title: Time-frequency parameters of the surface myoelectric signal for assessing muscle fatigue during cyclic dynamic contractions.
abstract: The time-dependent shift in the spectral content of the surface myoelectric signal to lower frequencies has proven to be a useful tool for assessing localized muscle fatigue. Unfortunately, the technique has been restricted to constant-force, isometric contractions because of limitations in the processing methods used to obtain spectral estimates. A novel approach is proposed for calculating spectral parameters from the surface myoelectric signal during cyclic dynamic contractions. The procedure was developed using Cohen class time-frequency transforms to define the instantaneous median and mean frequency during cyclic dynamic contractions. Changes in muscle length, force, and electrode position contribute to the nonstationarity of the surface myoelectric signal. These factors, unrelated to localized fatigue, can be constrained and isolated for cyclic dynamic contractions, where they are assumed to be constant for identical phases of each cycle. Estimation errors for the instantaneous median and mean frequency are calculated from synthesized signals. It is shown that the instantaneous median frequency is affected by an error slightly lower than that related to the instantaneous mean frequency. In addition, we present a sample application to surface myoelectric signals recorded from the first dorsal interosseous muscle during repetitive abduction/adduction of the index finger against resistance. Results indicate that the variability of the instantaneous median frequency is related to the repeatability of the biomechanics of the exercise.
authors.affiliation: NeuroMuscular Research Center, Boston University, MA 02215, USA. pbonato@bu.edu
authors.forename: P
authors.initials: P
authors.lastname: Bonato
authors.forename: S H
authors.initials: SH
authors.lastname: Roy
authors.forename: M
authors.initials: M
authors.lastname: Knaflitz
authors.forename: C J
authors.initials: CJ
authors.lastname: De Luca
mesh_terms: D004576:Electromyography; D015444:Exercise / Q000502:physiology; D005384:Finger Joint / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D009119:Muscle Contraction / Q000502:physiology*; D016059:Range of Motion, Articular / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D016474:Weight-Bearing