title: High-density surface electromyography provides reliable estimates of motor unit behavior.
abstract: To assess the intra- and inter-session reliability of estimates of motor unit behavior and muscle fiber properties derived from high-density surface electromyography (HDEMG).
  
  
  
  Ten healthy subjects performed submaximal isometric knee extensions during three recording sessions (separate days) at 10%, 30%, 50% and 70% of their maximum voluntary effort. The discharge timings of motor units of the vastus lateralis and medialis muscles were automatically identified from HDEMG by a decomposition algorithm. We characterized the number of detected motor units, their discharge rates, the coefficient of variation of their inter-spike intervals (CoVisi), the action potential conduction velocity and peak-to-peak amplitude. Reliability was assessed for each motor unit characteristics by intra-class correlation coefficient (ICC). Additionally, a pulse-to-noise ratio (PNR) was calculated, to verify the accuracy of the decomposition.
  
  
  
  Good to excellent reliability within and between sessions was found for all motor unit characteristics at all force levels (ICCs>0.8), with the exception of CoVisi that presented poor reliability (ICC<0.6). PNR was high and similar for both muscles with values ranging between 45.1 and 47.6dB (accuracy>95%).
  
  
  
  Motor unit features can be assessed non-invasively and reliably within and across sessions over a wide range of force levels.
  
  
  
  These results suggest that it is possible to characterize motor units in longitudinal intervention studies.
authors.affiliation: Department of Sports Medicine and Sports Orthopaedics, University of Potsdam, Potsdam, Germany.
authors.forename: E
authors.initials: E
authors.lastname: Martinez-Valdes
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen (BFNT), Bernstein Centre for Computational Neuroscience (BCCN), University Medical Center Göttingen, Georg-August University, Göttingen, Germany.
authors.forename: C M
authors.initials: CM
authors.lastname: Laine
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen (BFNT), Bernstein Centre for Computational Neuroscience (BCCN), University Medical Center Göttingen, Georg-August University, Göttingen, Germany; Pain Clinic, Center for Anesthesiology, Emergency and Intensive Care Medicine, University Hospital Göttingen, Göttingen, Germany.
authors.forename: D
authors.initials: D
authors.lastname: Falla
authors.affiliation: Department of Sports Medicine and Sports Orthopaedics, University of Potsdam, Potsdam, Germany.
authors.forename: F
authors.initials: F
authors.lastname: Mayer
authors.affiliation: Department of Neurorehabilitation Engineering, Bernstein Focus Neurotechnology Göttingen (BFNT), Bernstein Centre for Computational Neuroscience (BCCN), University Medical Center Göttingen, Georg-August University, Göttingen, Germany. Electronic address: Dario.farina@bccn.uni-goettingen.de.
authors.forename: D
authors.initials: D
authors.lastname: Farina
mesh_terms: D000328:Adult; D004576:Electromyography / Q000379:methods* / Q000592:standards; D019054:Evoked Potentials, Motor; D006801:Humans; D007717:Knee / Q000294:innervation / Q000502:physiology; D008297:Male; D052097:Quadriceps Muscle / Q000294:innervation / Q000502:physiology*; D059629:Signal-To-Noise Ratio
keywords: Conduction velocity; High-density surface EMG; Motor unit decomposition; Motor unit discharge rate; Vastus lateralis; Vastus medialis