980 majority of people aren't elite, and that's OK. 973 00:59:03,300 --> 00:59:05,940 But we want to make sure that they know that we are designing 974 00:59:05,940 --> 00:59:09,980 product for them and we want to make sure everybody feels heard, 975 00:59:10,180 --> 00:59:12,220 everybody has a product and that's really important not just 976 00:59:12,220 --> 00:59:14,940 from a clinical standpoint to go you know one of the you 977 00:59:14,940 --> 00:59:17,940 mentioned this earlier right during the examination your 978 00:59:17,940 --> 00:59:21,020 first visit gaining trust, but also making sure that person 979 00:59:21,020 --> 00:59:24,580 feels heard especially in a society as in the medical 980 00:59:24,580 --> 00:59:28,180 community like that's people get not heard all the time, they get 981 00:59:28,180 --> 00:59:30,260 talked over stuff like that and I'm sure. 982 00:59:30,770 --> 00:59:32,610 People sometimes feel that, like that, but in the running 983 00:59:32,610 --> 00:59:37,210 community like, oh, I'm not an ex fast marathoner or 5K or why 984 00:59:37,210 --> 00:59:39,130 are they going to pay attention? To me it's like, well, no, we 985 00:59:39,130 --> 00:59:41,770 want you to be heard. And so I think this allows that 986 00:59:41,770 --> 00:59:43,490 connection. Yeah. 987 00:59:43,490 --> 00:59:47,850 And you know, I love Jen to death, like and she is 988 00:59:48,170 --> 00:59:52,490 absolutely the biggest proponent to, you know, serving that 989 00:59:52,490 --> 00:59:55,730 population. And that's why I think she's at 990 00:59:55,730 --> 00:59:59,770 Brooks and she's doing what she does and and that's why Brooks. 991 01:00:00,810 --> 01:00:04,770 You know, absolutely knows who they are as a brand and and and 992 01:00:04,770 --> 01:00:08,130 because of that, that's why they're really successful, 993 01:00:08,130 --> 01:00:12,610 right. And so I think they'll continue 994 01:00:12,610 --> 01:00:17,610 to serve that population as well as others very well as a result 995 01:00:17,610 --> 01:00:20,210 of people like Jim and others on on that team. 996 01:00:20,250 --> 01:00:24,050 Yeah, but that's awesome. So, so you got how the companies 997 01:00:24,050 --> 01:00:26,700 are using this? And I mentioned earlier that a 998 01:00:26,700 --> 01:00:30,220 lot of individuals might not know what's available to them. 999 01:00:30,220 --> 01:00:32,500 So if you would, you know, we're going to go back to the rule of 1000 01:00:32,500 --> 01:00:34,620 three, right? If you could tell people, hey, 1001 01:00:34,620 --> 01:00:37,620 there's two or three things, two or three metrics that you just 1002 01:00:37,620 --> 01:00:40,900 have easily available to you that might be worth paying 1003 01:00:40,900 --> 01:00:43,300 attention to you. What were the, what would those 1004 01:00:43,300 --> 01:00:46,580 two to three metrics be? And notes, it's we're asking a 1005 01:00:46,580 --> 01:00:48,810 directed question. Rather than getting the 1006 01:00:48,810 --> 01:00:51,450 information of going, yeah, you might, you might already know, 1007 01:00:51,450 --> 01:00:54,130 but like, what do you think would be most helpful for people 1008 01:00:54,130 --> 01:00:55,610 that don't know to pay attention to? 1009 01:00:56,210 --> 01:00:59,050 Yeah, I'm going to really generalize this because and I'm 1010 01:00:59,050 --> 01:01:04,090 going to take it away from just completely like a specific 1011 01:01:04,090 --> 01:01:08,410 variable because I think the importance of lived experience 1012 01:01:08,410 --> 01:01:12,090 is translating this into something that's accessible and 1013 01:01:12,090 --> 01:01:13,770 actionable for a real human, right. 1014 01:01:14,930 --> 01:01:20,270 And so if I said, hey, you know, we know that there's some decent 1015 01:01:20,270 --> 01:01:24,390 evidence of as it relates to cadence and you know, 1016 01:01:24,550 --> 01:01:29,350 manipulation of of gait around that and and specifically with 1017 01:01:29,350 --> 01:01:34,110 people who have pain, maybe less so with people who don't, right. 1018 01:01:34,110 --> 01:01:39,030 And and specifically around the knee or maybe even into the calf 1019 01:01:39,030 --> 01:01:40,750 or some plantar facial issues, right. 1020 01:01:40,750 --> 01:01:45,720 And so and that's cool, but that requires a little bit of me and 1021 01:01:45,720 --> 01:01:48,480 you being around them and helping them through that 1022 01:01:48,480 --> 01:01:53,320 process potentially, right. But I would say, hey, I got a 1023 01:01:53,320 --> 01:01:56,440 thing and I, I, I, I call it the three C's. 1024 01:01:56,520 --> 01:02:01,920 And and these three C's I think are probably what I define as 1025 01:02:01,920 --> 01:02:05,480 being pretty important and we're going to simplify this for you. 1026 01:02:06,680 --> 01:02:12,140 The three C's consist of consistency, right, correct 1027 01:02:12,140 --> 01:02:15,220 loading whatever that means and we'll describe it. 1028 01:02:15,300 --> 01:02:21,860 And then what I call control and so consistency and we've done 1029 01:02:21,860 --> 01:02:25,220 this study with one of these brands is like looking at the 1030 01:02:25,300 --> 01:02:28,980 correlation of consistency to running injury. 1031 01:02:28,980 --> 01:02:34,180 And it's like extremely clear like people coming into a 1032 01:02:34,180 --> 01:02:38,460 specific thing and or coming out of it if if they aren't 1033 01:02:39,120 --> 01:02:41,640 consistent. We define consistency is running 1034 01:02:41,640 --> 01:02:47,360 at least three days a week in a seven day period over a certain 1035 01:02:47,360 --> 01:02:51,360 time span. They just happen to get injured 1036 01:02:51,360 --> 01:02:54,040 more and it's like pretty intuitive. 1037 01:02:55,320 --> 01:02:58,760 So let's, hey, let's just, if you're going to run, I don't 1038 01:02:58,760 --> 01:03:03,240 care about volume, let's just focus on kind of getting 1039 01:03:03,240 --> 01:03:06,320 consistent and that looks like this and then let's build upon 1040 01:03:06,320 --> 01:03:10,830 this. And so that's important and you 1041 01:03:10,830 --> 01:03:14,910 know you can use data to do that and a brand, this brand will use 1042 01:03:14,910 --> 01:03:18,590 that data to do this. And then there's correct 1043 01:03:18,590 --> 01:03:20,830 loading. And what does that mean, you 1044 01:03:20,870 --> 01:03:24,950 know, and that means, like, well, if I am going to run and 1045 01:03:24,950 --> 01:03:27,710 I'm going to be consistent, I probably need to do it in this 1046 01:03:27,710 --> 01:03:30,790 fashion. And that fashion is like, well, 1047 01:03:30,790 --> 01:03:33,350 I'm going to focus on frequently moving. 1048 01:03:34,530 --> 01:03:37,050 And that movement might be in the form of walking first. 1049 01:03:37,050 --> 01:03:38,890 So that movement might be in the form of running. 1050 01:03:38,890 --> 01:03:41,530 And we're going to capture those signals and help you through 1051 01:03:41,530 --> 01:03:43,970 that process. And then the next thing is like, 1052 01:03:43,970 --> 01:03:46,770 well, I might add a little bit more volume onto that and that 1053 01:03:46,770 --> 01:03:50,530 will just naturally happen. And at the very end, I might 1054 01:03:51,330 --> 01:03:53,730 tickle that with some speed every now and then. 1055 01:03:53,850 --> 01:03:57,010 And this is how we'll do that. And that's how we're going to 1056 01:03:57,010 --> 01:04:01,570 correctly load and we might have some fancy stuff that some fancy 1057 01:04:01,570 --> 01:04:09,180 researchers did, You know that that is cool, but like that's 1058 01:04:09,180 --> 01:04:11,780 pretty basic, right? And then the last thing is 1059 01:04:11,780 --> 01:04:13,500 control. What does control look like? 1060 01:04:13,500 --> 01:04:18,900 Well, if I go out for a run, what do? 1061 01:04:19,300 --> 01:04:21,780 And I'm going to ask you this, Matt, this is your test. 1062 01:04:24,180 --> 01:04:30,780 What do most runners do from from an intensity standpoint or 1063 01:04:30,780 --> 01:04:33,540 like a pacing standpoint when they go out for a run? 1064 01:04:33,540 --> 01:04:38,620 Like what's the most common error that they have at every 1065 01:04:38,620 --> 01:04:40,220 level? And I can think of one of my 1066 01:04:40,220 --> 01:04:42,860 professional runners right now is like really bad at this. 1067 01:04:44,340 --> 01:04:46,140 And I can think of 1 that's changed. 1068 01:04:46,140 --> 01:04:50,340 And like she's, you know, will be in Budapest this, this in a 1069 01:04:50,340 --> 01:04:53,780 month or so. What's the most common thing? 1070 01:04:54,560 --> 01:04:57,280 I will say this, and hopefully I'm not wrong because I'm going 1071 01:04:57,280 --> 01:04:59,880 to call my wife out who is also a professional athlete at the 1072 01:04:59,880 --> 01:05:03,520 moment and hated training with me because I do the exact 1073 01:05:03,520 --> 01:05:06,240 opposite because I was very lucky to have some very fast 1074 01:05:06,240 --> 01:05:10,040 people teach me this is that people start out way too hard. 1075 01:05:10,280 --> 01:05:13,000 They whether it's a race, whether it's their run, they 1076 01:05:13,200 --> 01:05:15,440 start out way too hard rather than warming up into it. 1077 01:05:15,440 --> 01:05:19,040 And my wife hated that, that I would start out 910 minute pace 1078 01:05:19,040 --> 01:05:22,500 and then finish faster. Yeah, yeah. 1079 01:05:22,500 --> 01:05:26,220 It's just like like their paces like probably too high, 1080 01:05:26,220 --> 01:05:27,940 especially on their easy days, right? 1081 01:05:27,940 --> 01:05:32,460 Like they're they're you know let's say someone, and I have 1082 01:05:32,660 --> 01:05:38,060 this woman is really amazing, but she's like was running her 1083 01:05:38,060 --> 01:05:44,460 easy paces like maybe maybe coming under 7 minute pace like 1084 01:05:44,660 --> 01:05:49,940 after and a really really really excruciating hard workout. 1085 01:05:50,020 --> 01:05:53,810 Right. And like what she said was like 1086 01:05:53,810 --> 01:05:59,650 the one thing that completely changed my game, It was like not 1087 01:05:59,650 --> 01:06:06,010 running any of my easy days under 8 minute pace, which felt 1088 01:06:06,010 --> 01:06:09,410 like I was walking. Like she literally said that 1089 01:06:09,410 --> 01:06:15,450 felt like I was walking but I but I am now crushing it and 1090 01:06:15,450 --> 01:06:17,570 that's Elise cranny to be honest with you. 1091 01:06:18,610 --> 01:06:21,970 So like and you know she's pretty good. 1092 01:06:22,530 --> 01:06:25,050 And if she. Can, you know, Understatement. 1093 01:06:25,050 --> 01:06:28,770 But yeah, yeah, if she can run her easy runs at 8 minute pace, 1094 01:06:28,770 --> 01:06:31,650 like why shouldn't other people run really easy, right. 1095 01:06:31,650 --> 01:06:38,730 And so those those three things I would tell every human and I 1096 01:06:38,730 --> 01:06:41,370 would tell them over and over again until they got it And then 1097 01:06:41,370 --> 01:06:45,370 you you can light obviously we we we can layer in data to this 1098 01:06:45,370 --> 01:06:50,820 and signals and triggers and and if I'm going to tell the brand, 1099 01:06:50,820 --> 01:06:53,660 hey, where should you go as it relates to prevention of 1100 01:06:53,660 --> 01:06:56,980 injuries, I'm going to start talking to him about the three 1101 01:06:56,980 --> 01:06:59,060 C's and maybe I have already done that. 1102 01:07:00,700 --> 01:07:03,700 And it sounds like when talking to people using this data is 1103 01:07:03,700 --> 01:07:06,780 this is already available. So if you have a GPS watch or a 1104 01:07:06,780 --> 01:07:09,300 phone like, you can track your mileage and you can start 1105 01:07:09,300 --> 01:07:12,420 looking at patterns going hey, you know what talking about. 1106 01:07:13,500 --> 01:07:16,100 Consistency, right? How many days a week are you 1107 01:07:16,100 --> 01:07:17,900 running? Or the other thing is, if you're 1108 01:07:17,900 --> 01:07:22,140 running frequently, do you have huge spikes in that consistency 1109 01:07:22,140 --> 01:07:24,420 of volume? Those spikes are where those 1110 01:07:24,420 --> 01:07:27,540 injuries typically tend to happen or after, because it's 1111 01:07:27,540 --> 01:07:29,780 your body's. The more consistency you are 1112 01:07:29,780 --> 01:07:32,860 with the more like equivalent load, the more your body's kind 1113 01:07:32,860 --> 01:07:34,220 of ready for it. It's those big spikes. 1114 01:07:34,220 --> 01:07:36,540 Got to be really careful. Little spikes, OK, That's how 1115 01:07:36,700 --> 01:07:38,700 you know if you're doing a workout or that's how you push 1116 01:07:38,700 --> 01:07:41,540 yourself to get better. But it's got to be appropriate. 1117 01:07:41,540 --> 01:07:45,330 You got to heal from it. The the second was it, it was 1118 01:07:45,810 --> 01:07:50,090 consistency correct load, knowing going, hey, am I 1119 01:07:50,090 --> 01:07:53,450 suddenly jumping up or am I doing things appropriately, 1120 01:07:53,450 --> 01:07:56,610 slowly building which our bodies don't do this really well. 1121 01:07:56,850 --> 01:07:59,890 They do this really well. So again, looking at your 1122 01:07:59,890 --> 01:08:03,690 mileage going week by week, what's happening And then the 1123 01:08:03,690 --> 01:08:07,930 final thing is control going. You get the watches, the phones. 1124 01:08:07,930 --> 01:08:11,130 They all look at pace and going, How do I know what I'm doing? 1125 01:08:11,460 --> 01:08:12,980 And how do I keep that under control? 1126 01:08:12,980 --> 01:08:17,660 So instead of running 630 pace on an easy day, you go, that's 1127 01:08:17,660 --> 01:08:20,300 not necessary, especially from a load management standpoint. 1128 01:08:20,300 --> 01:08:23,140 That's going, what's the purpose of today if it's to recover? 1129 01:08:23,420 --> 01:08:26,300 Let's make sure I'm comfortable with this. 1130 01:08:26,340 --> 01:08:29,819 I'm controlling this. I'm not letting my things get 1131 01:08:29,819 --> 01:08:31,100 ahead of me. Yeah. 1132 01:08:31,100 --> 01:08:34,020 And as a physio, this is like, right up our alley, right. 1133 01:08:34,100 --> 01:08:37,899 I mean, right, when we look at a treatment stem like we're, you 1134 01:08:37,899 --> 01:08:41,220 know the biggest thing is we're building awareness around 1135 01:08:41,220 --> 01:08:44,180 something, right. And then with awareness where we 1136 01:08:44,180 --> 01:08:47,420 build in context maybe with a movement or maybe without a 1137 01:08:47,420 --> 01:08:53,200 movement and then we're working to transfer you know, you know 1138 01:08:53,760 --> 01:08:58,399 some transfer that idea into something that's more, more 1139 01:08:58,439 --> 01:09:00,439 makes sense, which is the act of running. 1140 01:09:00,880 --> 01:09:03,960 And then we're looking to stabilize this over time, right. 1141 01:09:03,960 --> 01:09:07,200 And that's like a very basic treatment model that we go 1142 01:09:07,200 --> 01:09:10,040 through. And so that awareness piece is 1143 01:09:10,040 --> 01:09:13,439 really big. And for my runners, if we're 1144 01:09:13,439 --> 01:09:17,920 talking about pace, I'm talking about is pace. 1145 01:09:17,920 --> 01:09:22,729 And this is like beyond this, but I think it's cool is pace. 1146 01:09:23,210 --> 01:09:25,649 Does your pace match your effort? 1147 01:09:25,689 --> 01:09:29,609 And if it doesn't like there's something wrong, right? 1148 01:09:29,609 --> 01:09:33,010 And that can be like you're tired, you're under recovered, 1149 01:09:34,330 --> 01:09:38,410 you traveled, you fought with your boyfriend or girlfriend or 1150 01:09:38,410 --> 01:09:42,810 other, right? And so, you know those signals 1151 01:09:42,810 --> 01:09:46,569 and that and building attention around specific, what I call 1152 01:09:46,569 --> 01:09:51,170 vital signs or points of awareness is really important. 1153 01:09:51,609 --> 01:09:54,450 But that's for another completely different podcast. 1154 01:09:54,450 --> 01:09:56,890 Sorry. No, you don't support. 1155 01:09:56,890 --> 01:09:58,690 You're speaking my language right now. 1156 01:09:58,690 --> 01:10:00,450 And it's gonna be dangerous because it's gonna be a four 1157 01:10:00,450 --> 01:10:04,170 hour podcast if we're not. Yeah, we better end this. 1158 01:10:04,170 --> 01:10:07,770 But at some point, I want to talk fancy shoes. 1159 01:10:07,810 --> 01:10:08,610 Fancy. Yeah. 1160 01:10:09,350 --> 01:10:10,910 We will. We'll definitely have to have 1161 01:10:10,910 --> 01:10:12,310 you back. We'll definitely have you on. 1162 01:10:12,430 --> 01:10:16,110 Jeff, this was phenomenal. I do really quickly before we we 1163 01:10:16,110 --> 01:10:19,270 finish up here, want to give people a location to find you. 1164 01:10:19,270 --> 01:10:23,310 So Dash LX has own website. There's also an Instagram face 1165 01:10:23,310 --> 01:10:25,750 for Dash LX. You can be found on Instagram at 1166 01:10:25,750 --> 01:10:27,590 Jeff Moran at Jeffparino, correct. 1167 01:10:27,590 --> 01:10:29,790 Is there any other ways to be able to reach out? 1168 01:10:30,210 --> 01:10:31,890 Or to find you some of this cool stuff. 1169 01:10:32,050 --> 01:10:35,970 Yeah, I mean they can, they can always, if they have interests 1170 01:10:35,970 --> 01:10:39,770 or they want to chat about anything, they can always e-mail 1171 01:10:39,770 --> 01:10:46,610 me at jefflx.com. And yeah, I mean, I love to have 1172 01:10:46,610 --> 01:10:49,980 a chat, so don't be shy. Yeah. 1173 01:10:50,340 --> 01:10:53,180 Also if you got to check out his LinkedIn, I love your profile 1174 01:10:53,180 --> 01:10:55,060 picture. It just looks so professional 1175 01:10:55,060 --> 01:10:56,860 and I'm like this is this is a LinkedIn photo. 1176 01:10:56,860 --> 01:10:58,500 It's great. So you can also find them on 1177 01:10:58,500 --> 01:11:00,660 LinkedIn. But Jeff, thank you so much for 1178 01:11:00,940 --> 01:11:01,940 coming on. Yeah. 1179 01:11:02,140 --> 01:11:04,540 What I really love to do is just surf, you know? 1180 01:11:04,540 --> 01:11:06,540 So. So if you do go to my LinkedIn, 1181 01:11:06,540 --> 01:11:10,180 you'll just see a guy surfing and run. 1182 01:11:10,380 --> 01:11:11,500 That's what that is. Okay. 1183 01:11:11,540 --> 01:11:13,100 Got it, got it, got it. All right. 1184 01:11:13,460 --> 01:11:15,980 Well, Jeff, thank you so much. It was awesome to pick your 1185 01:11:15,980 --> 01:11:18,740 brain and awesome to hear not only what you're doing, but what 1186 01:11:18,740 --> 01:11:20,980 brands are doing. And it's nice to also know that 1187 01:11:21,500 --> 01:11:25,780 that we people do care, right? In a situation for people, you 1188 01:11:25,780 --> 01:11:28,140 know, where we're having more trouble worldwide with people 1189 01:11:28,140 --> 01:11:30,780 feeling isolated. There are situations where you 1190 01:11:30,780 --> 01:11:34,580 can feel a part of something and you can also know that people do 1191 01:11:34,580 --> 01:11:36,020 care. And it's it's not just because 1192 01:11:36,020 --> 01:11:37,860 they're trying to sell you a product, it's because they want 1193 01:11:37,860 --> 01:11:40,020 you to be healthy. Because we're getting this point 1194 01:11:40,020 --> 01:11:44,060 where there is positive in the world, like longevity and we can 1195 01:11:44,060 --> 01:11:46,440 do this. Any last words by the way before 1196 01:11:46,440 --> 01:11:49,440 we land this? No, I think you know, at some 1197 01:11:49,440 --> 01:11:53,000 point people will have more of an opportunity to be a part of 1198 01:11:53,000 --> 01:11:57,280 these things and and just look out with your favorite brand and 1199 01:11:57,280 --> 01:11:59,320 that'll be coming to you soon, hopefully. 1200 01:11:59,960 --> 01:12:03,680 So yeah, thank you for the opportunity Matt, and good luck 1201 01:12:03,680 --> 01:12:07,360 on your research and and hey, let's do a shout out to Rich 1202 01:12:07,360 --> 01:12:10,440 Willie, because Rich really is. I love Rich. 1203 01:12:11,120 --> 01:12:14,460 Rich, if you're listening dude, you got to help Matt out. 1204 01:12:14,460 --> 01:12:17,100 He needs your help, man. All right, So we talked about 1205 01:12:17,100 --> 01:12:18,300 this for about. I'm going to call Rich. 1206 01:12:18,300 --> 01:12:20,620 I think Rich, you talked with, I'm going to leave this on and 1207 01:12:20,620 --> 01:12:22,420 we'll see if Vijay keeps this on there. 1208 01:12:22,420 --> 01:12:24,740 Rich, I know you were talking for sure. 1209 01:12:25,060 --> 01:12:27,340 I know they were. He and Nathan were talking about 1210 01:12:27,340 --> 01:12:29,580 coming out and doing a podcast. Rich, I don't know if you know 1211 01:12:29,580 --> 01:12:33,260 this, but I emailed you early on to my PhD asking if you'd be on 1212 01:12:33,260 --> 01:12:36,260 my PhD committee, which still open offer. 1213 01:12:36,640 --> 01:12:39,080 By the way, because I'm still looking like just to make sure I 1214 01:12:39,080 --> 01:12:41,720 have a final committee member but you never responded. 1215 01:12:41,720 --> 01:12:44,160 So I know you're come on rich Rich, I'm. 1216 01:12:44,280 --> 01:12:47,520 I know it's not like, yeah, it's not like the systematic review I 1217 01:12:47,520 --> 01:12:50,240 just published like reference to like 40 times or anything. 1218 01:12:50,240 --> 01:12:52,400 Like that's not you. Like you inspired my entire 1219 01:12:52,400 --> 01:12:54,640 project. But you know, hey, you're out 1220 01:12:54,640 --> 01:12:55,920 there. I'm curious. 1221 01:12:55,920 --> 01:12:58,680 We'd love to have you on too, but I will connect you to Rich. 1222 01:12:58,680 --> 01:13:00,360 And Rich is like my favorite person. 1223 01:13:00,360 --> 01:13:03,840 He's at one of the most beautiful humans, so he'll get a 1224 01:13:03,840 --> 01:13:05,810 hold of you, I'm sure. All right, Matt. 1225 01:13:05,890 --> 01:13:08,530 And for those, for those listing by the way, you got it, Rich. 1226 01:13:08,530 --> 01:13:11,090 Willie is another phenomenal place, but we'll wrap this up. 1227 01:13:11,090 --> 01:13:12,570 Thank you everybody, so much for listening. 1228 01:13:12,690 --> 01:13:15,210 We have, as always, we've got new contact coming out every 1229 01:13:15,210 --> 01:13:17,010 single week, usually released on Wednesday. 1230 01:13:17,210 --> 01:13:19,170 You can find us on all the different platforms. 1231 01:13:19,170 --> 01:13:21,730 So it's like you can find Jeff and on different platforms to be 1232 01:13:21,730 --> 01:13:24,870 at LinkedIn, which Bach has. Done a crazy good job of 1233 01:13:25,190 --> 01:13:27,950 Instagram, Facebook, Spotify, all different places. 1234 01:13:27,950 --> 01:13:29,830 YouTube that you can consume stuff. 1235 01:13:30,030 --> 01:13:32,790 Thanks as always for listening. And always, as always, Jeff, 1236 01:13:33,030 --> 01:13:35,910 thank you for coming on and having a beautiful conversation 1237 01:13:35,910 --> 01:13:37,030 as always. Thanks, Matt. 1238 01:13:37,030 --> 01:13:37,750 I appreciate it.