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Myers -

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he reliability of the treadmill belt speed using a feedback-controlled treadmill algorithm was analyzed in this study. Using biomechanical factors of the participant's walking behavior, an estimated walking speed was calculated and used to adjust the speed of the treadmill. Our proposed algorithm expands on the current hypotheses of feedback-controlled treadmill algorithms and is presented below. Nine healthy, young adults walked on a treadmill controlled by the algorithm for three trials over two days. Each participant walked on the feedback-controlled treadmill for one 16-minute and one five-minute trial during day one and one 16-minute trial during day two. Mean, standard deviation, interclass correlation coefficient (ICC), and standard error of measurement (SEM) were analyzed on the treadmill belt speed mean, standard deviation, and coefficient of variation. There were significantly high ICC for mean treadmill speed within- and between-days. Treadmill speed standard deviation and coefficient of variation were significantly reliable within-day. These results suggest the algorithm will reliably produce the same treadmill belt speed mean, but may only produce a similar treadmill belt speed standard deviation and coefficient of variation if the trials are performed in the same day. A feedback-controlled treadmill algorithm that accounts for the user's behavior provides a greater level of control and minimizes any possible constraints of walking on a conventional treadmill.


C. Wiens et al., "Reliability of a feedback-controlled treadmill algorithm dependent on the user's behavior," 2017 IEEE International Conference on Electro Information Technology (EIT), Lincoln, NE, USA, 2017, pp. 545-550, doi: 10.1109/EIT.2017.8053423.

IEEE International Conference on Eletro Information Technology

The Conference Data was May 14-17, 2017

PubMed ID 29399378 INSPEC Accession Number 17214838 DOI 10.1109/EIT.2017.8053423

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IEEE Xplore: IEEE International Conference on Eletro Information Technology





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Biomechanics Commons