Evaluation of adaptive/nonadaptive filtering and wavelet transform techniques for noise reduction in EMG mobile acquisition equipment.
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.
Ortolan
Rodrigo Lício
RL
Biocybernetics & Rehabilitation Engineering Laboratory (LABCIBER), Electrical Engineering Department, São Carlos Engineering School, University of São Paulo, São Paulo, SP 13566-590, Brazil. ortolan@sel.eesc.sc.usp.br
Mori
Ricardo Naoki
RN
Pereira
Roberto R Júnior
RR
Cabral
Cristina M N
CM
Pereira
José Carlos
JC
Cliquet
Alberto Júnior
AJ
D000465:Algorithms; D016477:Artifacts; D004576:Electromyography / Q000379:methods*; D005246:Feedback; D006801:Humans; D018670:Monitoring, Ambulatory / Q000379:methods*; D009068:Movement; D018482:Muscle, Skeletal / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes; D014955:Wrist Joint / Q000502:physiology