title: Quadriceps mechano- and electromyographic time-frequency responses during muscular contractions to volitional exhaustion.
abstract: BACKGROUND
  Surface electromyography (SEMG) and mechanomyography (SMMG) responses of the quadriceps during muscular contractions to exhaustion were computed and analyzed by analysis of variance and polynomial regression analyses.
  
  
  METHODS
  Participants performed maximum flexion-extension movements at 180°/s until volitional exhaustion, rested for 2 minutes, and then completed a second bout of movements until exhaustion. Torque and SEMG/SMMG median frequencies and amplitudes were examined at 9 points across repetitions completed.
  
  
  RESULTS
  (1) Torque decreased precipitously; (2) SEMG amplitude displayed an initial increase, then a steady decrease, and SMMG amplitude showed a continuous decrease; and (3) SEMG and SMMG median frequencies displayed a continual decrease over repetitions completed. Fractional polynomial and quadratic models explained the fatigue process with the highest precision.
  
  
  CONCLUSIONS
  Changes in electrical and mechanical properties of the quadriceps during fatigue reflect alterations in neuromuscular activation strategies and/or muscle wisdom. SEMG frequency modeled muscle fatigue more effectively than amplitude, whereas SMMG frequency and amplitude were equally effective.
authors.affiliation: Motor Control and Biomechanics Laboratory, Department of Kinesiology, University of New Hampshire, Durham, New Hampshire, 03824, USA.
authors.forename: Ronald
authors.initials: R
authors.lastname: Croce
authors.affiliation: Motor Control and Biomechanics Laboratory, Department of Kinesiology, University of New Hampshire, Durham, New Hampshire, 03824, USA.
authors.forename: Amber
authors.initials: A
authors.lastname: Craft
authors.affiliation: Motor Control and Biomechanics Laboratory, Department of Kinesiology, University of New Hampshire, Durham, New Hampshire, 03824, USA.
authors.forename: John
authors.initials: J
authors.lastname: Miller
authors.affiliation: Department of Electrical and Computer Engineering, University of New Hampshire, Durham, New Hampshire, USA.
authors.forename: Kent
authors.initials: K
authors.lastname: Chamberlin
authors.affiliation: Department of Electrical and Computer Engineering, University of New Hampshire, Durham, New Hampshire, USA.
authors.forename: David
authors.initials: D
authors.lastname: Filipovic
mesh_terms: D061725:Accelerometry; D000704:Analysis of Variance; D004558:Electric Stimulation; D004576:Electromyography; D019054:Evoked Potentials, Motor / Q000502:physiology*; D015444:Exercise / Q000502:physiology*; D005583:Fourier Analysis; D006801:Humans; D008297:Male; D009119:Muscle Contraction / Q000502:physiology*; D053581:Muscle Strength Dynamometer; D018482:Muscle, Skeletal / Q000502:physiology*; D010812:Physical Stimulation; D012044:Regression Analysis; D013997:Time Factors; D019415:Torque; D055815:Young Adult
keywords: electromyography; fatigue; isokinetics; mechanomyography; wavelet transform