title: Tracking motor units longitudinally across experimental sessions with high-density surface electromyography.
abstract: Classic motor unit (MU) recording and analysis methods do not allow the same MUs to be tracked across different experimental sessions, and therefore, there is limited experimental evidence on the adjustments in MU properties following training or during the progression of neuromuscular disorders. We propose a new processing method to track the same MUs across experimental sessions (separated by weeks) by using high-density surface electromyography. The application of the proposed method in two experiments showed that individual MUs can be identified reliably in measurements separated by weeks and that changes in properties of the tracked MUs across experimental sessions can be identified with high sensitivity. These results indicate that the behaviour and properties of the same MUs can be monitored across multiple testing sessions. The proposed method opens new possibilities in the understanding of adjustments in motor unit properties due to training interventions or the progression of pathologies.
  
  
  
  A new method is proposed for tracking individual motor units (MUs) across multiple experimental sessions on different days. The technique is based on a novel decomposition approach for high-density surface electromyography and was tested with two experimental studies for reliability and sensitivity. Experiment I (reliability): ten participants performed isometric knee extensions at 10, 30, 50 and 70% of their maximum voluntary contraction (MVC) force in three sessions, each separated by 1 week. Experiment II (sensitivity): seven participants performed 2 weeks of endurance training (cycling) and were tested pre-post intervention during isometric knee extensions at 10 and 30% MVC. The reliability (Experiment I) and sensitivity (Experiment II) of the measured MU properties were compared for the MUs tracked across sessions, with respect to all MUs identified in each session. In Experiment I, on average 38.3% and 40.1% of the identified MUs could be tracked across two sessions (1 and 2 weeks apart), for the vastus medialis and vastus lateralis, respectively. Moreover, the properties of the tracked MUs were more reliable across sessions than those of the full set of identified MUs (intra-class correlation coefficients ranged between 0.63-0.99 and 0.39-0.95, respectively). In Experiment II, ∼40% of the MUs could be tracked before and after the training intervention and training-induced changes in MU conduction velocity had an effect size of 2.1 (tracked MUs) and 1.5 (group of all identified motor units). These results show the possibility of monitoring MU properties longitudinally to document the effect of interventions or the progression of neuromuscular disorders.
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: Institute of Neurorehabilitation Systems, Bernstein Focus Neurotechnology Göttingen (BFNT), Bernstein Centre for Computational Neuroscience (BCCN), University Medical Center Göttingen, Georg-August University, Göttingen, Germany.|Department of Clinical and Experimental Sciences, Università degli Studi di Brescia, Brescia, Italy.
authors.forename: F
authors.initials: F
authors.lastname: Negro
authors.affiliation: Institute of Neurorehabilitation Systems, 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: Centre of Precision Rehabilitation for Spinal Pain (CPR Spine), School of Sport, Exercise and Rehabilitation Sciences, College of Life and Environmental Sciences, University of Birmingham, Birmingham, UK.
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: Institute of Neurorehabilitation Systems, Bernstein Focus Neurotechnology Göttingen (BFNT), Bernstein Centre for Computational Neuroscience (BCCN), University Medical Center Göttingen, Georg-August University, Göttingen, Germany.|Department of Bioengineering, Imperial College London, Royal School of Mines, London, UK.
authors.forename: D
authors.identifier: 0000-0002-7883-2697
authors.initials: D
authors.lastname: Farina
mesh_terms: D000200:Action Potentials; D000328:Adult; D004576:Electromyography; D015444:Exercise / Q000502:physiology*; D006801:Humans; D007537:Isometric Contraction; D007717:Knee / Q000502:physiology; D008297:Male; D009046:Motor Neurons / Q000502:physiology*; D010807:Physical Endurance / Q000502:physiology; D052097:Quadriceps Muscle / Q000502:physiology; D055815:Young Adult