DocumentCode :
1215107
Title :
Comments on "Upper Extremity Limb Function Discrimination Using EMG Signal Analysis" and the Relationship Between Parallel-Fltering and Hypothesis-Testing Limb Function Classifiers
Author :
Triolo, R.J. ; Moskowitz, G.D.
Author_Institution :
Departments of Biomedical Engineering and Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA, and the Veterans Administration Medical Center
Issue :
3
fYear :
1985
fDate :
3/1/1985 12:00:00 AM
Firstpage :
239
Lastpage :
241
Abstract :
A continuity which is not readily apparent exists between certain limb function classification algorithms based on time series models of the surface EMG for use in the control of prostheses and orthoses. Superficially, the parallel-filtering system proposed by Graupe et al. [1], [2] appears to be arbitrary, inconsistent, and ad hoc in nature, and has been criticized as such [3] . Doerschuk et al. independentty developed a multichannel decision algorithm for limb function descrinination within the framework of classical detection theory using multiple-hypothesis testing [3]. This conimtihication establishes the fundamental equivalence of the two algorithms by showing that the system advocated by Graupe is in actuality a degenerate form of that proposed by Doerschuk when conditions of equal residual variance and a priori probabilities are met. A theoretical basis for Graupe´s system is presented and its relationship to the multiple hypothesis test of Doerschuk is derived which unifies the contributions of both groups.
Keywords :
Channel bank filters; Classification algorithms; Electromyography; Extremities; Orthotics; Prosthetics; Signal analysis; Signal resolution; System testing; Arm; Artificial Limbs; Electromyography; Filtration; Humans; Mathematics; Models, Biological; Orthotic Devices; Time Factors;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.1985.325534
Filename :
4122031
Link To Document :
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