This document discusses non-negative matrix factorization (NMF) and its application to electromyography (EMG) sampled signals. NMF decomposes a non-negative data matrix into two non-negative matrices, approximating the original matrix. It has been used to extract muscle synergies from EMG data, with the data matrix representing EMG signals and the output matrices representing muscle synergies and their activations over time. The document also briefly compares FPGAs, microprocessors and microcontrollers for implementing NMF in real-time on hardware, noting that FPGAs allow real-time NMF with acceptable energy costs.