December 17, 2024 • 46 mins
Chris Duffin is joined by Alex Miller, a dedicated innovator transforming the fitness tech landscape. They'll dive into the groundbreaking features of the Lift Lab app—a cutting-edge training tool designed to bring personalized coaching right to your phone. From sophisticated AI that analyzes your movement to a uniquely adaptable coaching system, the Lift Lab app is changing the game by focusing on simplicity and effectiveness.
Alex Miller will share insights into the advanced pose estimation models, the importance of personalized stress management, and how the app leverages years of data to deliver hyper-personalized training. Chris and Alex will also discuss the thoughtful methodology behind data collection and the app's user-friendly approach, ensuring that complexity doesn't hinder your progress. Whether you're preparing for a competitive powerlifting meet or looking to enhance your everyday workouts, this episode explores how the Lift Lab app can help you achieve your fitness goals with precision and ease.
Download the LiftLab app today and find the optimal balance between effort and recovery: https://www.liftlabapp.com
This episode of the ARCHITECT of RESILIENCE podcast is available on Apple, Spotify & YouTube, and is sponsored by
@naboso_technology : The Foundation of Movement. 🦶🏼Use Code RESILIENCE for 20% off your first order at https://www.naboso.com
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In this Episode, We Discuss:
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The Lift Lab App: Explore how the app leverages advanced AI, mobile technology, and data science to deliver a hyper-personalized training experience. Imagine having a "coach in your pocket" that tracks your movement and offers real-time feedback without the need for additional devices.
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Innovative Features: Understand the unique features of the Lift Lab app, such as AI pose estimation, joint position analysis, and velocity-based training (VBT), all designed to streamline your fitness journey and ensure you're always on the right track.
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Real-World Applications: Alex Miller shares how this technology can be applied across diverse activities like swimming, alpine skiing, ski hunting, and horseback riding. It’s about making fitness adaptable to your lifestyle.
Contents:
00:00 AI-driven, personalized coaching via Lift Lab app.
05:28 Systematizing coaching data with AI-enhanced tools.
08:36 Phone calculates weight, guides adjustments seamlessly.
12:41 App personalizes training program based on user data.
14:09 App estimates individual stress loading for deadlifts.
18:43 Using stress index maintains consistent training stress.
22:49 Analyzing training variance for abnormal stress levels.
24:29 Traditional deloads risk overtraining, potential injuries.
29:00 App helps diagnose and improve deadlift technique.
33:26 Developing app tracks recovery metrics and sensations.
34:21 App adjusts workouts based on elbow stress.
39:01 Oxygen delivery, critical power, sustainable output strategy.
40:48 Maintain power output, achieve 35 VO2 max.
43:56 Balancing simplicity and careful data collection.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to the Architect of Resilience podcast, where we
explore the secrets of overcoming. Life'S challenges and
unlocking unstoppable strength through deep personal
conversations and expert insights. Let's quit
dancing around it. Alex. Lift Lab. That's
right. We've been talking about training, science and all this because,
(00:21):
well, we've been working quite some time. I know you've
been working full time on this and by Alex, full time, that's I don't know,
what, 60, 70 hours a week, something like that. Since
the beginning of this year. I think it was January.
Yeah. Because you started working on the algorithms as we were related to
(00:42):
this acquisition of another tech company and then
switched gears. But I was talking with the Lift Lab
folks, well, the true rep folks, Colby and
Luke, last year, they've been
working on the IP around
this velocity tracking, not using a device quite some
(01:04):
time. So Kabuki's actually partnered with them. So this project
is years into the technological development at this
point in time. So we have two
programmers and yourself on the sports science side, me in
there as well. I've been just
digging into this and we have been working on
(01:26):
the side, busting our ass on this for quite some time.
And it is incredible what we can do
with being able to capture all these adaptive
modulators and really look into
how one individual is
responding. So this is lift like
(01:48):
it's like a coach in your pocket with bionic
vision that can just see the intricacies of like the
smoothness of the movement and do the physics calculation to know
are we getting compensation patterns breaking in, where are you at on an injury
threshold, calculating all those K values that we
talked about, looking at the entire training and actually putting this down
(02:10):
into a hyper
personalized coaching experience. A
program one of one that
just refines itself and continually adapts to
how you are responding to both the training and the
stresses in your life. And just continually
(02:31):
refining that along with, you know, looking
at the movement quality, feeding that
into what is the exercise selection. We're going to dive more into this. I'm, I'm
just giving a broad strokes, larger
picture of what we're doing with the Lift Lab app
because there's, there is nothing like what we're doing.
(02:53):
And I think it's so cool because we're taking, we're harnessing like
all this stuff has been out there from a technology standpoint, just
hitting the market. We're using the fact that, you know,
our phones now, the pixels on these
are so refined that we can actually capture
lab grade Velocity. We've got AI pose
(03:16):
estimation that we're looking at joint positions. Like, the tech is there. That's
cool. The science is there. Like, we've. We've talked about the adaptive
modulators and the jerk metric, and like, there's nothing you could do with
it until you have a lab. But we literally
have a lab in everybody's hands.
Some people might call it a lifting lab. You might. You might call it a
(03:38):
lifting lab. Yeah, some people might do that.
Yeah. So let's talk a little bit more about actually
peeling back the layers of what we're doing here
and this experience.
Where do you want to start? Oh, yeah, that's the question. So,
(03:58):
okay, I'll talk about it from, like, when I first started working
on the whole kind of concept of this,
like, organization of a training process. Because this goes back, like a long time.
Like, this goes back. So I started working on the systems
behind this before I was even at kabuki.
Yeah. This is like, I'm not going to say like a
(04:21):
magnum opus, but, like, it's a. It's a lot of time, your. Your
life's work. And anybody that doesn't know Alex, it's. It's incredible. I think that's
been one. One of the discussions that we've had over the course of this
is like, well, we're dumping,
like, anything and everything in our minds on training
and the details around that, you
(04:44):
know, and then it's all going to be out there and all be
programmed and where. What do I do now? Right.
But it's. This is something I spoke to some guys in
the school group today about. Like, I've been coaching nearly 20
years now, like, but not, not exactly 20 years, but it's coming
up to 20 years of coaching. And like, it's all.
(05:07):
It's all in there, like, everything that we've had. And it's not
just like, hey, this kind of collect this information. It is
like, it's actually using. Knowing how to use the
information as well, which is a really big deal. Like, anyone can take velocity.
We have that now. But how do we impact it in a way which is
going to progress you? That's what we want to do. Yeah. And
(05:30):
that's what you've been doing with this, is systematizing it. And that
was your role for so long, was
taking all this information, the theory, and systemizing it
for a group of coaches, which was, you know,
a half dozen to Almost, you know, 10 coaches at a period of
time, and educating all of them how to Doing that
(05:51):
and creating the tools which was this massive amount of
databases. We had all these databases pulling the
statistics so that we could look at and see how
an individual, what are the key metrics, how are they adapting and pulling all that
out. And it was, it was a depth, I mean incredibly proud of the tools
that we had for coaching. But now we're taking
(06:13):
that coach's eye using also the AI
tools and the processing capabilities we have today
and developing this super smart programming
that's actually even better now because we're able to factor
in things like sleep recovery, the fatigue.
(06:34):
It's so incredible. And also I just love it because nobody's doing it yet.
Nobody has doing anything like this. So we're, this is the
first entry in the market truly using
anything of this level anywhere close to it. Yeah.
Combining these techs and like some of the stuff we have planned, or at least
I've planned for tech is like no one's doing it. Like there is
(06:56):
other app roomy stuff which is algorithmic. It's just not
as good. I'm not saying that in a bragging way. I don't
really enjoy bragging. It's more like it just is better.
Like I don't, I don't know say it's like you know we're going to do.
Yeah, well let's, let's talk through some of these things.
So you know, the advanced posed pose intimidation,
(07:18):
the you know, the coaching because there's actual coaching that
happens within it. Velocity based training, our holistic
approach to it. At the end of the day it's all
about creating this very simple tool, this user friendly, you get it? You don't
even need a lot of education to be able to like set your phone up,
watch you and it tells you what load to go on the bar. So this
(07:41):
is simplifying even vbt. Because we did vbt.
I started pioneering VBT for use in the
tying into the neurologic your, your, your readiness
15 years ago where people were only using VBT
to, for speed training. Right. And so it
was creating this profile. Brandon Sin
(08:03):
covered this really well in the auto regulation book of methods.
But then we would give people like here's a velocity range to hit. Well the
end of the day was all about moving more weight within a desired
range. And so we worked with
nearly every VBT manufacturer around. Maybe
there's some new ones now out there in development because of
(08:26):
what we were doing. But the, the
true rep was really unique. It was first a puck that went on the
weight and would capture to that. And now we've taken it
to where we're actually able to identify the plate and then use
the plate. So there's no extra technology whatsoever, except your
phone is looking at that and
(08:49):
seeing how fast that weight moves. But we're doing all the
background calculations so that it's completely,
you know, you don't need to know VBT training at all. I was doing
my training yesterday, and
it said to use 95 pounds for curls,
and I used a hundred. And I'm like, I was a little heavy. I should
(09:11):
have gone with what was listing then. I was doing some good mornings, and it
wanted me to. I did my set, and it's like, no, you need to add
five more pounds on the next set, because it just tells you what that load
is. And that's the. That's the value itself. Adjusting. Now, for
me, like, I go in there, when I first restart the program, it says,
hey, you need to do this at. With £890 for sets of eight,
(09:32):
because it's going off a thousand pounds immediately. I put in. I did
440, yet. I put it. I did 440. And it knows the speed, and it
says, okay, next set, you're going doing eight reps. You're dropping
that to 390 pounds. And I mean. And it's going to be an
RPE8. And I mean, it's just spot on. Spot on,
right? Yeah, spot on. I mean, just amazing. Better than that,
(09:53):
because you don't even need the barbell if
you look at, like. So my program has a ton of goblet squats in
it. Yep. Just. Just because that's what. That's what I'm down right
now. And it doesn't have a barbell, but it captures my velocity
perfectly. It can. It captures movement, so it
showed me stuff. So I'm a big fan of filming myself lifting because
(10:16):
I think, like, sen got me into it. Like, did I start doing it? So
I get to judge myself. Okay. And it's picked up something I didn't even
know. Like, and I've been coaching 20 years, and it's picked up this rotation I
have on my hip that I've never noticed and people I train have never noticed,
but definitely there. So it's even better than
just having the barbell pops. Even better when coaches are. Because it sees
(10:38):
things that are objectively there and not. Not
having to worry about people like me going. Having to fix my hips. Like,
I can do it, but I still really want to. Yeah, I.
You know, when I say that the coaches eye too and like being able to
call that next set. There's a level of that skill that only a few people
really have and it's almost intuition for that
(11:00):
coach to go, you know, let's call it for the day, let's add, you know,
£5, £10, whatever it is. You could ask that
person like, what are they seeing to do that? And they'll, they just, they
can't tell you. Yeah, it's just so. It's this very subtle
because when we're talking like the jerk metric, you cannot see that with your
eye. The smoothness of the movement with the parameters that are called out, you cannot
(11:22):
see it. But there's some people that have those few coaches that have
that ability, that sense to be able to tell
you, you know, hey, it's time or to add or whatever. And I think
that that is a high level skill that they're seeing those
refinements but they consciously don't see them.
It's intuitive. And now we're able to pick that
(11:44):
up, put the data on it and actually make those calls based
on it. Which is just incredible because I
can't tell you the times when I'm working with somebody that I'm like, I just
feel that I know this and I don't
have, you know, it's the data because
like you think about it. Oops. Ah. I guess
(12:06):
I'm speaking to this camera now. Yeah, one of your cameras is gone.
Yeah.
I'm going to pause this.
So yeah, it's incredible what we're doing on
the velocity standpoint. But it's not just
(12:26):
that. Do you want to talk about the. How you're using?
I guess. Where does someone start with. You get the app, you
open it up, you want to walk through that process of how the
initial program gets developed. I'll talk
about how it is now and then I'll talk about
(12:47):
some small upgrades which are coming because it's cool, because it's going to make the
rest of it better. As you open the app
up now, it will say hi and go through hey, welcome to the app, all
that kind of stuff. Then you put in your amphiprometric data, so, so
you'll take your age, high
weight, like lifting experience and all those kind
(13:08):
of biological statistics and it
will take your training history or take how well you recover all
into account. And then that goes into a separate algorithm
we have which helps predict
your starting volume. So we have this idea
of like the body can only handle so much stress. Okay. And
(13:31):
that stress is a proxy for volumes
or volumes in a proxy for the stress, however you want to look at this.
But that's individualized to each person. So if we,
if we take someone like your man Peter
Palouse. So if we look at, if we look at his metrics on
there, like he's a, he's old.
(13:54):
I mean that's the way around it. He's just, he's getting on a bit. You're
going to program, let's say, you know, like a Rudy or whoever.
If you've got a 60 or 70 year client, they're going to be completely different
recovery capability than a well trained, let's say 30 year old,
you know. Yeah. And that's a big deal. So if we look at Peter, Peter's
doing like two, this is
(14:15):
exactly two sets of deadlifts or two like main sets of
deadlifts per week to start with because
that's our best estimate of what we can handle. This is what the app does.
The app goes with, okay, this is what we're going to start you as an
estimation of your individual stress loading. And we're going to put
that in, you're going to start there, then we're going to see how you respond
(14:36):
to that. So once it has an idea of the amount
of total sets you can do. So we're using total
sets as a proxy here. We have an idea of the total
internal load you can be subject to. So that is like
how hard are we sets? And we're splitting that
into like central loading and peripheral loading, which is basically
(14:58):
like, you can imagine it as nervous system stress
and then skeletal muscle system stress or
myofascial system stress. People see that
there's nothing useful, but you pick an exercise and it'll say the
central and peripheral stress index that we're using on those.
Yeah. And that's really important because we go back to
(15:20):
use Peter as an example again, like he can probably handle a
buttload of peripheral stress. Okay. And he's going to have to
because like that's where his real work is going to come in
now. Because maybe he doesn't have the capacity to handle so much axial loading anymore.
But that's very individual. Okay. So we have that and then
it will do its magic, like black box in, black box
(15:42):
out kind of stuff where it will tell us the movements
that will fill up the volume without exceeding
like your estimated kind of dosage, which is
amazing. Okay. Like that's just like that. That is what
you pay a very experienced coach to do.
Like you, if we're talking very experience there's a lot of coaches, I'd
(16:05):
say most don't fall into that that round where they're actually calculating
all that out. Like you know it's taken
10 years to build the tools to calculate all that out for clients and
like it's a, it's not something that somebody just has the capability to just turn
on and do. Yeah, it's just. And even if
people understand it, there's a subtlety to it. Like people do talk about
(16:27):
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(17:11):
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be like hey, like it says this
but let's not do that and the app gets that right. But
I've not seen it do and I've messed around with this a lot. I've not
seen it get something wrong in this entire kind of process which is
(17:33):
incredible. And then let's talk about how it refines that. So you're
completing your work for the week. We've got a training, training
block for a certain period of time. So loading is not just
completely linear. Um, uh, so you want to
walk through that. Yeah. So and this actually kind of plays
into my bias as a coach that we, we have
(17:55):
a. There's no set system of periodization.
Now I know that sounds kind of maybe a little bit crazy,
but you don't need it. We have internal stress levels if you can
measure instead because things change over time. And
what I mean by that is what happens to me this week with my stress
and what happens to me next week. My stress is not the same.
(18:18):
So we can't assume an increase. We can't assume that I'll have the
ability to handle more load next week. And then if you're a girl and
you're on your cycle, then like that is. That's a big deal. Like for some
women. Like you get like a like 30% drop in strength. Like
if you're one of outliers and a 30% drop in strength and you,
you're in a peak, like that's going to make you feel pretty shit. Unless you're
(18:40):
using velocity systems. Right. In which case we can still apply
the same central stress that you're still straining as hard without
the burden of having loading. Okay. So the
way we kind of accommodate this is that partly with stress
index. Okay. Which, which is super good because we, we keep
the level of stress similar over time. And as you get
(19:02):
stronger, the RPE of whatever weight is
will go down because you're stronger or the weight will go up at the same
RPE if you want to do it to maintain a level of stress which is
recoverable from the other way that
we're kind of looking at progress. I kind
of lost my train of thought a little bit here. So ask me the question
(19:23):
again. Is it. Yeah, I got excited about
a bunch of stuff. I got lost and was thinking
about my next questions actually. Okay. So it was
progressing over time. Yeah. So we have this
idea that progress only happens when you earn
progress as well. So if
(19:47):
you are keeping going and you're
seeing positive change over time, you're
unlikely in the current state of the program or the
whole kind of stuff to get change. Because why would
you. If I'm consistently putting 10 pounds on
any lift, like I'm in a good place and there is no need
(20:09):
to mess with that. That's like, that's. That's gold. And
when that stops happening, then we see a change and
that change is done by looking where the weak
points are. So we see that with our either
pose estimation model or where we see changes
in rate of acceleration. That's a new bit that's coming
(20:31):
soon as. I mean the guy spoke about that a couple days ago
and that would say. Okay, well we're going to choose
an exercise which biases training of
the. What can we call a weak zones or slow zones or the
point where deceleration starts. This is really important. I think we
spoke about it before that. Yeah, yeah, we did. We did. I think we use
(20:54):
Kitty as an example of the focusing on those deceleration
points and yeah, rather than, rather than. The place you
stop, it's a place that your force output starts decreasing. And
app, which I can see that. Yeah, the app knows where
those points are. Yeah, yeah. Which is incredible. So you actually get
better exercise choices because going back to this idea of dynamic
(21:16):
correspondence, it has a better idea of what's going to have a
good impression. Yep. So we're seeing that you quit
making progress. The app is going to look at, you know, those lifts, look
at where the deceleration point is, and then choose exercises
specific to addressing those as an example.
Yeah, that's exactly it. And it's not just primary
(21:39):
exercises. It will pick the secondary exercises and the accessories that go with
that as well. The whole system
is driven by how you're performing as an
athlete, which is driven by how you're recovering. Right. It's driven by what
stress loads you're under. And that's individual to the person. But that.
That's coaching. That's what. That's what coaching us. Yeah. So
(22:01):
let's talk about those stress levels too, because we talked about when we were
walking through adaptive modulators, the difference where
maybe the velocity metrics are remaining exactly the same, but all of a sudden
we see a change in
the perceived effort of a set. How does
that feed into the program? Yeah.
(22:24):
So this is where we start. Do we talk about z values in this
one? Essentially this statistical. Yeah, so we did. That's what
I was referring to was the Z values, because
not. I don't know anybody. Well, there's certainly no apps, I think, that
are looking at, because they can't calculate the actual.
The mechanical component of it. Right. Which we're doing. We're
(22:47):
not just. Yeah, so we're looking at
the change in standard deviation over time, which is
just a really fancy way of saying is, is this abnormal for you?
But there's a normal amount of deviation. There's a normal amount of up and down
that people's training, if it's outside of that, like you're saying, like,
we'll see about a week or two where your stress just starts going up
(23:11):
super high, but your RPE is the same weight away above
where the app predicts they will be.
That might be a sign for some sort of
lowering stress. Okay. Now, we could call it a deload.
I wouldn't. I don't think. I don't think deloads are really a thing that we.
We do per se. We just see a reduction in stress.
(23:33):
Yes. Yeah. Because a deload implies like
a. Like taking time off.
Right. And we don't want that. We don't want to take away from someone's
resilience by. By saying we're going to stop Doing
this, we just dial it back until you can get in a good place from
doing this. Yeah. So it may be a reduction in set
(23:55):
numbers, it may be a reduction in
rpa, but it's never going to be a,
hey, we're going to change everything up because you might be slightly stressed
out. So if we start seeing those said
values change in a significant manner, the program
isn't going to deload, but it's going to start reducing some of the stresses to
(24:16):
get you back online till we see a return
to the state where I would like to see, well, progress.
Yeah, yeah. So you could call it deload, but it's not
traditional deload, right? Yeah, I think traditional deloads I've
done. I think I've done videos that, like 10 years, 15 years ago
around. Yeah. A true, like
(24:38):
deload, like where you've got to take a week off or very minimally trained for
a week. You know, we've got a fault that's pushing way too hard on
the program if you're required to do that. And over time, you're going to end
up with potential for, you know, injury, likely because you're over pushing in
those, those sessions. Right. Which is what
I achieved in those years where I did that traditional
(25:00):
conjugate training, I think, from 2003
to 2012. And that's when the majority of my
injuries and surgeries were instigated. And I still have problems
to this day as it relates to that
period in, in, in my training history. Yeah,
absolutely. It's a really big deal. Like, there is a time and a place
(25:23):
for overreaching, but not overreaching to the
extent that you're, you're driving something to the ground
where you're purposely doing. It every, you know, three, four, five weeks.
Yeah, yeah. You're like two times a year, like twice. Like, I, I'm not a
huge fan of people competing more than three times a year. Like, I know it's.
If you're doing for fun, like, great. If you're doing it seriously
(25:45):
and you're really pushing yourself, like two or three times, plenty.
But that's like competitive powerlifting we're talking about. Yeah, yeah, competitive
powerlifting. Like, if you're truly, like prepping for a meet is
incredibly hard. Like those phases, when you're overreaching
to that level and you just feel like dog shit, like it's
impacting your work, it's impacting your family, it's impacting all these things because your mood,
(26:07):
your behavior, your sleep all these things are truly changing in that
period of time. That is not something like showing up for a
meet, you know, every few months. That's not. Yeah, that's his fault. But that's.
Yeah, that's how. That's a hobby, which is cool. Like, that's super cool to do.
I. I have a girl prepping for meet right now and it's just, she knows
it's for fun. She's going to PR because she's got stronger, but, like, she's definitely
(26:31):
not in the same place she was before, say, nationals. Yeah.
So let's talk about the, the pose estimation. Like, you know,
you're talking about measuring velocity with the pose estimation for your goblet
squats. I know that we're going to continue to advance that.
Like right now, I was talking about yesterday, I was doing my training. My
curls, my meadows rows, all these non traditional
(26:53):
metrics were, you know, we're measuring the velocity and the
stress with those because it's using a plate. But we're going to continue
to add more and more to the point. Like if I'm doing skull
crushers right now, I've got velocity. If I'm using a bar but not doing
press downs as of yet. But those are things that
will continue to add. What other ways are we using
(27:15):
that pose estimation to guide exercise
selection or, you know, any other correcting
movement inefficiencies? Yeah, that's a great question.
So to me, the pose estimation model is
like the most exciting part is because this is truly what no one's doing, because
there's apps which have velocity and there's apps that are programming. Not great programming, but
(27:36):
they got programming and no one's combining
them, but no one at all is doing the pose estimation, which
is incredible. So what this does
is it can work out from
either the position of your head or position of the bar bone
where your body parts are. So we can tell length of limbs, it
(27:58):
can tell the increase and decrease in joint angles, they can
tell rotation, and it just tells you your position space.
Now, this is a really big deal because this is what coaches look at.
If I'm looking at someone squatting, then
I'm not looking at them as a person squatting. I'm looking to see
what's happening at each individual joint section. But we have this idea of a joint
(28:21):
by joint approach. It's been popularized over a long time now.
Okay. And the app sees that and we have a
database of what and it's actually from the American
physiotherapist society, what joints should be able to do.
Okay. And if we don't see a joint
moving in a traditional way and it's not
(28:43):
good or bad, it's just what we would expect, then that
would then go on to influence preparation, bills, game. If
we see a squat happen or deadlift
happen in a way which is indicative of a
muscular deficit. Right. So if we see
someone deadlift and then they do this massive hitch, they see
(29:05):
the knees under the bar and drive up with the
quads. We're like, oh, dude, hamstrings. Depending on the hip
half, it'll be hamstrings might be shit or the glutes might
be shit, or they might just be bad at deadlifting, which is a
big deal. And the appeals that we'll be able to
tell from the changes within the position of the
(29:27):
barbell for joints and the start position
what the issue is and then prescribe to fix that. So
when you load up the app, there is
a very detailed now queuing system on there. So
you'll go into it and it will talk you through, hey, this is like
the points of a deadlift. So I think one of the good ones was
(29:50):
the deadlift to kneel deadlift chains.
It has like a couple of paragraphs of points like, hey, these are
the steps you go through if you know what a deadlift, great. Just use a
pose estimation model, use the stick figure frame that we
have to judge it and then see what the app says.
If you're unsure about how to depth it, this will walk you through it. It's
(30:14):
gonna be really hard to get it wrong if you listen to the
app. Yeah, that's incredible.
And we've got these into the movement prep plans right at the
beginning of the workout as well. So those are influenced by those.
Yeah, they will be. Yeah, yeah, they will be.
And then every exercise, obviously some pretty basic stuff.
(30:37):
Like you click on the exercise, there's a video of how to do it,
coaching cues, all of that in there. Yeah. Oh, there's something we should point out
first. You mentioned this. For your accessory work that
is taking velocity measurements of that, people
sandbag the shit out of their accessory work. I know.
You cannot do that on the app without it being like,
(30:59):
hey, you should be doing this heavier. And like, so all the
benefits, both like therapeutically
for like actual muscle gain and for
like consideration of balance. I'm not a huge fan of that term. I
don't think bodies should be balanced. But in terms of injury prevention, yeah, like
you should be pushing that kind of accessory work to build a more
(31:21):
robust body. You just can't sandbag it unless you're happy being like, oh, I'm
just going to take the weight down every time. And that's, that's not cool. All
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(31:44):
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(32:06):
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is so common that people do some.
Do some heavy sets and then phone in all the accessory work, which
(32:26):
is VBT forces effort based
training, which is, you know how we termed that a
long time ago when we were talking about vbt. Is it? Yeah, it's
effort based training. So let's talk about the
holistic kind of approach to training with looking at these
variable stresses outside of training.
(32:49):
So we're talking about. This is the check in
model, right, that we talked about. Yeah. Okay. So we're collecting a
ton of data about either
like discomfort or sensations in training or after
training or collecting a ton of data about how you felt the
session went. I think we collect data
(33:11):
about seep as well right now, don't we? I don't think it's
in there as of yet. Although I did miss the last upload. I got to
update mine there was. Actually updated again this morning. So. Okay,
so maybe it is. Maybe. If not it will be soon.
Probably by the plan is there's. We haven't mentioned
this, but this is like a revive kind of module which I'm working on right
(33:32):
now, which will basically take a ton of recovery metrics into account.
Anyway, so we take a lot of these subjective kind
of sensational feedback
metrics. So when I say sensational, I mean like to do with the
senses. Yeah, it's cool. But you know what I'm saying?
And we're going to let those tell us how things are feeling.
(33:55):
So for example, if you feedback and you've had a couple of weeks
where you have like not an impingement in your shoulder, but like your shoulders a
little bit cranky, the app will recognize that
it's developing into a personal sensation and dial back
that specific kind of joint. So
I occasionally get some medial elbow pain
(34:17):
after bench pressing because my shoulders are fucked. The
app would actually take me off bench press if I
repeatedly showed stress on my elbow and then either
put it into tempo movements if it's one of the first times it's happened,
which is a great kind of recovery work for us, or it would actually shift
me into something which is less stressful to the body. Maybe a machine
(34:39):
press or a dumbbell press. Currently, I think the bias
is towards machines, which I'm totally for, because a more stable
environment is probably much, much better. And then from the
machine work you go to tempo work. And from tempo work it'll feed you back
into the main X exercise. And this is over a few weeks. But
if we look at like movement sensitivity and joint
(35:01):
sensitivity, like it might take that long. The future plans are
to drop into isometric work. We need the analgesic effect. There's
tons of stuff in the future coming there, but currently that's how it deals with
that kind of pain sensitive model. Yeah, and
I think we talked about that on a prior podcast. Not having
to just take complete time off from a certain body port or
(35:23):
joint with those methodologies. And why we chose.
We like choose machine and then tempo work
as ways of still adding load
but providing some time for the
desensitization of
those pain. Anything
(35:45):
else that as it relates to the app that you really want to
dive into.
I'm so immersed in the app right now that
like. Yeah, just everything,
I guess, but nothing specific. It's just. You want to talk about some
of the things that we're working on right with it. Oh, shit.
(36:07):
Yeah. So right. I do because I'm super excited about
stuff we're working on. So the way I picture the
progression of this is we go through like separate stages, steps
again and I give fancy names to them because I like that
the next couple of steps were actually kind of where we're at is working
(36:27):
on. I can't remember names right now,
but it's basically this automated feedback loop which we've just been speaking
about. And then the recovery stuff because when
we get inside that whole rest system, I think it's called, oh, I'm calling
it, at least we can start Being able
to be, to imply power
(36:49):
says, let's say we have a certain number of
recovery methodologies that we'd like to use. Okay. We might have
recovery methodologies that we just think are more effective.
For example, like having, like, and this is super underrated,
having dinner with your loved ones, like, that's
an incredible recovery tool. And it's something that
(37:12):
people probably don't think about now rather than being like,
hey, I'm going to go and pay 200 bucks for cryotherapy,
which, like, great, like reducing inflammation. Fantastic.
200 bucks for it. Probably not great. You see what I'm saying? Like,
maybe there's. Maybe that you can get a better bang for your buck than that.
And we'll be able to look at people's stress and
(37:34):
prescribe what we would expect to be the most efficient recovery
methodology to do for that one. Like, the way I think
about recovery is a nervous system based deal.
And what I'm kind of says, like really simplistically is
if you think it's relaxing, it's probably really good for
you. Right. So if you want to play computer
(37:56):
games, because that's what chills you out, I think that's
a legit recovery strategy if you want to have naps every day. Like,
I am religious about napping. I will, I will nap every
single day because it makes me feel better. Like my
life is better because I prioritize
like the recovery aspect of sleeping and
(38:18):
napping. Right. And the app will
algorithmically suggest that depending upon stress
levels, which is. That's super cool to me.
Yeah, it's a really big one. I think it's really underrated to be able to
prescribe or suggest recovery methodologies that are
as broad as like sitting in deep water. Really
(38:40):
big deal. Like that deload of the body, like, makes it way less
essentially all the way through to like, like, like literally having
dinner or going outside for a walk. It's a big deal.
Other stuff I'm excited about is the, the cardio aspect of things.
I'm really looking forward to. Yeah, pretty
excited. Yeah. Yeah. Like,
(39:03):
so I think about cardio in a very specific way about
oxygen delivery and utilization, which we've spoken about.
But there's something I've been working on very recently, which I'm not sure
I showed you yet, where we take critical power, which is the
sustainable amount of output that someone can have.
Now it varies person to person, but it's a pretty
(39:26):
steady number on depending on your fitness. Okay. And then we have
something called a w Prime, which is the gap between
critical power and maximum output. So let's say if
you're going for a walk and then
you have to really sprint, that sprint will go above critical power because
it's not sustainable all the way up to W prime.
(39:49):
If we know what someone's critical power is and we have a way to
test this out and we know the task
someone has to do, we can then program
really, really easily a way for them to be above
their critical power or have their critical power above the task
demand for the most part, which is insane because then
(40:11):
you can go. Okay, I have, let's just say.
Yeah, let's give some examples of what that would be.
Yeah, if we use,
we use the Army Fitness Test. Okay. Because that's, that's standardized. Okay.
So the Army Fitness test is one of a two mile run.
Right. I'm actually going to pull this up now because I have, I have the
(40:33):
information right in front of me. The two mile run, the army fitness test
means you have 12 and a half minutes to run two
miles to get a maximum score. Right. Because we only really care about getting a
maximum score, which means you have to run.
Let me find this out here. What's my speed?
15 kilometers an hour. Okay. Or
(40:56):
you have to have a constant power output
where we are, give or take
between 4 and 500 watts. Okay. Now
that probably slightly above most people's critical power, but if
you get your critical power around there, you wouldn't be
(41:17):
tired doing that run and you would pass that test of flying cards and we
can train up to that. You would need a VO2 max of
like 35, which is reasonable. Pretty
good. If you know the task demand,
the app will program it together. So let's
say I'm preparing for hunting season where I know I'm
(41:39):
going to have a 30 pound pack and I'm going to
spend a week, you know, climbing X
amount. You know, you, we would be able to input that
and you would actually be able to have your
training prepare you so that you could, you know, sustain
that week of, you know, going up and down these giant hills with a pack
(42:01):
on. Did I talk to you about this already? No.
Oh, okay. Well, ever happened? I don't know exactly
that. So I
actually wrote a Python script which analyzed binary topographical
data. So it will tell you
how hard going hunting would be and prepare you for
(42:23):
that. And the app will have information on it which will take
into account elevation or take into account change in elevation
distance of each thing together as it happens.
Hunting is is one of the things that it'll be really good at.
Yeah. We talked, we talked about rucking and I was just using
hunting as an example because I know so many people actually that do
(42:46):
physically prepare each season for this because they know
how much they're going to get shredded if they're not. So they, they start putting
a pack on, they're doing hiking, but they don't have necessarily a
targeted plan to get in shape knowing what they have to hit.
Yeah, this. And we'll have the data to do exactly
that like really, really well because I spent the entire
(43:08):
weekend, I think probably 10 to 12 hours each day
doing this. Yeah. Love it,
love it. Yeah. I just got, it's one of the things I'm
planning on taking quite a big interest in is scouting and kind of rocking in
the, in the wilderness. Okay. So
we got to get, we got. To get you move, move to Oregon here at
(43:29):
some point in time then. Yeah, that's the thing. Right. But yeah,
so it will do exact that and it will be able to do it from
anything from, they will be able to do it swimming, you'll be able to do
it with off like alpine skiing. If you're going to do ski
hunting or horseback riding, it will have the information there.
Yeah. So that will not be in our release coming
in. No, no, that, that's something that I literally did over the weekends. Yeah,
(43:53):
yeah, yeah, but that's that. Yeah. Well, I,
I, I, I want to reiterate there's a lot of complexity that we're talking about
here with science and data. But
really what makes this thing so cool is where it's
the simplicity with which we're meeting this innovation
(44:13):
and we're being very cognizant
of how many metrics we're also collecting and having you manually
input. We don't need to spend 15 minutes collecting
data that we're not using. So we're being very
conscious of how we're approaching the data collection that
is, that is input with these check ins as well and the
(44:35):
timing of when that check in is so that it's not influencing
you in a predictive manner around your training, which I think is,
is a miss. There's a lot of kind of psychological standpoints that
I think are missed with some of the products out there that may set
you up for having a bad day or bad training, depending on the approach
as well. Yeah, that's one of the things we spoke about a while
(44:58):
ago which was like if I ask you, hey, are you having a bad
day like, that influences the answer. And,
like, there's been a lot of coaching hours put towards this and a lot
of understanding of, like, what makes people think the way they
do. Okay. And rather than saying, hey, do you have a bad day?
Maybe we collect stuff afterwards. We try not to
(45:20):
influence the training by giving you a ton super
forehand. And a lot of the time, it's not that we don't let you tell
us the information. It's like, you don't have to tell us information. It's done.
It's. It's done. So you might have a recap. Okay.
And it might just be as simple as a 1 to 5. Let's say it
might be. It's as simple as a one to five scale. Yeah. Right. How
(45:43):
hard is this? It takes. I don't know how long it takes you, but it
takes me probably less than a minute to get back over it. Yeah, yeah,
yeah. So I'm super good that way. Well, I think this is
a pretty. Pretty good overview and a good
place to kind of wrap this up. I hope that people.
Yeah. Got a little bit more information about what we're doing again, you can review
(46:06):
the prior episodes if you want to dig into some of the science around
exercise selection, adaptive modulators, things
of that nature. But we're going to continue this series of
podcasts talking about the next generation
science of training and how we're having
technology meet. Meet this in the middle. And it's. It's
(46:29):
really cool. We're super excited. We've been absolutely loving this last
year of taking this to the final iteration that is about ready
to drop. Yeah, I'm excited. I'm, like,
genuinely quite excited about this. Yeah, yeah,
same, same, same.
Welcome to the Architect of Resilience podcast, where we
explore the secrets of overcoming. Life'S challenges and
unlocking unstoppable strength through deep personal
conversations and expert insights. Let's quit
dancing around it. Alex. Lift Lab. That's
right. We've been talking about training, science and all this because,
(00:21):
well, we've been working quite some time. I know you've
been working full time on this and by Alex, full time, that's I don't know,
what, 60, 70 hours a week, something like that. Since
the beginning of this year. I think it was January.
Yeah. Because you started working on the algorithms as we were related to
(00:42):
this acquisition of another tech company and then
switched gears. But I was talking with the Lift Lab
folks, well, the true rep folks, Colby and
Luke, last year, they've been
working on the IP around
this velocity tracking, not using a device quite some
(01:04):
time. So Kabuki's actually partnered with them. So this project
is years into the technological development at this
point in time. So we have two
programmers and yourself on the sports science side, me in
there as well. I've been just
digging into this and we have been working on
(01:26):
the side, busting our ass on this for quite some time.
And it is incredible what we can do
with being able to capture all these adaptive
modulators and really look into
how one individual is
responding. So this is lift like
(01:48):
it's like a coach in your pocket with bionic
vision that can just see the intricacies of like the
smoothness of the movement and do the physics calculation to know
are we getting compensation patterns breaking in, where are you at on an injury
threshold, calculating all those K values that we
talked about, looking at the entire training and actually putting this down
(02:10):
into a hyper
personalized coaching experience. A
program one of one that
just refines itself and continually adapts to
how you are responding to both the training and the
stresses in your life. And just continually
(02:31):
refining that along with, you know, looking
at the movement quality, feeding that
into what is the exercise selection. We're going to dive more into this. I'm, I'm
just giving a broad strokes, larger
picture of what we're doing with the Lift Lab app
because there's, there is nothing like what we're doing.
(02:53):
And I think it's so cool because we're taking, we're harnessing like
all this stuff has been out there from a technology standpoint, just
hitting the market. We're using the fact that, you know,
our phones now, the pixels on these
are so refined that we can actually capture
lab grade Velocity. We've got AI pose
(03:16):
estimation that we're looking at joint positions. Like, the tech is there. That's
cool. The science is there. Like, we've. We've talked about the adaptive
modulators and the jerk metric, and like, there's nothing you could do with
it until you have a lab. But we literally
have a lab in everybody's hands.
Some people might call it a lifting lab. You might. You might call it a
(03:38):
lifting lab. Yeah, some people might do that.
Yeah. So let's talk a little bit more about actually
peeling back the layers of what we're doing here
and this experience.
Where do you want to start? Oh, yeah, that's the question. So,
(03:58):
okay, I'll talk about it from, like, when I first started working
on the whole kind of concept of this,
like, organization of a training process. Because this goes back, like a long time.
Like, this goes back. So I started working on the systems
behind this before I was even at kabuki.
Yeah. This is like, I'm not going to say like a
(04:21):
magnum opus, but, like, it's a. It's a lot of time, your. Your
life's work. And anybody that doesn't know Alex, it's. It's incredible. I think that's
been one. One of the discussions that we've had over the course of this
is like, well, we're dumping,
like, anything and everything in our minds on training
and the details around that, you
(04:44):
know, and then it's all going to be out there and all be
programmed and where. What do I do now? Right.
But it's. This is something I spoke to some guys in
the school group today about. Like, I've been coaching nearly 20
years now, like, but not, not exactly 20 years, but it's coming
up to 20 years of coaching. And like, it's all.
(05:07):
It's all in there, like, everything that we've had. And it's not
just like, hey, this kind of collect this information. It is
like, it's actually using. Knowing how to use the
information as well, which is a really big deal. Like, anyone can take velocity.
We have that now. But how do we impact it in a way which is
going to progress you? That's what we want to do. Yeah. And
(05:30):
that's what you've been doing with this, is systematizing it. And that
was your role for so long, was
taking all this information, the theory, and systemizing it
for a group of coaches, which was, you know,
a half dozen to Almost, you know, 10 coaches at a period of
time, and educating all of them how to Doing that
(05:51):
and creating the tools which was this massive amount of
databases. We had all these databases pulling the
statistics so that we could look at and see how
an individual, what are the key metrics, how are they adapting and pulling all that
out. And it was, it was a depth, I mean incredibly proud of the tools
that we had for coaching. But now we're taking
(06:13):
that coach's eye using also the AI
tools and the processing capabilities we have today
and developing this super smart programming
that's actually even better now because we're able to factor
in things like sleep recovery, the fatigue.
(06:34):
It's so incredible. And also I just love it because nobody's doing it yet.
Nobody has doing anything like this. So we're, this is the
first entry in the market truly using
anything of this level anywhere close to it. Yeah.
Combining these techs and like some of the stuff we have planned, or at least
I've planned for tech is like no one's doing it. Like there is
(06:56):
other app roomy stuff which is algorithmic. It's just not
as good. I'm not saying that in a bragging way. I don't
really enjoy bragging. It's more like it just is better.
Like I don't, I don't know say it's like you know we're going to do.
Yeah, well let's, let's talk through some of these things.
So you know, the advanced posed pose intimidation,
(07:18):
the you know, the coaching because there's actual coaching that
happens within it. Velocity based training, our holistic
approach to it. At the end of the day it's all
about creating this very simple tool, this user friendly, you get it? You don't
even need a lot of education to be able to like set your phone up,
watch you and it tells you what load to go on the bar. So this
(07:41):
is simplifying even vbt. Because we did vbt.
I started pioneering VBT for use in the
tying into the neurologic your, your, your readiness
15 years ago where people were only using VBT
to, for speed training. Right. And so it
was creating this profile. Brandon Sin
(08:03):
covered this really well in the auto regulation book of methods.
But then we would give people like here's a velocity range to hit. Well the
end of the day was all about moving more weight within a desired
range. And so we worked with
nearly every VBT manufacturer around. Maybe
there's some new ones now out there in development because of
(08:26):
what we were doing. But the, the
true rep was really unique. It was first a puck that went on the
weight and would capture to that. And now we've taken it
to where we're actually able to identify the plate and then use
the plate. So there's no extra technology whatsoever, except your
phone is looking at that and
(08:49):
seeing how fast that weight moves. But we're doing all the
background calculations so that it's completely,
you know, you don't need to know VBT training at all. I was doing
my training yesterday, and
it said to use 95 pounds for curls,
and I used a hundred. And I'm like, I was a little heavy. I should
(09:11):
have gone with what was listing then. I was doing some good mornings, and it
wanted me to. I did my set, and it's like, no, you need to add
five more pounds on the next set, because it just tells you what that load
is. And that's the. That's the value itself. Adjusting. Now, for
me, like, I go in there, when I first restart the program, it says,
hey, you need to do this at. With £890 for sets of eight,
(09:32):
because it's going off a thousand pounds immediately. I put in. I did
440, yet. I put it. I did 440. And it knows the speed, and it
says, okay, next set, you're going doing eight reps. You're dropping
that to 390 pounds. And I mean. And it's going to be an
RPE8. And I mean, it's just spot on. Spot on,
right? Yeah, spot on. I mean, just amazing. Better than that,
(09:53):
because you don't even need the barbell if
you look at, like. So my program has a ton of goblet squats in
it. Yep. Just. Just because that's what. That's what I'm down right
now. And it doesn't have a barbell, but it captures my velocity
perfectly. It can. It captures movement, so it
showed me stuff. So I'm a big fan of filming myself lifting because
(10:16):
I think, like, sen got me into it. Like, did I start doing it? So
I get to judge myself. Okay. And it's picked up something I didn't even
know. Like, and I've been coaching 20 years, and it's picked up this rotation I
have on my hip that I've never noticed and people I train have never noticed,
but definitely there. So it's even better than
just having the barbell pops. Even better when coaches are. Because it sees
(10:38):
things that are objectively there and not. Not
having to worry about people like me going. Having to fix my hips. Like,
I can do it, but I still really want to. Yeah, I.
You know, when I say that the coaches eye too and like being able to
call that next set. There's a level of that skill that only a few people
really have and it's almost intuition for that
(11:00):
coach to go, you know, let's call it for the day, let's add, you know,
£5, £10, whatever it is. You could ask that
person like, what are they seeing to do that? And they'll, they just, they
can't tell you. Yeah, it's just so. It's this very subtle
because when we're talking like the jerk metric, you cannot see that with your
eye. The smoothness of the movement with the parameters that are called out, you cannot
(11:22):
see it. But there's some people that have those few coaches that have
that ability, that sense to be able to tell
you, you know, hey, it's time or to add or whatever. And I think
that that is a high level skill that they're seeing those
refinements but they consciously don't see them.
It's intuitive. And now we're able to pick that
(11:44):
up, put the data on it and actually make those calls based
on it. Which is just incredible because I
can't tell you the times when I'm working with somebody that I'm like, I just
feel that I know this and I don't
have, you know, it's the data because
like you think about it. Oops. Ah. I guess
(12:06):
I'm speaking to this camera now. Yeah, one of your cameras is gone.
Yeah.
I'm going to pause this.
So yeah, it's incredible what we're doing on
the velocity standpoint. But it's not just
(12:26):
that. Do you want to talk about the. How you're using?
I guess. Where does someone start with. You get the app, you
open it up, you want to walk through that process of how the
initial program gets developed. I'll talk
about how it is now and then I'll talk about
(12:47):
some small upgrades which are coming because it's cool, because it's going to make the
rest of it better. As you open the app
up now, it will say hi and go through hey, welcome to the app, all
that kind of stuff. Then you put in your amphiprometric data, so, so
you'll take your age, high
weight, like lifting experience and all those kind
(13:08):
of biological statistics and it
will take your training history or take how well you recover all
into account. And then that goes into a separate algorithm
we have which helps predict
your starting volume. So we have this idea
of like the body can only handle so much stress. Okay. And
(13:31):
that stress is a proxy for volumes
or volumes in a proxy for the stress, however you want to look at this.
But that's individualized to each person. So if we,
if we take someone like your man Peter
Palouse. So if we look at, if we look at his metrics on
there, like he's a, he's old.
(13:54):
I mean that's the way around it. He's just, he's getting on a bit. You're
going to program, let's say, you know, like a Rudy or whoever.
If you've got a 60 or 70 year client, they're going to be completely different
recovery capability than a well trained, let's say 30 year old,
you know. Yeah. And that's a big deal. So if we look at Peter, Peter's
doing like two, this is
(14:15):
exactly two sets of deadlifts or two like main sets of
deadlifts per week to start with because
that's our best estimate of what we can handle. This is what the app does.
The app goes with, okay, this is what we're going to start you as an
estimation of your individual stress loading. And we're going to put
that in, you're going to start there, then we're going to see how you respond
(14:36):
to that. So once it has an idea of the amount
of total sets you can do. So we're using total
sets as a proxy here. We have an idea of the total
internal load you can be subject to. So that is like
how hard are we sets? And we're splitting that
into like central loading and peripheral loading, which is basically
(14:58):
like, you can imagine it as nervous system stress
and then skeletal muscle system stress or
myofascial system stress. People see that
there's nothing useful, but you pick an exercise and it'll say the
central and peripheral stress index that we're using on those.
Yeah. And that's really important because we go back to
(15:20):
use Peter as an example again, like he can probably handle a
buttload of peripheral stress. Okay. And he's going to have to
because like that's where his real work is going to come in
now. Because maybe he doesn't have the capacity to handle so much axial loading anymore.
But that's very individual. Okay. So we have that and then
it will do its magic, like black box in, black box
(15:42):
out kind of stuff where it will tell us the movements
that will fill up the volume without exceeding
like your estimated kind of dosage, which is
amazing. Okay. Like that's just like that. That is what
you pay a very experienced coach to do.
Like you, if we're talking very experience there's a lot of coaches, I'd
(16:05):
say most don't fall into that that round where they're actually calculating
all that out. Like you know it's taken
10 years to build the tools to calculate all that out for clients and
like it's a, it's not something that somebody just has the capability to just turn
on and do. Yeah, it's just. And even if
people understand it, there's a subtlety to it. Like people do talk about
(16:27):
the art and science of coaching and like as much as I like
royal against it, like I think it's very science driven. There is an
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(17:11):
code resilience@merrick health.com that's
code resilience for 10% off. And like there's a not to
be like hey, like it says this
but let's not do that and the app gets that right. But
I've not seen it do and I've messed around with this a lot. I've not
seen it get something wrong in this entire kind of process which is
(17:33):
incredible. And then let's talk about how it refines that. So you're
completing your work for the week. We've got a training, training
block for a certain period of time. So loading is not just
completely linear. Um, uh, so you want to
walk through that. Yeah. So and this actually kind of plays
into my bias as a coach that we, we have
(17:55):
a. There's no set system of periodization.
Now I know that sounds kind of maybe a little bit crazy,
but you don't need it. We have internal stress levels if you can
measure instead because things change over time. And
what I mean by that is what happens to me this week with my stress
and what happens to me next week. My stress is not the same.
(18:18):
So we can't assume an increase. We can't assume that I'll have the
ability to handle more load next week. And then if you're a girl and
you're on your cycle, then like that is. That's a big deal. Like for some
women. Like you get like a like 30% drop in strength. Like
if you're one of outliers and a 30% drop in strength and you,
you're in a peak, like that's going to make you feel pretty shit. Unless you're
(18:40):
using velocity systems. Right. In which case we can still apply
the same central stress that you're still straining as hard without
the burden of having loading. Okay. So the
way we kind of accommodate this is that partly with stress
index. Okay. Which, which is super good because we, we keep
the level of stress similar over time. And as you get
(19:02):
stronger, the RPE of whatever weight is
will go down because you're stronger or the weight will go up at the same
RPE if you want to do it to maintain a level of stress which is
recoverable from the other way that
we're kind of looking at progress. I kind
of lost my train of thought a little bit here. So ask me the question
(19:23):
again. Is it. Yeah, I got excited about
a bunch of stuff. I got lost and was thinking
about my next questions actually. Okay. So it was
progressing over time. Yeah. So we have this
idea that progress only happens when you earn
progress as well. So if
(19:47):
you are keeping going and you're
seeing positive change over time, you're
unlikely in the current state of the program or the
whole kind of stuff to get change. Because why would
you. If I'm consistently putting 10 pounds on
any lift, like I'm in a good place and there is no need
(20:09):
to mess with that. That's like, that's. That's gold. And
when that stops happening, then we see a change and
that change is done by looking where the weak
points are. So we see that with our either
pose estimation model or where we see changes
in rate of acceleration. That's a new bit that's coming
(20:31):
soon as. I mean the guy spoke about that a couple days ago
and that would say. Okay, well we're going to choose
an exercise which biases training of
the. What can we call a weak zones or slow zones or the
point where deceleration starts. This is really important. I think we
spoke about it before that. Yeah, yeah, we did. We did. I think we use
(20:54):
Kitty as an example of the focusing on those deceleration
points and yeah, rather than, rather than. The place you
stop, it's a place that your force output starts decreasing. And
app, which I can see that. Yeah, the app knows where
those points are. Yeah, yeah. Which is incredible. So you actually get
better exercise choices because going back to this idea of dynamic
(21:16):
correspondence, it has a better idea of what's going to have a
good impression. Yep. So we're seeing that you quit
making progress. The app is going to look at, you know, those lifts, look
at where the deceleration point is, and then choose exercises
specific to addressing those as an example.
Yeah, that's exactly it. And it's not just primary
(21:39):
exercises. It will pick the secondary exercises and the accessories that go with
that as well. The whole system
is driven by how you're performing as an
athlete, which is driven by how you're recovering. Right. It's driven by what
stress loads you're under. And that's individual to the person. But that.
That's coaching. That's what. That's what coaching us. Yeah. So
(22:01):
let's talk about those stress levels too, because we talked about when we were
walking through adaptive modulators, the difference where
maybe the velocity metrics are remaining exactly the same, but all of a sudden
we see a change in
the perceived effort of a set. How does
that feed into the program? Yeah.
(22:24):
So this is where we start. Do we talk about z values in this
one? Essentially this statistical. Yeah, so we did. That's what
I was referring to was the Z values, because
not. I don't know anybody. Well, there's certainly no apps, I think, that
are looking at, because they can't calculate the actual.
The mechanical component of it. Right. Which we're doing. We're
(22:47):
not just. Yeah, so we're looking at
the change in standard deviation over time, which is
just a really fancy way of saying is, is this abnormal for you?
But there's a normal amount of deviation. There's a normal amount of up and down
that people's training, if it's outside of that, like you're saying, like,
we'll see about a week or two where your stress just starts going up
(23:11):
super high, but your RPE is the same weight away above
where the app predicts they will be.
That might be a sign for some sort of
lowering stress. Okay. Now, we could call it a deload.
I wouldn't. I don't think. I don't think deloads are really a thing that we.
We do per se. We just see a reduction in stress.
(23:33):
Yes. Yeah. Because a deload implies like
a. Like taking time off.
Right. And we don't want that. We don't want to take away from someone's
resilience by. By saying we're going to stop Doing
this, we just dial it back until you can get in a good place from
doing this. Yeah. So it may be a reduction in set
(23:55):
numbers, it may be a reduction in
rpa, but it's never going to be a,
hey, we're going to change everything up because you might be slightly stressed
out. So if we start seeing those said
values change in a significant manner, the program
isn't going to deload, but it's going to start reducing some of the stresses to
(24:16):
get you back online till we see a return
to the state where I would like to see, well, progress.
Yeah, yeah. So you could call it deload, but it's not
traditional deload, right? Yeah, I think traditional deloads I've
done. I think I've done videos that, like 10 years, 15 years ago
around. Yeah. A true, like
(24:38):
deload, like where you've got to take a week off or very minimally trained for
a week. You know, we've got a fault that's pushing way too hard on
the program if you're required to do that. And over time, you're going to end
up with potential for, you know, injury, likely because you're over pushing in
those, those sessions. Right. Which is what
I achieved in those years where I did that traditional
(25:00):
conjugate training, I think, from 2003
to 2012. And that's when the majority of my
injuries and surgeries were instigated. And I still have problems
to this day as it relates to that
period in, in, in my training history. Yeah,
absolutely. It's a really big deal. Like, there is a time and a place
(25:23):
for overreaching, but not overreaching to the
extent that you're, you're driving something to the ground
where you're purposely doing. It every, you know, three, four, five weeks.
Yeah, yeah. You're like two times a year, like twice. Like, I, I'm not a
huge fan of people competing more than three times a year. Like, I know it's.
If you're doing for fun, like, great. If you're doing it seriously
(25:45):
and you're really pushing yourself, like two or three times, plenty.
But that's like competitive powerlifting we're talking about. Yeah, yeah, competitive
powerlifting. Like, if you're truly, like prepping for a meet is
incredibly hard. Like those phases, when you're overreaching
to that level and you just feel like dog shit, like it's
impacting your work, it's impacting your family, it's impacting all these things because your mood,
(26:07):
your behavior, your sleep all these things are truly changing in that
period of time. That is not something like showing up for a
meet, you know, every few months. That's not. Yeah, that's his fault. But that's.
Yeah, that's how. That's a hobby, which is cool. Like, that's super cool to do.
I. I have a girl prepping for meet right now and it's just, she knows
it's for fun. She's going to PR because she's got stronger, but, like, she's definitely
(26:31):
not in the same place she was before, say, nationals. Yeah.
So let's talk about the, the pose estimation. Like, you know,
you're talking about measuring velocity with the pose estimation for your goblet
squats. I know that we're going to continue to advance that.
Like right now, I was talking about yesterday, I was doing my training. My
curls, my meadows rows, all these non traditional
(26:53):
metrics were, you know, we're measuring the velocity and the
stress with those because it's using a plate. But we're going to continue
to add more and more to the point. Like if I'm doing skull
crushers right now, I've got velocity. If I'm using a bar but not doing
press downs as of yet. But those are things that
will continue to add. What other ways are we using
(27:15):
that pose estimation to guide exercise
selection or, you know, any other correcting
movement inefficiencies? Yeah, that's a great question.
So to me, the pose estimation model is
like the most exciting part is because this is truly what no one's doing, because
there's apps which have velocity and there's apps that are programming. Not great programming, but
(27:36):
they got programming and no one's combining
them, but no one at all is doing the pose estimation, which
is incredible. So what this does
is it can work out from
either the position of your head or position of the bar bone
where your body parts are. So we can tell length of limbs, it
(27:58):
can tell the increase and decrease in joint angles, they can
tell rotation, and it just tells you your position space.
Now, this is a really big deal because this is what coaches look at.
If I'm looking at someone squatting, then
I'm not looking at them as a person squatting. I'm looking to see
what's happening at each individual joint section. But we have this idea of a joint
(28:21):
by joint approach. It's been popularized over a long time now.
Okay. And the app sees that and we have a
database of what and it's actually from the American
physiotherapist society, what joints should be able to do.
Okay. And if we don't see a joint
moving in a traditional way and it's not
(28:43):
good or bad, it's just what we would expect, then that
would then go on to influence preparation, bills, game. If
we see a squat happen or deadlift
happen in a way which is indicative of a
muscular deficit. Right. So if we see
someone deadlift and then they do this massive hitch, they see
(29:05):
the knees under the bar and drive up with the
quads. We're like, oh, dude, hamstrings. Depending on the hip
half, it'll be hamstrings might be shit or the glutes might
be shit, or they might just be bad at deadlifting, which is a
big deal. And the appeals that we'll be able to
tell from the changes within the position of the
(29:27):
barbell for joints and the start position
what the issue is and then prescribe to fix that. So
when you load up the app, there is
a very detailed now queuing system on there. So
you'll go into it and it will talk you through, hey, this is like
the points of a deadlift. So I think one of the good ones was
(29:50):
the deadlift to kneel deadlift chains.
It has like a couple of paragraphs of points like, hey, these are
the steps you go through if you know what a deadlift, great. Just use a
pose estimation model, use the stick figure frame that we
have to judge it and then see what the app says.
If you're unsure about how to depth it, this will walk you through it. It's
(30:14):
gonna be really hard to get it wrong if you listen to the
app. Yeah, that's incredible.
And we've got these into the movement prep plans right at the
beginning of the workout as well. So those are influenced by those.
Yeah, they will be. Yeah, yeah, they will be.
And then every exercise, obviously some pretty basic stuff.
(30:37):
Like you click on the exercise, there's a video of how to do it,
coaching cues, all of that in there. Yeah. Oh, there's something we should point out
first. You mentioned this. For your accessory work that
is taking velocity measurements of that, people
sandbag the shit out of their accessory work. I know.
You cannot do that on the app without it being like,
(30:59):
hey, you should be doing this heavier. And like, so all the
benefits, both like therapeutically
for like actual muscle gain and for
like consideration of balance. I'm not a huge fan of that term. I
don't think bodies should be balanced. But in terms of injury prevention, yeah, like
you should be pushing that kind of accessory work to build a more
(31:21):
robust body. You just can't sandbag it unless you're happy being like, oh, I'm
just going to take the weight down every time. And that's, that's not cool. All
right, guys. We talk a lot about mental resilience on this podcast, but
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is so common that people do some.
Do some heavy sets and then phone in all the accessory work, which
(32:26):
is VBT forces effort based
training, which is, you know how we termed that a
long time ago when we were talking about vbt. Is it? Yeah, it's
effort based training. So let's talk about the
holistic kind of approach to training with looking at these
variable stresses outside of training.
(32:49):
So we're talking about. This is the check in
model, right, that we talked about. Yeah. Okay. So we're collecting a
ton of data about either
like discomfort or sensations in training or after
training or collecting a ton of data about how you felt the
session went. I think we collect data
(33:11):
about seep as well right now, don't we? I don't think it's
in there as of yet. Although I did miss the last upload. I got to
update mine there was. Actually updated again this morning. So. Okay,
so maybe it is. Maybe. If not it will be soon.
Probably by the plan is there's. We haven't mentioned
this, but this is like a revive kind of module which I'm working on right
(33:32):
now, which will basically take a ton of recovery metrics into account.
Anyway, so we take a lot of these subjective kind
of sensational feedback
metrics. So when I say sensational, I mean like to do with the
senses. Yeah, it's cool. But you know what I'm saying?
And we're going to let those tell us how things are feeling.
(33:55):
So for example, if you feedback and you've had a couple of weeks
where you have like not an impingement in your shoulder, but like your shoulders a
little bit cranky, the app will recognize that
it's developing into a personal sensation and dial back
that specific kind of joint. So
I occasionally get some medial elbow pain
(34:17):
after bench pressing because my shoulders are fucked. The
app would actually take me off bench press if I
repeatedly showed stress on my elbow and then either
put it into tempo movements if it's one of the first times it's happened,
which is a great kind of recovery work for us, or it would actually shift
me into something which is less stressful to the body. Maybe a machine
(34:39):
press or a dumbbell press. Currently, I think the bias
is towards machines, which I'm totally for, because a more stable
environment is probably much, much better. And then from the
machine work you go to tempo work. And from tempo work it'll feed you back
into the main X exercise. And this is over a few weeks. But
if we look at like movement sensitivity and joint
(35:01):
sensitivity, like it might take that long. The future plans are
to drop into isometric work. We need the analgesic effect. There's
tons of stuff in the future coming there, but currently that's how it deals with
that kind of pain sensitive model. Yeah, and
I think we talked about that on a prior podcast. Not having
to just take complete time off from a certain body port or
(35:23):
joint with those methodologies. And why we chose.
We like choose machine and then tempo work
as ways of still adding load
but providing some time for the
desensitization of
those pain. Anything
(35:45):
else that as it relates to the app that you really want to
dive into.
I'm so immersed in the app right now that
like. Yeah, just everything,
I guess, but nothing specific. It's just. You want to talk about some
of the things that we're working on right with it. Oh, shit.
(36:07):
Yeah. So right. I do because I'm super excited about
stuff we're working on. So the way I picture the
progression of this is we go through like separate stages, steps
again and I give fancy names to them because I like that
the next couple of steps were actually kind of where we're at is working
(36:27):
on. I can't remember names right now,
but it's basically this automated feedback loop which we've just been speaking
about. And then the recovery stuff because when
we get inside that whole rest system, I think it's called, oh, I'm calling
it, at least we can start Being able
to be, to imply power
(36:49):
says, let's say we have a certain number of
recovery methodologies that we'd like to use. Okay. We might have
recovery methodologies that we just think are more effective.
For example, like having, like, and this is super underrated,
having dinner with your loved ones, like, that's
an incredible recovery tool. And it's something that
(37:12):
people probably don't think about now rather than being like,
hey, I'm going to go and pay 200 bucks for cryotherapy,
which, like, great, like reducing inflammation. Fantastic.
200 bucks for it. Probably not great. You see what I'm saying? Like,
maybe there's. Maybe that you can get a better bang for your buck than that.
And we'll be able to look at people's stress and
(37:34):
prescribe what we would expect to be the most efficient recovery
methodology to do for that one. Like, the way I think
about recovery is a nervous system based deal.
And what I'm kind of says, like really simplistically is
if you think it's relaxing, it's probably really good for
you. Right. So if you want to play computer
(37:56):
games, because that's what chills you out, I think that's
a legit recovery strategy if you want to have naps every day. Like,
I am religious about napping. I will, I will nap every
single day because it makes me feel better. Like my
life is better because I prioritize
like the recovery aspect of sleeping and
(38:18):
napping. Right. And the app will
algorithmically suggest that depending upon stress
levels, which is. That's super cool to me.
Yeah, it's a really big one. I think it's really underrated to be able to
prescribe or suggest recovery methodologies that are
as broad as like sitting in deep water. Really
(38:40):
big deal. Like that deload of the body, like, makes it way less
essentially all the way through to like, like, like literally having
dinner or going outside for a walk. It's a big deal.
Other stuff I'm excited about is the, the cardio aspect of things.
I'm really looking forward to. Yeah, pretty
excited. Yeah. Yeah. Like,
(39:03):
so I think about cardio in a very specific way about
oxygen delivery and utilization, which we've spoken about.
But there's something I've been working on very recently, which I'm not sure
I showed you yet, where we take critical power, which is the
sustainable amount of output that someone can have.
Now it varies person to person, but it's a pretty
(39:26):
steady number on depending on your fitness. Okay. And then we have
something called a w Prime, which is the gap between
critical power and maximum output. So let's say if
you're going for a walk and then
you have to really sprint, that sprint will go above critical power because
it's not sustainable all the way up to W prime.
(39:49):
If we know what someone's critical power is and we have a way to
test this out and we know the task
someone has to do, we can then program
really, really easily a way for them to be above
their critical power or have their critical power above the task
demand for the most part, which is insane because then
(40:11):
you can go. Okay, I have, let's just say.
Yeah, let's give some examples of what that would be.
Yeah, if we use,
we use the Army Fitness Test. Okay. Because that's, that's standardized. Okay.
So the Army Fitness test is one of a two mile run.
Right. I'm actually going to pull this up now because I have, I have the
(40:33):
information right in front of me. The two mile run, the army fitness test
means you have 12 and a half minutes to run two
miles to get a maximum score. Right. Because we only really care about getting a
maximum score, which means you have to run.
Let me find this out here. What's my speed?
15 kilometers an hour. Okay. Or
(40:56):
you have to have a constant power output
where we are, give or take
between 4 and 500 watts. Okay. Now
that probably slightly above most people's critical power, but if
you get your critical power around there, you wouldn't be
(41:17):
tired doing that run and you would pass that test of flying cards and we
can train up to that. You would need a VO2 max of
like 35, which is reasonable. Pretty
good. If you know the task demand,
the app will program it together. So let's
say I'm preparing for hunting season where I know I'm
(41:39):
going to have a 30 pound pack and I'm going to
spend a week, you know, climbing X
amount. You know, you, we would be able to input that
and you would actually be able to have your
training prepare you so that you could, you know, sustain
that week of, you know, going up and down these giant hills with a pack
(42:01):
on. Did I talk to you about this already? No.
Oh, okay. Well, ever happened? I don't know exactly
that. So I
actually wrote a Python script which analyzed binary topographical
data. So it will tell you
how hard going hunting would be and prepare you for
(42:23):
that. And the app will have information on it which will take
into account elevation or take into account change in elevation
distance of each thing together as it happens.
Hunting is is one of the things that it'll be really good at.
Yeah. We talked, we talked about rucking and I was just using
hunting as an example because I know so many people actually that do
(42:46):
physically prepare each season for this because they know
how much they're going to get shredded if they're not. So they, they start putting
a pack on, they're doing hiking, but they don't have necessarily a
targeted plan to get in shape knowing what they have to hit.
Yeah, this. And we'll have the data to do exactly
that like really, really well because I spent the entire
(43:08):
weekend, I think probably 10 to 12 hours each day
doing this. Yeah. Love it,
love it. Yeah. I just got, it's one of the things I'm
planning on taking quite a big interest in is scouting and kind of rocking in
the, in the wilderness. Okay. So
we got to get, we got. To get you move, move to Oregon here at
(43:29):
some point in time then. Yeah, that's the thing. Right. But yeah,
so it will do exact that and it will be able to do it from
anything from, they will be able to do it swimming, you'll be able to do
it with off like alpine skiing. If you're going to do ski
hunting or horseback riding, it will have the information there.
Yeah. So that will not be in our release coming
in. No, no, that, that's something that I literally did over the weekends. Yeah,
(43:53):
yeah, yeah, but that's that. Yeah. Well, I,
I, I, I want to reiterate there's a lot of complexity that we're talking about
here with science and data. But
really what makes this thing so cool is where it's
the simplicity with which we're meeting this innovation
(44:13):
and we're being very cognizant
of how many metrics we're also collecting and having you manually
input. We don't need to spend 15 minutes collecting
data that we're not using. So we're being very
conscious of how we're approaching the data collection that
is, that is input with these check ins as well and the
(44:35):
timing of when that check in is so that it's not influencing
you in a predictive manner around your training, which I think is,
is a miss. There's a lot of kind of psychological standpoints that
I think are missed with some of the products out there that may set
you up for having a bad day or bad training, depending on the approach
as well. Yeah, that's one of the things we spoke about a while
(44:58):
ago which was like if I ask you, hey, are you having a bad
day like, that influences the answer. And,
like, there's been a lot of coaching hours put towards this and a lot
of understanding of, like, what makes people think the way they
do. Okay. And rather than saying, hey, do you have a bad day?
Maybe we collect stuff afterwards. We try not to
(45:20):
influence the training by giving you a ton super
forehand. And a lot of the time, it's not that we don't let you tell
us the information. It's like, you don't have to tell us information. It's done.
It's. It's done. So you might have a recap. Okay.
And it might just be as simple as a 1 to 5. Let's say it
might be. It's as simple as a one to five scale. Yeah. Right. How
(45:43):
hard is this? It takes. I don't know how long it takes you, but it
takes me probably less than a minute to get back over it. Yeah, yeah,
yeah. So I'm super good that way. Well, I think this is
a pretty. Pretty good overview and a good
place to kind of wrap this up. I hope that people.
Yeah. Got a little bit more information about what we're doing again, you can review
(46:06):
the prior episodes if you want to dig into some of the science around
exercise selection, adaptive modulators, things
of that nature. But we're going to continue this series of
podcasts talking about the next generation
science of training and how we're having
technology meet. Meet this in the middle. And it's. It's
(46:29):
really cool. We're super excited. We've been absolutely loving this last
year of taking this to the final iteration that is about ready
to drop. Yeah, I'm excited. I'm, like,
genuinely quite excited about this. Yeah, yeah,
same, same, same.
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