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The myoelectric signal can be used to control many rehabilitation systems, for instance, prostheses and artificial neuromuscular electrical stimulation toward restoring movement to spinal cord injured subjects. These mobile systems are usually used in different environments and thus are being exposed to different noise levels with characteristics not completely known. In this article, three main techniques for noise reduction were evaluated: wavelet transform (WT), adaptive digital filters, and nonadaptive digital filters. The WT was used to reconstruct the signal with the components without noise information. Adaptive filters were designed using least mean square (LMS) and recursive least square (RLS) algorithms. Finite-impulse response (FIR) and infinite-impulse response (IIR) nonadaptive filters were used for comparison to both the adaptive filters and the signal reconstruction through the WT.