Abstract
The current study examined stiffness in the tibialis anterior muscle during the swing phase of walking while wearing various footwear. Seven healthy young men participated in this study. Participants were instructed to walk on a treadmill at 3 km/h while wearing sports shoes, slippers, or slippers with belts. The common peroneal nerve was electrically stimulated every two steps at toe-off during walking. Mechanomyograms (MMGs), electromyograms, and ankle angle were measured. Evoked MMG was extracted using a Kalman filter and subtraction of walking acceleration. The transfer function from the electrical stimulation to the evoked MMG was identified using a singular value decomposition method, and the natural frequency of the transfer function was calculated as an index of muscle stiffness. The natural frequency did not show a clear relationship with footwear type. Four participants showed the lowest natural frequency when they wore slippers with belts. The remaining subjects showed the lowest natural frequency when they wore slippers or shoes. These contrasting findings may have been caused by different degrees of adaptation of participants to the footwear.
Original language | English |
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Title of host publication | 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
Subtitle of host publication | Smarter Technology for a Healthier World, EMBC 2017 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 4131-4134 |
Number of pages | 4 |
ISBN (Electronic) | 9781509028092 |
DOIs | |
Publication status | Published - 2017 Sep 13 |
Event | 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of Duration: 2017 Jul 11 → 2017 Jul 15 |
Other
Other | 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 |
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Country | Korea, Republic of |
City | Jeju Island |
Period | 17/7/11 → 17/7/15 |
ASJC Scopus subject areas
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics