title: Cross-comparison of time- and frequency-domain methods for monitoring the myoelectric signal during a cyclic, force-varying, fatiguing hand-grip task.
abstract: Various conventional methods to estimate the mean and median power spectral frequencies, and amplitude of the surface electromyogram during 30-90 min, cyclic, force-varying, constant-posture contractions were cross-compared in an experimental trial. The aim was to determine the most appropriate algorithm implementations and reduce the total number of algorithms that need to be considered when monitoring time trends. Subjects produced hand-grip contractions in a repeated intermittent pattern until exhaustion. For all estimated parameters: analysis of contraction levels below 25% maximum voluntary contraction produced poor estimates due to high relative measurement noise; parameter reproducibility was best when comparisons were aligned to the actual force produced rather than the target force and when the biomechanics of the contraction were more consistent; and estimates were not greatly influenced by the rate of change of the force trajectory. For frequency parameters: estimates based on the short-time Fourier transform were similar to those based on time-varying autoregressive methods; longer duration analysis windows exhibited better repeatability; and simple frequency-domain noise filters were not effective in reducing the impact of measurement noise. For amplitude estimates: whitening reduced the variance of the amplitude estimate; and the best analysis window duration was a trade-off between bias (decreased with a short duration window) and variance (decreased with a long duration window).
authors.affiliation: Department of Electrical and Computer Engineering, Worcester Polytechnic Institute, 100 Institute Road, Worcester, MA 10609, USA. ted.clancy@alum.wpi.edu
authors.forename: Edward A
authors.initials: EA
authors.lastname: Clancy
authors.forename: Dario
authors.initials: D
authors.lastname: Farina
authors.forename: Roberto
authors.initials: R
authors.lastname: Merletti
mesh_terms: D000328:Adult; D000465:Algorithms; D016477:Artifacts; D001696:Biomechanical Phenomena; D004576:Electromyography / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D018737:Hand Strength / Q000502:physiology*; D006801:Humans; D008297:Male; D009119:Muscle Contraction / Q000502:physiology*; D018763:Muscle Fatigue / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*; D010807:Physical Endurance / Q000502:physiology; D015203:Reproducibility of Results; D013997:Time Factors