Resolving superimposed MUAPs using particle swarm optimization.
Resolving superimposed MUAPs using particle swarm optimization.
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DOI：
10.1109/tbme.2008.2005953
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发表时间：
2009-03
期刊：
影响因子：
--
通讯作者：
McGill KC
中科院分区：
文献类型：
--
作者：
Marateb HR;McGill KC
This paper presents an algorithm to resolve superimposed action potentials encountered during the decomposition of electromyographic signals. The algorithm uses particle swarm optimization with a variety of features including randomization, cross-over, and multiple swarms. In a simulation study involving realistic superpositions of 2-5 motor-unit action potentials, the algorithm had an accuracy of 98%.
