@article{MartinezValdesGuzmanVenegasSilvestreetal.2016,
  author    = {Martinez-Valdes, Eduardo Andr{\´e}s and Guzman-Venegas, R. A. and Silvestre, R. A. and Macdonald, J. H. and Falla, D. and Araneda, O. F. and Haichelis, D.},
  title     = {Electromyographic adjustments during continuous and intermittent incremental fatiguing cycling},
  series = {Psychotherapeut},
  volume    = {26},
  journal   = {Psychotherapeut},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0905-7188},
  doi       = {10.1111/sms.12578},
  pages     = {1273 -- 1282},
  year      = {2016},
  abstract  = {We studied the sensitivity of electromyographic (EMG) variables to load and muscle fatigue during continuous and intermittent incremental cycling. Fifteen men attended three laboratory sessions. Visit 1: lactate threshold, peak power output, and VO2max. Visits 2 and 3: Continuous (more fatiguing) and intermittent (less fatiguing) incremental cycling protocols [20\%, 40\%, 60\%, 80\% and 100\% of peak power output (PPO)]. During both protocols, multichannel EMG signals were recorded from vastus lateralis: muscle fiber conduction velocity (MFCV), instantaneous mean frequency (iMNF), and absolute and normalized root mean square (RMS) were analyzed. MFCV differed between protocols (P<0.001), and only increased consistently with power output during intermittent cycling. RMS parameters were similar between protocols, and increased linearly with power output. However, only normalized RMS was higher during the more fatiguing 100\% PPO stage of the continuous protocol [continuous-intermittent mean difference (95\% CI): 45.1 (8.5\% to 81.7\%)]. On the contrary, iMNF was insensitive to load changes and muscle fatigue (P=0.14). Despite similar power outputs, continuous and intermittent cycling influenced MFCV and normalized RMS differently. Only normalized RMS was sensitive to both increases in power output (in both protocols) and muscle fatigue, and thus is the most suitable EMG parameter to monitor changes in muscle activation during cycling.},
  language  = {en}
}
@article{MartinezValdesLaineFallaetal.2016,
  author    = {Martinez-Valdes, Eduardo Andr{\´e}s and Laine, C. M. and Falla, D. and Mayer, Frank and Farina, D.},
  title     = {High-density surface electromyography provides reliable estimates of motor unit behavior},
  series = {Clinical neurophysiology},
  volume    = {127},
  journal   = {Clinical neurophysiology},
  publisher = {Elsevier},
  address   = {Clare},
  issn      = {1388-2457},
  doi       = {10.1016/j.clinph.2015.10.065},
  pages     = {2534 -- 2541},
  year      = {2016},
  abstract  = {Objective: 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). Methods: 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. Results: 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 47.6 dB (accuracy > 95\%). Conclusion: Motor unit features can be assessed non-invasively and reliably within and across sessions over a wide range of force levels. Significance: These results suggest that it is possible to characterize motor units in longitudinal intervention studies. (C) 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.},
  language  = {en}
}