Title :
Modeling of surface myoelectric signals. II. Model-based signal interpretation
Author :
Merletti, Roberto ; Roy, Serge H. ; Kupa, Edward ; Roatta, Silvestro ; Granata, Angelo
Author_Institution :
Dipt. di Elettronica, Politecnico di Torino, Italy
fDate :
7/1/1999 12:00:00 AM
Abstract :
For pt. I see ibid., vol. 46, no. 7, p. 810-20 (1999). Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in pt. I of this work. A multichannel linear electrode array, spanning the length of the biceps, was used to detect monopolar and bipolar signals, from which double differential signals were computed, during either voluntary or electrically elicited isometric contractions. For relatively low-level voluntary contractions (10%-30% of maximum force) individual firings of three to four-different motor units were identified and their waveforms were closely approximated by the model. Motor unit parameters such as depth, size, fiber orientation and length, location of innervation and tendonous zones, propagation velocity, and source width were estimated using the model. Two applications of the model are described. The first analyzes the effects of electrode rotation with respect to the muscle fiber direction and shows the possibility of conduction velocity (CV) over- and under-estimation. The second focuses on the myoelectric manifestations of fatigue during a sustained electrically elicited contraction and the interrelationship between muscle fiber CV, spectral and amplitude variables, and the length of the depolarization zone. It is concluded that a) surface EMG detection using an electrode array, when combined with a model of signal propagation, provides a useful method for understanding the physiological and anatomical determinants of EMG waveform characteristics and b) the model provides a way for the interpretation of fatigue plots.
Keywords :
electromyography; medical signal processing; physiological models; spectral analysis; EMG waveform characteristics; biceps; bipolar signals; depolarization zone length; double differential signals computation; electrical stimulation; electrode rotation effect; fatigue plots interpretation; fiber orientation; model-based signal interpretation; monopolar signals; motor unit parameters; multichannel linear electrode array; muscle fiber direction; propagation velocity; source width; surface myoelectric signals modeling; tendonous zones; Biomedical engineering; Computational modeling; Electrical stimulation; Electrodes; Electromyography; Fatigue; Humans; Muscles; Neuromuscular; Skin; Action Potentials; Electric Stimulation; Electrodes; Electromyography; Evoked Potentials; Humans; Isometric Contraction; Models, Biological; Muscle, Skeletal; Signal Processing, Computer-Assisted;
Journal_Title :
Biomedical Engineering, IEEE Transactions on