WEBVTT

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OK.

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Now we are actually at the
end of this RITMO course

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on motion capture.

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And we have been going
through how the body works,

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how we can name the
different parts of the body,

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different types of
technologies-- motion capture,

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EMG, accelerometry,
video analysis.

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And we have also been
looking at some specific use

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cases of these technologies
in various types of research.

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And to wrap these
things up, what

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is kind of our main
message of all of this?

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Why should people
use motion capture,

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and why is it useful again?

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Well, I'd like to
sort of emphasise,

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at least from the perspective
of music cognition, which

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is my field, like
really the importance

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of the body and
understanding how

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the body plays into different
kinds of musical processes.

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Whether that's
communicative processes

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or just kind of meaning
making of music,

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making sense of music,
experiencing music, enjoying

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music--

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how all these things can be
reflected in bodily motion

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or body movement.

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And I guess this, again,
kind of relates back

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to one of the challenges that
we have with motion capture

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is the kind of the variety
of different kinds of context

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in which we could
study body motion

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and all this need
to balance between

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the ecological validity--
trying to study

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the phenomenon in its
actual environment

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or having the environment
as realistic as possible,

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versus having some degree of
control over the circumstances.

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And which one is better?

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Exactly.

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Exactly.

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So these are the
sort of dilemmas

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we have to really
weigh on a daily basis,

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always, when we're approaching
a specific research topic.

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It really depends on
the exact question

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that you want to
answer, which is

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sort of a combination
of different settings,

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different motion
capture methods.

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It's really the most suitable
to answer your question.

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So because in the research that
we are doing at RITMO, often

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we use many different types
of data capturing methods

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and different types of motion
capture and physiological

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measurements at the same time.

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And also often combining both
qualitative and quantitative

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ways of analysing these things.

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Because I guess what we have
learned through the years

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is that it's not really
one or the other.

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It's really the
combination of these things

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which makes it
interesting, right?

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Absolutely.

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And when you get
the most sort of--

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the fullest picture or the
most kind of complimentary

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or comprehensive type of
information about a phenomenon

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is when you actually combining
the different methods of both

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collecting data as
well as analysing it.

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And that's perhaps
also another thing

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that we have learned
throughout this year

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is really that often we talk
about a collaborative effort.

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Because doing the types of the
things that we often want to do

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requires a lot of people.

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It requires a lot of
equipment, but it also

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requires a lot of
people and knowledge.

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And that's also why
we are very focused

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now on trying to teach
these things better,

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because we are combining
methods that are not otherwise

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usually so easily combined.

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And that's also what
we're struggling

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from a technological
perspective,

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but also from a more
general conceptual level,

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struggling to figure out
how we need to combine

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these things together.

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So that's one of
the reasons we're

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focused on motion capture
in this particular course.

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But we have other courses also
in the RITMO course series

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where you're also able to
learn about EEG, eye tracking,

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pupillometry as well.

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So if you haven't taken
those courses already,

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then you can go and
check them out as well.

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