Karan Veer

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Here, the wavelet analysis has been investigated to improve the quality of myoelectric signal before use in prosthetic design. Effective Surface Electromyogram (SEMG) signals were estimated by first decomposing the obtained signal using wavelet transform and then analysing the decomposed coefficients by threshold methods. With the appropriate choice of(More)
Surface electromyogram (SEMG) is a complex signal and is influenced by several external factors/artifacts. The electromyogram signal from the stump of the subject is picked up through surface electrodes. It is amplified and artifacts are removed before digitising it in a controlled manner so that minimum signal loss occurs due to processing. As removing(More)
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