End of course reflections

OK. Now we are actually at the end of this RITMO course on motion capture. And we have been going through how the body works, how we can name the different parts of the body, different types of technologies– motion capture, EMG, accelerometry, video analysis. And we have also been looking at some specific use cases of these technologies in various types of research. And to wrap these things up, what is kind of our main message of all of this? Why should people use motion capture, and why is it useful again?

Well, I’d like to sort of emphasise, at least from the perspective of music cognition, which is my field, like really the importance of the body and understanding how the body plays into different kinds of musical processes. Whether that’s communicative processes or just kind of meaning making of music, making sense of music, experiencing music, enjoying music– how all these things can be reflected in bodily motion or body movement.

And I guess this, again, kind of relates back to one of the challenges that we have with motion capture is the kind of the variety of different kinds of context in which we could study body motion and all this need to balance between the ecological validity– trying to study the phenomenon in its actual environment or having the environment as realistic as possible, versus having some degree of control over the circumstances. And which one is better? Exactly. Exactly. So these are the sort of dilemmas we have to really weigh on a daily basis, always, when we’re approaching a specific research topic.

It really depends on the exact question that you want to answer, which is sort of a combination of different settings, different motion capture methods. It’s really the most suitable to answer your question. So because in the research that we are doing at RITMO, often we use many different types of data capturing methods and different types of motion capture and physiological measurements at the same time. And also often combining both qualitative and quantitative ways of analysing these things. Because I guess what we have learned through the years is that it’s not really one or the other. It’s really the combination of these things which makes it interesting, right? Absolutely.

And when you get the most sort of– the fullest picture or the most kind of complimentary or comprehensive type of information about a phenomenon is when you actually combining the different methods of both collecting data as well as analysing it. And that’s perhaps also another thing that we have learned throughout this year is really that often we talk about a collaborative effort. Because doing the types of the things that we often want to do requires a lot of people. It requires a lot of equipment, but it also requires a lot of people and knowledge.

And that’s also why we are very focused now on trying to teach these things better, because we are combining methods that are not otherwise usually so easily combined. And that’s also what we’re struggling from a technological perspective, but also from a more general conceptual level, struggling to figure out how we need to combine these things together. So that’s one of the reasons we’re focused on motion capture in this particular course. But we have other courses also in the RITMO course series where you’re also able to learn about EEG, eye tracking, pupillometry as well. So if you haven’t taken those courses already, then you can go and check them out as well.