Surface electromyography signal processing and classification techniques.

Surface electromyography signal processing and classification techniques.
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DOI:
10.3390/s130912431
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发表时间:
2013-09-17
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
通讯作者:
Chang TG
Chang TG
中科院分区:
其他
文献类型:
--
作者:
Chowdhury RH;Reaz MB;Ali MA;Bakar AA;Chellappan K;Chang TG

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肌电(EMG)信号在许多应用中变得越来越重要,包括临床/生物医学、假肢或康复设备、人机交互等。然而,为了在上述应用中实现更好的性能,噪声EMG信号是需要克服的主要障碍。肌电(EMG)的检测、处理和分类分析是非常必要的,因为它可以对神经生理学、再居住和辅助技术结果进行更标准化和精确的评估。本文综述了两个突出的领域:一是在记录肌电信号时通过适当的准备来消除可能存在的伪影的预处理方法;二是对肌电信号的不同处理和分类方法的简要说明。然后,这项研究比较了多种分析肌电信号的方法,并比较了它们的性能。本文的重点是回顾与上述问题相关的最新发展和研究成果。
Electromyography (EMG) signals are becoming increasingly important in many applications, including clinical/biomedical, prosthesis or rehabilitation devices, human machine interactions, and more. However, noisy EMG signals are the major hurdles to be overcome in order to achieve improved performance in the above applications. Detection, processing and classification analysis in electromyography (EMG) is very desirable because it allows a more standardized and precise evaluation of the neurophysiological, rehabitational and assistive technological findings. This paper reviews two prominent areas; first: the pre-processing method for eliminating possible artifacts via appropriate preparation at the time of recording EMG signals, and second: a brief explanation of the different methods for processing and classifying EMG signals. This study then compares the numerous methods of analyzing EMG signals, in terms of their performance. The crux of this paper is to review the most recent developments and research studies related to the issues mentioned above.
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