Less is more: high pass filtering, to remove up to 99% of the surface EMG signal power, improves EMG-based biceps brachii muscle force estimates.
It is generally assumed that raw surface EMG (sEMG) should be high pass filtered with cutoffs of 10-30 Hz to remove motion artifact before subsequent processing to estimate muscle force. The purpose of the current study was to explore the benefits of filtering out much of the raw sEMG signal when attempting to estimate accurate muscle forces. Twenty-five subjects were studied as they performed rapid static, anisotonic contractions of the biceps brachii. Biceps force was estimated (as a percentage of maximum) based on forces recorded at the wrist. An iterative approach was used to process the sEMG from the biceps brachii, using progressively greater high pass cutoff frequencies (20-440 Hz in steps of 30 Hz) with first and sixth order filters, as well as signal whitening, to determine the effects on the accuracy of EMG-based biceps force estimates. The results indicate that removing up to 99% of the raw sEMG signal power resulted in significant and substantial improvements in biceps force estimates. These findings challenge previous assumptions that the raw sEMG signal power between about 20 and 500 Hz should used when estimating muscle force. For the purposes of force prediction, it appears that a much smaller, high band of sEMG frequencies may be associated with force and the remainder of the spectrum has little relevance for force estimation.
Potvin
J R
JR
Department of Kinesiology, University of Windsor, Windsor, Ont., Canada N9B 3P4. jpotvin@uwindsor.ca
Brown
S H M
SH
D000328:Adult; D000465:Algorithms; D001132:Arm / Q000502:physiology; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004576:Electromyography / Q000379:methods*; D005260:Female; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology*; D008297:Male; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000502:physiology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted