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 fr
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BioMediTech Institute and Faculty of Biomedical Sciences and Engineering, Tampere University of Technology, Tampere, Finland
Abstract— 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 highfrequency 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. Keywords— electromyography, functional electrical stimulation, filtering, stimulation artifact
I. I NTRODUCTION Neuroprosthetic devices are used to restore functionality that is missing or lacking due to paralysis or disability. Functional electrical stimulation can be used to cause muscle contractions. Electromyography (EMG) on the other hand can be used to measure muscle activity for controlling the stimulation. However, so called stimulation artifact can cause problems in applications that measure EMG simultaneously when carrying out electrical stimulation [1]. The stimulus voltages can be hundreds of volts while the EMG amplitudes may be only in the order of tens of microvolts. Artifacts can distort the EMG measurements and render them unusable for reliable detection of muscle activity levels. Low-amplitude artifacts can be digitally removed but it is impossible if the EMG measurement amplifiers become saturated. Unilateral facial paralysis causes facial functions on one side of the face to be missing or lacking. Facial pacing refers to neuroprosthetic technology for reanimating the disabled © Springer Nature Singapore Pte Ltd. 2018 H. Eskola et al. (eds.), EMBEC & NBC 2017, IFMBE Proceedings 65, DOI: 10.1007/978-981-10-5122-7_106
side of the face based on the measurements of the healthy side. The principle was introduced four decades ago [2]. Reliable measurement of muscle contraction intensities, controlled production of muscle contractions, and low latency between these two to achieve symmetric and synchronous facial expressions are basic requirements for the pacing. Most people notice a delay in an eye blink when it exceed 33 ms between the eyes, but other movements allow longer delays between the sides of the face go unnoticed [3]. The simplest approach for handling EMG measurements contaminat
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