一个数据依赖的计算机算法检测肌肉活动的开始和偏移从肌电图记录

Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control Pub Date : 1998-04-01 DOI:10.1016/S0924-980X(97)00066-0

J.K. Leader III , J.R. Boston , C.A. Moore

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引用次数: 14

摘要

本文描述了对marpe - horvat和Gilbey(1992)提出的一种算法的修改，该算法用于识别肌电图(EMG)记录中的肌肉活动爆发。我们试图将他们的算法应用到自发移动的婴幼儿身上，结果收效甚微。改进后的算法使几个参数依赖于被分析的数据;这些变化使它能够更有效地分析各种肌电图记录。当应用于独立的测试数据集时，原始算法的成功率(正确识别的突发)为62.9%，组合错误率(插入和删除的数量)为73.0%。改进算法的准确率为85.4%，综合错误率为23.6%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A data dependent computer algorithm for the detection of muscle activity onset and offset from EMG recordings

This paper describes modifications to an algorithm presented by Marple-Horvat and Gilbey (1992)for identifying bursts of muscle activity in electromyographical (EMG) recordings. Our efforts to apply their algorithm to spontaneously moving infants and toddlers resulted in limited success. The modified algorithm makes several parameters dependent on the data being analyzed; these changes enabled it to analyze a variety of EMG recordings more effectively. The original algorithm had a success rate (correctly identified bursts) of 62.9% and combined error rate (number of insertions and deletions) of 73.0% when applied to an independent test data set. The modified algorithm displayed a success rate of 85.4% and combined error rate of 23.6%.

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Electroencephalography and Clinical Neurophysiology/Electromyography and Motor Control

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