TY - GEN
T1 - Reliability of a feedback-controlled treadmill algorithm dependent on the user's behavior
AU - Wiens, Casey
AU - Denton, William
AU - Schieber, Molly N.
AU - Hartley, Ryan
AU - Marmelat, Vivien
AU - Myers, Sara A.
AU - Yentes, Jennifer M.
N1 - Funding Information:
Funding was provided by University of Nebraska at Omaha Graduate Research and Creative Activity award and NASA Nebraska Space Grant. Additional funding provided by the National Institutes of Health (P20 GM109090, R01AG034995 and R01HD090333).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/9/27
Y1 - 2017/9/27
N2 - The 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.
AB - The 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.
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U2 - 10.1109/EIT.2017.8053423
DO - 10.1109/EIT.2017.8053423
M3 - Conference contribution
C2 - 29399378
AN - SCOPUS:85033697612
T3 - IEEE International Conference on Electro Information Technology
SP - 545
EP - 550
BT - 2017 IEEE International Conference on Electro Information Technology, EIT 2017
PB - IEEE Computer Society
T2 - 2017 IEEE International Conference on Electro Information Technology, EIT 2017
Y2 - 14 May 2017 through 17 May 2017
ER -