Journal of Electromyography and Kinesiology
Volume 21, Issue 1 , Pages 178-183, February 2011

Piper rhythm in the activation of the gastrocnemius medialis during running

  • Lisa M. Stirling

      Affiliations

    • Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Canada
    • Corresponding Author InformationCorresponding author. Address: Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4. Tel.: +1 403 220 2170; fax: +1 403 282 7637.
  • ,
  • Vinzenz von Tscharner

      Affiliations

    • Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Canada
  • ,
  • Patrick Kugler

      Affiliations

    • Pattern Recognition Laboratory, University of Erlangen-Nuremberg, Germany
  • ,
  • Benno M. Nigg

      Affiliations

    • Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Canada

Received 15 April 2010; received in revised form 28 June 2010; accepted 28 June 2010. published online 23 July 2010.

Abstract 

The presence of temporal rhythmicity in electromyographic (EMG) signals at frequencies of 35–60Hz was initially noted by Piper (1907). This modulation and synchronization of motor unit activity is generally accepted to represent a centrally generated coding of motor commands. The purpose of this study was to resolve and quantify the Piper rhythm in the gastrocnemius medialis (GM) muscle during running. EMG was recorded from the GM of 14 female runners during 1-h treadmill runs. The average wavelet transform was computed for EMG from series of steps taken at 2min intervals throughout the run. The total intensity across three wavelets (center frequencies: 170, 218 and 271Hz) was computed and a histogram indicating the incidence peaks in this signal was generated for each subject. In order to rule out effects of the analysis process, the process was repeated using simulated EMG data. Autocorrelations of the histograms were used to extract the frequency of the peaks resulting in rhythmicity at 25–55Hz. The ability to measure superimposed rhythmicity in EMG signals during dynamic tasks allows investigation of the role of aspects of central drive during movement. In particular, the changes in central control during dynamic activities can be examined with this approach.

Keywords: EMG, Running, Time–frequency analysis, Wavelet transform

 

PII: S1050-6411(10)00096-9

doi:10.1016/j.jelekin.2010.06.007

Journal of Electromyography and Kinesiology
Volume 21, Issue 1 , Pages 178-183, February 2011