Stimulation Waveform Selection to Suppress Functional Electrical Stimulation Artifact from Surface EMG Signals

We present a simple method to suppress the artifact that functional electrical stimulation causes to surface electromyography signals. The method is based on selecting a high frequency sinusoidal wavelet as the stimulation waveform to make the artifact frequencies easily removable from the measured signals, and combining it with simple filters in the hardware and as digital filters. Our theoretical computations demonstrate how the selected stimulus pulses attenuate significantly compared to commonly used square wave pulses already in a first-order low-pass filter used before the measurement amplifier. The experimental results with 8 participants show that the artifacts can be suppressed in our target application: facial pacing for unilateral facial paralysis. The method can be beneficial also for other neuroprosthetic applications that apply functional electrical stimulation in combination with electromyography measurements. More complex artifact suppression methods are unnecessary and the delays of the processing are caused only by the simple filters in the signal processing chain.