Wavelet and short-time Fourier transform comparison-based analysis of myoelectric signals

Karan Veer and Ravinder Agarwal

Journal of Applied Statistics, 2015, vol. 42, issue 7, 1591-1601

Abstract: In this investigation, extracted features ofsignals have been analyzed for the recognition of arm movements. Short-time Fourier transform and wavelet transform based on Euclidian distance were applied to reordered signals. Results show that wavelet is a more useful and powerful tool for analyzing signals, since it shows multiresolution property with a significant reduction in the computation time for eliminating resolution problems. Finally, a statistical technique of repeated factorial analysis of variance for experimental recorded data was implemented in a way to investigate the effect of class separability for multiple motions for establishing surface electromyogram-muscular force relationship.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:taf:japsta:v:42:y:2015:i:7:p:1591-1601

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DOI: 10.1080/02664763.2014.1001728

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