Myoelectric signal analysis using neural networks

1990 ◽  
Vol 9 (1) ◽  
pp. 61-64 ◽  
Author(s):  
M.F. Kelly ◽  
P.A. Parker ◽  
R.N. Scott
Keyword(s):  
Neural Networks ◽  
Signal Analysis ◽  
Myoelectric Signal

scholarly journals Decoding Arm Movements by Myoelectric Signal and Artificial Neural Networks

2013 ◽  
Vol 04 (01) ◽  
pp. 87-93 ◽  
Author(s):  
Alexandre Balbinot ◽  
Adalberto Schuck Júnior ◽  
Gabriela Winkler Favieiro
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Arm Movements ◽  
Myoelectric Signal ◽  
Artificial Neural

scholarly journals POLYCHRONOUS WAVEFRONT COMPUTATIONS

2009 ◽  
Vol 19 (05) ◽  
pp. 1733-1739 ◽  
Author(s):  
EUGENE M. IZHIKEVICH ◽  
FRANK C. HOPPENSTEADT
Keyword(s):  
Neural Networks ◽  
Signal Analysis ◽  
Brain Research ◽  
Neural Nets ◽  
Computational Framework ◽  
Logical Operations ◽  
Temporal Pattern Recognition ◽  
Temporal And Spatial ◽  
Artificial Neural ◽  
Biological Circuits

There is great interest in methods for computing that do not involve digital machines. Many computational paradigms were inspired by brain research, such as Boolean neuronal logic [McCulloch & Pitts, 1943], the perceptron [Rosenblatt, 1958], attractor neural networks [Hopfield, 1982] and cellular neural nets [Chua & Yang, 1988]. All these paradigms abstract biological circuits to artificial neural networks, i.e. interconnected units (neurons) that perform computations based on the connections between the units (synapses). Here we present a novel computational framework based on polychronous wavefront dynamics. It is entirely different from an artificial neural network paradigm, rather it is based on temporal and spatial patterns of activity in pulse-propagating media and their interaction with transponders, which create pulses in response to receiving appropriate inputs, e.g. two coincident input pulses. A pulse propagates as a circular wave from its source to other transponders. Computations result from interactions between transponders, and they are encoded by the exact physical locations of transponders and by precise timings of pulses. We illustrate temporal pattern recognition, reverberating memory, temporal signal analysis and basic logical operations using polychronous wavefront computations. This work reveals novel principles for designing nanoscale computational devices.

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