Low-density, high surface area electromyography of the hamstring muscles during running and kicking. Issue 2 (20th January 2011)

• Record Type: Journal Article
• Authors: Sakthibalan, S; Twycross-Lewis, R; Woledge, R; Hao, Y; Morrissey, D
• Is Part Of: British journal of sports medicine. Volume 45:Issue 2(2011)
• Page Start: e1
• Page End: e1
• Publication Date: 2011-01-20
• Subjects: Sports medicine -- Periodicals; 617.1027
• DOI: 10.1136/bjsm.2010.081554.18
• Languages: English
• ISSNs: 0306-3674

Abstract

Abstract : Background: Surface electromyography (sEMG) is used extensively in the assessment of hamstring muscle activity. Conventional sEMG techniques may not fully represent overall muscle activity, despite clinically standardised placement of electrodes. High density EMG provides more information about biopotential activity but it is limited to signal collection over a small surface area. Our work proposes a low density high surface area EMG method to analyse muscle biopotentials over an entire muscle belly. Objectives: To assess whether there is a pattern of EMG output over an entire muscle during running and repeated kicking. Method: 16 channel EMG and motion analysis data were collected for 10 healthy volunteers during treadmill running at 10 km/h, and kicking a football. Active infra-red motion analysis instrumentation was used to register limb segment movement with the raw time series EMG signals. Each EMG channel was subjected to Windowed Fourier Transform for construction of a false colour map for the hamstring. Each EMG and motion analysis channel were analysed by ANCOVA. Results: Visual analysis showed that different areas of the hamstring muscles are active at different points in the running cycle independently of each other. Quantitative analysis within a single subject showed main effects for electrode position and stride point (p<0.001) during running. A significant interaction between stride point and electrode position was noted. Conclusion: Results suggest the presence of an EMG activity pattern showing consistent variation within stride-point and channel location during running. A larger subject group is needed to further investigate EMG patterns in kicking. The scope for further research using the results of this paper as a foundation is vast, with the future inclusion of wireless EMG, electrode arrays and custom garments. The findings may lead to an application in a screening, rehabilitation and diagnosis setting.