DocumentCode :
2620096
Title :
A neural network for noninvasive decomposition of surface EMG signals using Gaussian nodes
Author :
Liu, Ruey-wen ; Huang, Qiu ; Graupe, Daniel
Author_Institution :
Notre Dame Univ., IN, USA
fYear :
1990
fDate :
1-3 May 1990
Firstpage :
2053
Abstract :
The decomposition of surface EMG (electromyograms) signals into their constituent single fiber action potentials (SFAPs) is addressed. Generally, this problem is analytically not tractable and is computationally too complex to be reliable. It is demonstrated that it can be resolved by a specially designed neural network called the neural network with Gaussian nodes. Together with a modified back-propagation algorithm, a method of choosing initial conditions is presented. The significance of such solutions is that they allow a physician or medical researcher to observe the time behavior of SFAPs in a noninvasive manner for diagnostic purposes or other medical applications
Keywords :
bioelectric potentials; computerised signal processing; muscle; neural nets; patient diagnosis; Gaussian nodes; SFAP; back-propagation algorithm; diagnosis; electromyograms; medical signal processing; neural network; noninvasive decomposition; physiology; simulation; single fiber action potentials; surface EMG signal decomposition; time behavior; Backpropagation algorithms; Electrodes; Electromyography; Intelligent networks; Medical diagnostic imaging; Muscles; Neural networks; Robustness; Surface reconstruction; Telecommunication network reliability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
Type :
conf
DOI :
10.1109/ISCAS.1990.112158
Filename :
112158
Link To Document :
بازگشت