• N J Cronin, S Kumpulainen, T Joutjärvi, T Finni, and H Piitulainen.
• Neuromuscular Research Centre, Department of Biology of Physical Activity, University of Jyväskylä, P.O. Box 35, 40014 Jyväskylä, Finland. Electronic address: neil.j.cronin@jyu.fi.
• Neuroscience. 2015 Aug 6;300:19-28.

AbstractHuman leg muscles are often activated inhomogeneously, e.g. in standing. This may also occur in complex tasks like walking. Thus, bipolar surface electromyography (sEMG) may not accurately represent whole muscle activity. This study used 64-electrode high-density sEMG (HD-sEMG) to examine spatial variability of lateral gastrocnemius (LG) muscle activity during the stance phase of walking, maximal voluntary contractions (MVCs) and maximal M-waves, and determined the effects of different normalization approaches on spatial and inter-participant variability. Plantar flexion MVC, maximal electrically elicited M-waves and walking at self-selected speed were recorded in eight healthy males aged 24-34. sEMG signals were assessed in four ways: unnormalized, and normalized to MVC, M-wave or peak sEMG during the stance phase of walking. During walking, LG activity varied spatially, and was largest in the distal and lateral regions. Spatial variability fluctuated throughout the stance phase. Normalizing walking EMG signals to the peak value during stance reduced spatial variability within LG on average by 70%, and inter-participant variability by 67%. Normalizing to MVC reduced spatial variability by 17% but increased inter-participant variability by 230%. Normalizing to M-wave produced the greatest spatial variability (45% greater than unnormalized EMG) and increased inter-participant variability by 70%. Unnormalized bipolar LG sEMG may provide misleading results about representative muscle activity in walking due to spatial variability. For the peak value and MVC approaches, different electrode locations likely have minor effects on normalized results, whereas electrode location should be carefully considered when normalizing walking sEMG data to maximal M-waves.Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.

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