Jie Liu1, Sheng Li2, Xiaoyan Li1, Cliff Klein1, William Z Rymer3, Ping Zhou4. 1. Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA. 2. Department of Physical Medicine and Rehabilitation, University of Texas Health Science Center at Houston, Houston, TX, USA The Neurorehabilitation Research Laboratory, The Institute of Rehabilitation and Research (TIRR)-Memorial Hermann Hospital, Houston, TX, USA. 3. Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA. 4. Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL, USA Department of Physical Medicine and Rehabilitation, Northwestern University, Chicago, IL, USA Institute of Biomedical Engineering, University of Science and Technology of China, Hefei, China.
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.
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.
Entities:
Keywords:
M wave; electromyography (EMG); stimulus artifact suppression
Authors: Mamede de Carvalho; Adriano Chio; Reinhard Dengler; Martin Hecht; Markus Weber; Michael Swash Journal: Amyotroph Lateral Scler Other Motor Neuron Disord Date: 2005-03