Surface electromyography can quantify temporal and spatial patterns of activation of intrinsic human foot muscles. (April 2018)

• Record Type: Journal Article
• Authors: Ferrari, E.; Cooper, G.; Reeves, N.D.; Hodson-Tole, E.F.
• Is Part Of: Journal of electromyography and kinesiology. Volume 39(2018)
• Page Start: 149
• Page End: 155
• Publication Date: 2018-04
• Subjects: Surface EMG -- Intrinsic foot muscles -- Topographical mapping -- Sample entropy; Electromyography -- Periodicals; Kinesiology -- Periodicals; Electromyography -- Periodicals; Movement -- physiology -- Periodicals; Muscles -- physiology -- Periodicals; Électromyographie -- Périodiques; Cinésiologie -- Périodiques; Electromyography; Kinesiology; Electronic journals; Periodicals; 616.740757
• DOI: 10.1016/j.jelekin.2018.02.009
• Languages: English
• ISSNs: 1050-6411

Abstract

Abstract: Intrinsic foot muscles (IFM) are a crucial component within the human foot. Investigating their functioning can help understand healthy and pathological behaviour of foot and ankle, fundamental for everyday activities. Recording muscle activation from IFM has been attempted with invasive techniques, mainly investigating single muscles. Here we present a novel methodology, to investigate the feasibility of recording physiological surface EMG (sEMG) non-invasively and quantify patterns of activation across the whole plantar region of the foot. sEMG were recorded with a 13 × 5 array from the sole of the foot ( n = 25) during two-foot stance, two-foot tiptoe and anterior/posterior sways. Physiological features of sEMG were analysed. During anterior/posterior epochs within the sway task, sEMG patterns were analysed in terms of signal amplitude (intensity) and structure (Sample Entropy) distribution, by evaluating the centre of gravity (CoG) of each topographical map. Results suggest signals are physiological and not affected by loading. Both amplitude and sample entropy CoG coordinates were grouped in one region and overlapped, suggesting that the region with highest amplitude corresponds with the most predictable signal. Therefore, both spatial and temporal features of IFM activation may be recorded non-invasively, providing opportunity for more detailed investigation of IFM function in healthy and patient populations.