Comparison of Particle Filter to Established Filtering Methods in Electromyography Biofeedback

Surface electromyography (sEMG) is a potentially useful signal that can provide therapeutic biofeedback. However, sEMG signal processing is difficult because of the low signal-to-noise ratio and non-stationarity of the raw signal. Conventional online filters often suffer from a compromise between smoothness and responsiveness. Here we propose a new particle filtering method for sEMG processing and compare it to established filtering methods. A...