A Framework of Temporal-Spatial Descriptors-Based Feature Extraction for Improved Myoelectric Pattern Recognition
getTSDfeat is a feature extraction algorithm for any kind of signals, although this was mainly developed for myoelectric, a.k.a, Electromyogram (EMG), signal feature extraction for prostheses control.
The algorithm extracts 7 features from each channel individually, and from the combination of NCC channels to extract few features including:
- 3 time-domain driven spectral moments
- 1 Sparsiness measure
- 1 Irregularity factor
- 1 Coefficient of Variation
- 1 Teager–Kaiser energy operator
You will need to specify the window size and window increment.
As this is a matlab function (adding a python version soon), then usage is really simple, just call this function by submitting the signals matrix (denoted as variable x) as input
feat = getTSDfeat(x,winsize,wininc)
x columns of signals (rows are samples and column are the signals).
winsize window size.
wininc how much to slid the windows by.
feat extracted features from all channels/combinations of channels