Title :
Improving detection of muscle activation intervals
Author :
Micera, S. ; Vannozzi, G. ; Sabatini, A.M. ; Dario, P.
Author_Institution :
Scuola Superiore Sant´´Anna, Pisa, Italy
Abstract :
In this article the characteristics of traditional and novel algorithms for the detection of the onset (and offset) of muscle contraction using EMG signals have been briefly summarized. As is evident from these descriptions, many studies have been carried out in the last few years in order to improve the accuracy of the detection and to make the performance of the algorithm less dependent on the skill of the operator
Keywords :
Gaussian distribution; electromyography; feature extraction; maximum likelihood detection; medical signal detection; medical signal processing; statistical analysis; EMG signals; computerized approach; double-threshold detector; feature extraction; generalized likelihood ratio test; motor-related events; muscle activation intervals detection; muscle contraction; single-threshold method; statistical algorithms; Algorithm design and analysis; Data mining; Electromyography; Inspection; Motion control; Motor drives; Muscles; Pathology; Signal design; Signal processing;
Journal_Title :
Engineering in Medicine and Biology Magazine, IEEE
