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sEMG BSS on PULP

Blind source separation of sEMG signals on PULP platform (inference only). This code has been used in the paper Mattia Orlandi et al., sEMG Neural Spikes Reconstruction for Gesture Recognition on a Low-Power Multicore Processor. In: Biomedical Circuits and Systems.

Usage

First of all, use docker-compose run --rm semg-bss-online to run the container and open a shell. Then, move to the directory containing the project (i.e., ~/semg-bss-online) and compile it using make clean all; you can set the following variables:

  • NUM_CORES: number of cores to use (from 1 to 8);
  • FS: sampling frequency of the sEMG signal;
  • WIN_LEN: length (in ms) of the sEMG signal;
  • N_CH: number of sEMG channels;
  • FE: extension factor used by the BSS algorithm;
  • N_MU: number of motor units discovered during the training phase;
  • Q: number of time steps processed at a time;
  • N_TA: number of hidden neurons in the temporal aggregation layer;
  • N_CA: number of hidden neurons in the channel aggregation layer;
  • N_OUT: number of output classes;
  • USE_SVM: whether to use the Support Vector Machine or the Multilayer Perceptron.

Finally, the program can be run with make run.