Okay, all right, so we move to the next discussion, which is Francois lectures.

So first of all, did you enjoy it?

So by the way, I didn't introduce Sebastian, but Sebastian is a friend of mine and he visited

us and he's a PhD student at the Olympic German Institute of Sport.

So you probably see him in television when we will win a gold medal, when Germany will

win a gold medal.

But he's also very interested in EMG because he has many applications with sport.

They are not only like in disease, because we talked a lot in this course about disease

and pathology.

We just touched base actually, didn't talk a lot about that.

We just touched base on some stuff, but he has many applications on sport, especially

for the prediction of performance and fatigue.

So if now we move to the next, so we will discuss about Francois presentation on muscle

synergy.

So Francois gave a nice presentation on his work.

This is quite a lot of work.

He did a very nice presentation that was about 14 minutes of all of the studies and the tests

being involved in muscle coordination.

So the problem is that when we grasp an object or whatever, the brain is actually controlling

multiple degrees of freedom.

So many muscles, but he does it this is such an easy way.

It's really easy.

And how does the brain accomplish this task?

There are many theories.

One theory is that there is one common drive that drives all these muscles and is commonality

has been measured by using the EMG many muscle and looking then you can apply different techniques.

One is the negative matrix factorization, that is a blind source separation sort of

is a clustering approach, right?

And identify these clusters and then you see these clusters, how much balance they explain.

So did you enjoy the lecture? Do you have any other questions? This is really now completely

up to you. It's an open discussion. Please, if you have any questions about the lecture,

go on. Otherwise, I will start picking names. I will start picking names as a question.

As I see on my screen. So the first on top right is Raoul. Did you enjoy the lecture?

Yeah, I enjoyed it a bit, especially because I work right now in gate analysis and it was

a nice combination of both. Nice. Nice. And do you have any, what was your highlight or

do you have any questions? My highlight? Well, let's say, let's say we talked about the thrift

right? And I think that's very interesting. But I also like the approach that he used

with the neural network. Like basically, he used some sort of an vector machine, I think.

And obviously that's a little bit basic, but I think it's still, if it does the job, I

think it's really nice. Yeah. Yeah. It does the job. And it was nice that he said that,

you know, it's because, you know, sometimes with EMG, you need to be careful when you

use, you want to predict stuff, you want to predict the variables from the two cluster

individual subjects, because, you know, we know, yeah, it's a black box at the end of

the day, but that seems that it works well. So then Jonas, I have you as my next one.

Did you enjoy the lecture? Do you have any questions about it? I have to be honest, I

haven't seen it so far. Okay. So I cannot judge. Okay. Okay. Yeah. I suggest you take

a look at it. It's a very nice one. Yeah. But no problem. And yeah, I really do. Clementine

and you, did you? I really enjoyed the presentation. And there was a question during this by Joanna,

I think, according to the edge and the gate, like, if there is a difference between the

individual, according to the edge. And I saw in another lecture that our gate evolve during,