Modeling of surface myoelectric signals--Part II: Model-based signal interpretation.
Experimental electromyogram (EMG) data from the human biceps brachii were simulated using the model described in [10] 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.
Merletti
R
R
Department of Electronics, Politecnico di Torino, Italy.
Roy
S H
SH
Kupa
E
E
Roatta
S
S
Granata
A
A
D000200:Action Potentials / Q000502:physiology; D004558:Electric Stimulation; D004566:Electrodes; D004576:Electromyography; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000502:physiology*; D012815:Signal Processing, Computer-Assisted