A force myography-based system for gait event detection in overground and ramp walking

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dc.contributor.author Godiyal, Anoop Kant
dc.contributor.author Verma, Hemant Kumar
dc.contributor.author Khanna, Nitin
dc.contributor.author Joshi, Deepak
dc.date.accessioned 2018-04-27T06:13:14Z
dc.date.available 2018-04-27T06:13:14Z
dc.date.issued 2018-04
dc.identifier.citation Godiyal, Anoop Kant; Verma, Hemant Kumar; Khanna, Nitin and Joshi, Deepak, "A force myography-based system for gait event detection in overground and ramp walking", IEEE Transactions on Instrumentation and Measurement, DOI: 10.1109/TIM.2018.2816799, Apr. 2018. en_US
dc.identifier.issn 0018-9456
dc.identifier.uri http://dx.doi.org/10.1109/TIM.2018.2816799
dc.identifier.uri https://repository.iitgn.ac.in/handle/123456789/3630
dc.description.abstract In this paper, we present a novel method to determine the heel strike (HS) and toe-off (TO) during overground (OG) and ramp walking, including the transition. The method utilizes force myography (FMG) signals from thighs while subjects walked on OG and ramp. Five adult male subjects wore a wireless FMG data acquisition system, developed in-house using force resistive sensors and electronic components. A heuristic approach for subject-dependent and terrain-independent model was developed to determine HS and TO in a given gait cycle in steady state and transition. The average error in HS determination was 9.66 ± 8.29, 9.38 ± 9.35, and 13.94 ± 18.95 ms, while TO was determined with an average error of 16.99 ± 18.12, 13.35 ± 15.10, and 17.29 ± 21.92 ms for OG, ramp, and transition, respectively. The proposed system is less expensive, simple to develop, and friendly to wear. The reported errors are comparable to previously reported errors using pressure sensitive insole, gyroscope, accelerometers, and electromyography, which are much complex and expensive in comparison to proposed FMG-based system. Although the tests were conducted on healthy subjects, the system promises to be generalizable to amputee and other pathological gaits also. While the tests were conducted on young adults at self-selected speeds, the system also promises to be generalizable for a wide range of walking speeds across the population.
dc.description.statementofresponsibility by Anoop Kant Godiyal, Hemant Kumar Verma, Nitin Khanna and Deepak Joshi
dc.language.iso en en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.subject Sensors en_US
dc.subject Force en_US
dc.subject Legged en_US
dc.subject locomotion en_US
dc.subject Muscles en_US
dc.subject Eventdetection en_US
dc.subject Databases en_US
dc.subject Electromyography en_US
dc.subject Force myography (FMG) en_US
dc.subject gait cycle en_US
dc.subject heel strike (HS) en_US
dc.subject locomotion en_US
dc.subject toe-off (TO) en_US
dc.subject transitions en_US
dc.title A force myography-based system for gait event detection in overground and ramp walking en_US
dc.type Article en_US
dc.relation.journal IEEE Transactions on Instrumentation and Measurement

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