So we found two things. The first thing was that
there was certainly a better device. It was actually
pretty accurate. The level of accuracy was the
maximum error that we found was around 0 .01
meter per second. And we also found that this
error was unbiased. This means that there was
no preference in this device to overestimate
or underestimate the actual velocity of the device.
during testing while most of the other devices
that we found actually presented a bias. Hi Francesco,
it's my pleasure to have you the second time.
The first time we've been talking muscle activation,
using straps, not using straps, and this time
we'll be talking about velocity. But before we
get there, could you please briefly introduce
yourself? My name is Francesco Travascio and
I'm Associate Professor at the Department of
Mechanical and Aerospace Engineering of the University
of Miami. I'm also a Master Weightlifter and
I really enjoy doing studies in weightlifting
and sports related biomechanics. So we're talking
velocity, measurement of velocity in weightlifting
movements. If you would tell me first why you
decided to set up the study. Well, I was very
fascinated about the training methodology based
on barbell velocity. I find it that in principle,
it seems to me a very rational approach to the
optimization of the performance of the athlete.
At that time, there were a number of devices
that were used for it. tracking the bar per velocity,
obviously the first thing that we started to
do was to look into those that could be more
immediately available for a general user. And
we looked into camera apps, phones or tablets,
and we found one that at that time seemed to
us a very interesting type of app, very, very
nice. And we also wanted to compare the accuracy
of this system, obviously with our gold standard
that is within a gate lab and motion capture.
system. It was an OptiTrac system that we used.
Another problem that we found, and we actually
couldn't find a practical solution for that,
was the fact that some of these devices are built
as boxes with a rotational encoder and a wire
that is attached to the side of the barbell.
When the barbell is lifted, a cable is pulled
out of this device, and the rotational encoder
measures the number of rotations, and there's
a timer. So by the number of rotations, the timers
can determine distance and time. to determine
the velocity. The problem is that when you throw
the bar on the ground, you have to be very careful
not to throw it on the device. Eventually, it
happened. I think Murphy's Law. It happened that
one of these devices was smashed, and so we had
to purchase a new one. Together with these devices,
we also used another very interesting device
that is a laser positional device. Essentially,
it's a device that is attached to the end of
the barbell and has a sensor that emits the light.
that is reflected by a surface and then receives
the light back. So by measuring how much time
it takes from the light to get out of the sensor
and coming back, you can determine essentially
the distance of the barber from the floor. It
was a very neat device. I really liked it. The
only cumbersome aspect of it is that you really
need to have a reflecting surface, an appropriate
reflecting surface. In fact, the device comes
together with a little mat of a reflecting surface.
Overall, I think that the iPhone app is probably
one of those most practical things you can possibly
do because everyone has a phone nowadays. And,
you know, it's quite simple to set up. It only
requires to establish a distance of around 3
to 10 meters. So we are talking about between
10 and 30 feet distance from the lifter. Possibly
being on the side of the lifter, catching the
thermal weight in the surgical plate. And it's
quite practical. All right. So let's bring the
design of the study together. Could you list
the devices and then what you compared it to
to get the accuracy? Sure. So we had a total
of five devices. We had what is called the Jim
Aware RS, a Vitro, a Gravity Box. And then those
three essentially are boxes with a cable. The
principle of function is always the same. Then
we had the Kinetic Flex, the device that is applied
on the side of the barbell. And then we had the
phone app that was called the WL Analysis, Reclinic
analysis. So three linear transducers, one laser.
the laser -based measurement tool and one phone
app, so camera, 2D camera -based measurement.
Yeah, that is correct. And your gold standard
was? Our gold standard was our motion capture
system, an Optidrug system that included 12 cameras.
Awesome. Obviously, to make it work, track the
movement of the barbell, we had to apply a marker
to the barbell. We applied the marker to the
side of the barbell. It's essentially, it's a
reflective sphere. We performed the measurement,
all the measurements simultaneously. We had on
one side, the two linear transducers and the
reflective marker. On the other side, one linear
transducer and the Kinect Flex. Awesome. And
obviously the phone. Yes, the phone on the side
and 12 cameras around for the touching system.
Correct, yes. Now, who were the participants?
Who did you invite to the study? Those were athletes
competing at regional and national levels. Most
of them were from a local gym. But there were
a wee session. We advertised the study in all.
Florida in our state and actually we were very
pleased by a couple of athletes that came from
Tampa which is located five hours driving from
Miami and they explicitly came to Miami and they
drove for five hours just to be part of the study
and this was really incredible. In terms of comparing
the devices what measurements did you decide
to use and what movements did you pass? So for
the measurements we essentially we the barbell
velocity in clean and in snatch. We left to the
participants to decide whether they wanted to
power or to execute the full movement of all
the pieces. And we wanted to measure the barbell
velocity at different percentages of the maximum
effort just to see if there are any changes in
the accuracy of the devices as the velocity increases
or decreases. So we decided to make sure that
every lift was a proper lift. And also for probably
safety reasons, we wanted to limit the percentage
of effort to 70%. So we had lifts executed at
40 % and at 70%. Essentially at 40%, probably
the barbell velocity at that point is probably
quite high, I would say. But at 70 % still, you
have a pretty high speed of the barbell. The
numbers, what are the average, more like median
velocity of the barbell? would be at 40 %? We
are in the range of two meters per second. There
are some values of barber velocity that have
been measured in the past, many, many years ago.
And well, I mean, but those measurements were
performed on elite athletes. And obviously, I
believe that the elite is always, you know, biomechanically
speaking, is a different animal rather compared
to the normal population of excellent athletes,
but still at regional and national levels. They
are probably more similar. humans. In terms of
clean, we are talking at 40%, we are talking
about 2 .3 meters per second. We take it at 70
% is about 1 .93 meters per second. And for the
snatch, it's a little bit faster. It's about
2 .5 or 40 % and around 2 .2, around 70%. Awesome.
Was it mean velocity or peak velocity you were
measuring? No, we are talking about peak velocity.
We were interested in measuring the peak velocity
because it would just make more sense in my opinion
within generally in powerlifting the measurements
that are reported refer to the peak velocity
as well as the mean velocity within the entire
lift but we wanted to focus only on a variable
that in our view made more sense for the sport
that is essentially the peak velocity which expresses
the maximum power you can express we measure
the three repetitions per lift per at 40 percent
three repetitions per lift that's seven percent
and we averaged the measurements and essentially
what we did was to measure these velocities with
all these devices these peak velocities with
all these devices and compare them to the gold
standard that was the motion capture system and
calculate the error essentially we calculated
that the error as the difference between the
measurement with the device versus the measurement
with the motion capture system and the errors
made that we found for all the values that we
All the leads that we measured would vary between,
in the lowest case, like 0 .01 meter per second
up to almost 0 .2 meters per second. Let's start
from the most important thing. So which one,
which of the devices, if any, was the most accurate?
So we found two things. The first thing was that
there was certainly a better device. That was
the GymAware. It was actually pretty accurate.
The level of accuracy was the maximum error that
we found was around 0 .01 meter per second. And
we also found that this error was unbiased. This
means that there was no preference in this device
to overestimate or underestimate the actual velocity
of the device of the barbell during testing,
while most of the other devices that we found
actually presented a bias, meaning that the flex
device, owner and the truth box presented a negative
bias meaning that they tended to underestimate
the actual peak velocity and these underestimations
were up to 0 .18 0 .17 meter per second now in
order to get a sense of how important is this
error if we would extrapolate The value of the
velocity of an athlete from 60 % to 100 % represents
the one repetition max. When we are in the region
of the 95 % to 100%, which is the region that
most matters to us because it's the peak of the
performance of this person, that change in the
power back velocity could be of 0 .1 billion
per second or probably less. So essentially having
an error for almost a double, 0 .15, 0 .17. represents
a great limitation in this device for this particular
application. Regarding, we actually was, I mean,
obviously all these devices have a different
cost associated to it, right? So the GymAware
device was represented the most expensive type
of device and something that is probably not
immediately accessible to the general user because
we are talking about around $2 ,000 or $3 ,000
to purchase it versus a phone app that is free
or $9 without. advertisements right so we were
a little bit disheartened when we found that
the phone app actually presented this big limitation
but i believe that the main limitation of the
phone app is not on the algorithm that actually
calculates the velocity of the barbell the limitation
is essentially in frame per second that the phone
can can acquire. So, initially, if you could
have a phone that has, or a tablet, or any device
that has a larger frame per fps compared to a
regular iPhone or an Android, it is highly possible
that you could significantly reduce the error
in the estimate. The advantage of this, so one
tool of this... Well, could we just explain why
frames per second matter? Why they are the limitation?
Sure, absolutely. Essentially, the software that
is used in this in these applications essentially
tracks the position of the plate frame by frame.
So by tracking the position, it tracks the position
of the plate and refers this position of the
plate to an origin of a system of reference.
So when the lifter is about to start, the plate
is in the lowest position. So the app generally
boxes the plate into a square and determines
the center of the square. The center of the square
would be the origin of the motion of the parallel.
As the frames go by, the position of that square
that identifies the position of the plate changes
in space. So a new center of the plate is identified
and obviously a new center has a different coordinate,
different distance from the ground, right? That's
what we want to measure. Now, the problem is
if we don't have enough temporal resolution of
the images, in other words, if we have only few
images of the lift, we may miss the actual peak
moment in which there is the maximum... extension
of the barbell before the velocity starts to
reduce. So essentially by increasing the number
of frames per second that you can get, you may
not, you would eventually reduce the possibility
of making an underestimate or more overestimate
of the actual velocity. So the camera is measuring
here. The next photo is taken here. If the peak
velocity happens here, that's missed. So when
you have this and this. Exactly. You're essentially
missing. Or the larger is the number of pictures
that you can take, allows you to take a better,
to a pricing with a higher precision, the moment
in which you attain the peak velocity, essentially.
So for the mean velocity, maybe it's not such
a big problem because you kind of average all
the measurements across the whole movement, like,
for example, in squat. But for snatch and clean,
where the movements are very fast, this loss
of data is quite significant and will impact.
accuracy. Yes, absolutely. I agree. And it's
also a matter of, yes, absolutely. Okay. So Gmware,
the most accurate, unfortunately the most expensive,
then phone app probably would be more accurate
if the camera would be better. So maybe in a
few years we will get there where the general
phone camera will be sampling in 120 or maybe
more, I don't know. I believe that you should
go for a higher than 120 probably. Yes, probably
you should have. The good thing of the phone
app is that you can also upload videos and analyze
the videos. So, for instance, if you could acquire
data with a GoPro camera that is pretty good
at taking images with a very large number of
frames per second, you could upload this video
into your phone or tablet or whatever device
you want to use and analyze the data with this
phone application. Obviously, this defeats the
purpose of the practical aspect of having a phone.
the gym and measuring on the spot. So it makes
further, it increases the difficulty of the logistic,
if you want, the logistic complexity of implementing
a parallel velocity training system. But you
could set it up at the competition. So it's,
you know, measuring maximal effort at the right
environment, the optimal environment, which is
a competition for a weightlifter without even
touching the lifter. Absolutely. Yes. That's
minimally invasive. I mean, it's non -invasive
essentially. Yes. So I just wanted to move to
Flex device and, oh yeah, these two. So could
you comment on these? How did they perform in
terms of accuracy and what were the problems?
So the V -Trub also had a performance that was
comparable to the phone app. And it's also true
that V -Trub was the lowest cost position device
of the three that we tested. Flex also had an
error that was in the neighborhood of 0 .1 meter
per second, a little bit more than. 0 .1 0 .12
meter per second according to the type of lift
probably gravity box was the next best device
after the gym aware still included an error of
0 .1 meter per second in the clean at the box
and 0 .05 meters per second for a snatch so in
my opinion still difficult to would be still
problematic when you are interested in to determine
the actual peak velocity at very high percentages
Do you think if obviously many coaches, most
of the coaches will not have access to motion
capture. So this level of data accuracy is unattainable
for a casual coach or the coach who is not working
in a sports center or Olympics preparation center.
So would it be still worth buying a linear transducers
or they are basically at the level, apart from
DreamAware, that is pretty accurate. Are they
at the level of the mobile? How do they, from
the practical sense, how do they line up? Well,
I mean, from the practical sense, I think that
besides Gemaware, that it showed to be extremely
accurate compared to the others. These other
linear transducers, in my opinion, are not, in
my opinion, they are not designed in a way. Well,
they could be certainly used for this purpose
with all their limitations in accuracy. But I
think that the main limitation is the risk that
you can actually break them because of the nature
of the type of lift that you do. So I wouldn't
feel comfortable in a gym. If I were a gym owner,
I wouldn't be comfortable in purchasing such
a device with the high risk that this can be.
It is very possible that you can break it. Me
personally, as a user, as an athlete, I wouldn't
make this type of investment personally. Okay,
how about the Flex device, the laser optical
one? Well, the Flex device actually still presented,
in my opinion, still presented an error that
is... almost comparable to the phone app. We
are comparing, in terms of snatch, we are comparing
an error that is 0 .1 versus 0 .1. We are pretty
much there in terms of errors. So I wouldn't
make that investment. It's a very cool tool,
I think. The principle is very interesting. It's
a very nice tool, but according to the data that
we report, it's probably not the best. Do you
think it is related, or maybe I will ask it differently,
why do you think it didn't perform that well?
I am not sure, honestly. I don't know if the
problem is making sure that there is the right
illumination, the surface presents wrinkles,
the reflective surface, the matte that you place
underneath presents wrinkles, or there are differences
in the index of reflection within the matte,
or there must be some dust. that changes this
index of reflection and probably can change something.
I don't know. honestly why he didn't perform
in he didn't perform as expected at the end i
always ask a question about the favorite lift
i asked you before so if people are interested
they have to go to the previous interview and
i have a different question for you you are very
well versed on both sides the research in weightlifting
and the practical side you are an athlete and
you try the velocity for programming and so on
so you are a coach too now if you could change
one think in Olympic weightlifting as a sport,
what would it be? Wow. I think that the sport
as it is conceived is very simple, right? Because
it's probably, I would say, a better way of determining
and an objective way to determine whether the
lift is valid or not. I mean, we talk about pressing
and position angle of the elbows in pressing,
in snatch and in the jerk pace. If we could have
a system implemented that that can objectively
determine whether or not the link is valid. Well,
there is actually a system. They could actually
replay, but maybe in real time, I don't know.
Yeah, just to make this experience a little bit
transparent, more transparent for the audience,
I guess. Yes. All right, fair point. Now, where
people can find you if they want to follow your
work or contact you about your research? Oh,
well, they can look up our website, and we also
have a Twitter account, and every time that we
publish a new research, or there is a new thing
going on in our lab, we always tweet and they
can always consult for any type of information
regarding us on the website of the University
of Miami, Florida. And could you mention the
handle for the Twitter account? Yes, that would
be um underscore biomech. Awesome. Thank you,
Francesco. It was a pleasure. It was my pleasure.