Affiliations: [a] Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA | [b] Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX, USA | [c] The Neurorehabilitation Research Laboratory, The Institute of Rehabilitation and Research (TIRR)-Memorial Hermann Hospital, Houston, TX, USA | [d] Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA | [e] Institute of Biomedical Engineering, University of Science and Technology of China, Hefei, China
Correspondence:
[*]
Address for correspondence: Ping Zhou, PhD, SMPP, RIC, 345 E Superior St, Suite 1406, Chicago, IL 60611, USA.
Tel.: +1 312 238 1365; E-mail: [email protected]
Abstract: Background:Electrical stimulation of muscle or nerve is a very useful technique for understanding of muscle activity and its pathological changes for both diagnostic and therapeutic purposes. During electrical stimulation of a muscle, the recorded M wave is often contaminated by a stimulus artifact. The stimulus artifact must be removed for appropriate analysis and interpretation of M waves. Objectives:The objective of this study was to develop a novel software based method to remove stimulus artifacts contaminating or superimposing with electrically evoked surface electromyography (EMG) or M wave signals. Methods:The multiple stage method uses a series of signal processing techniques, including highlighting and detection of stimulus artifacts using Savitzky-Golay filtering, estimation of the artifact contaminated region with Otsu thresholding, and reconstruction of such region using signal interpolation and smoothing. The developed method was tested using M wave signals recorded from biceps brachii muscles by a linear surface electrode array. To evaluate the performance, a series of semi-synthetic signals were constructed from clean M wave and stimulus artifact recordings with different degrees of overlap between them. Results:The effectiveness of the developed method was quantified by a significant increase in correlation coefficient and a significant decrease in root mean square error between the clean M wave and the reconstructed M wave, compared with those between the clean M wave and the originally contaminated signal. The validity of the developed method was also demonstrated when tested on each channel's M wave recording using a linear electrode array. Conclusions:The developed method can suppress stimulus artifacts contaminating M wave recordings.
Keywords: M wave, stimulus artifact suppression, electromyography (EMG)
