Journal
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
Volume 59, Issue 1, Pages 219-225Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TBME.2011.2170687
Keywords
Cyclic movements; signal-to-noise ratio (SNR); surface electromyography (sEMG); surface myoelectric signal (SMES)
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In many applications requiring the study of the surface myoelectric signal (SMES) acquired in dynamic conditions, it is essential to have a quantitative evaluation of the quality of the collected signals. When the activation pattern of a muscle has to be obtained by means of single-or double-threshold statistical detectors, the background noise level e(noise) of the signal is a necessary input parameter. Moreover, the detection strategy of double-threshold detectors may be properly tuned when the SNR and the duty cycle (DC) of the signal are known. The aim of this paper is to present an algorithm for the estimation of e(noise), SNR, and DC of an SMES collected during cyclic movements. The algorithm is validated on synthetic signals with statistical properties similar to those of SMES, as well as on more than 100 real signals.
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