Title :
A Signal-to-Noise Investigation of Nonlinear Electromyographic Processors
Author :
Kreifeldt, John G. ; Yao, Sumner
Author_Institution :
Department of Engineering Design, Tufts University, Medford, Mass. 02155.
fDate :
7/1/1974 12:00:00 AM
Abstract :
A general class of nonlinear electromyographic (EMG) processors has been evaluated for their signal-to-noise ratio (SNR) properties. These filters incorporate as the detector element either a power-law (xn) or root-law (x1/n) transformation (detector) followed by a linear low-pass smoothing filter. ``Linearized´´ versions of these processors in which the smoothing filter is followed by an element with the inverse detector characteristics were also evaluated.
Keywords :
Detectors; Electromyography; Engineering in medicine and biology; Feedback; Muscles; Noise level; Nonlinear filters; Open loop systems; Signal processing; Smoothing methods; Computers; Electromyography; Electronics, Medical; Humans; Mathematics; Models, Biological; Muscle Contraction; Noise;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.1974.324317
