Table 3.

Features categorisation for ML models.

Feature Category	Features	Number of Tri-Axial Features	Number of Magnitude * Features
Time	Root mean square, range, mean, variance, skew, kurtosis	18	6
Frequency	Dominant frequency, relative magnitude, moments of power spectral density (mean, standard deviation, skew, kurtosis)	18	6
Entropy	Sample entropy	3	1
Total for each sensor type		39	13

* The features were derived from the magnitude signals (Euclidean norm) of each sensor type within the IMU.