7. Analyzing time-varying data#
In biomechanics, we often process data that is function of time, e.g., electromyography, marker trajectories, force series, etc. When we analyze only a few data and that the sampling frequency is constant, using NumPy is usually sufficient. This is what we did in last section in the different NumPy exercises.
However, things can get more complicated when:
data are of different natures, such as marker trajectories, EMG, measured forces, calculated forces, etc.;
data were recorded by unsynchronized instruments at different sampling frequencies;
data were recorded with inconstant sample frequencies;
data are missing (e.g., occluded markers);
data are noisy;
etc.
For these reasons, Kinetics Toolkit provides a new type of variable: the TimeSeries.
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