TY - JOUR
T1 - Feasibility of Incorporating Test-Retest Reliability and Model Diversity in Identification of Key Neuromuscular Pathways during Head Position Tracking
AU - Ramadan, Ahmed
AU - Choi, Jongeun
AU - Cholewicki, Jacek
AU - Reeves, N. Peter
AU - Popovich, John M.
AU - Radcliffe, Clark J.
N1 - Publisher Copyright:
IEEE
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019
Y1 - 2019
N2 - To study complex neuromuscular control pathways in human movement, biomechanical parametric models and system identification methods are employed. Although test-retest reliability is widely used to validate outcomes of motor control tasks, it was not incorporated in system identification methods. This study investigates the feasibility of incorporating test-retest reliability in our previously published method of selecting sensitive parameters. We consider the selected parameters via this novel approach to be the key neuromuscular parameters because they meet three criteria: reduced variability, improved goodness of fit, and excellent reliability. These criteria ensure that parameter variability is below a user-defined value, the number of these parameters is maximized to enhance goodness of fit, and their test-retest reliability is above a user-defined value. We measured variability, goodness of fit, and reliability using Fisher information matrix, variance accounted for, and intraclass correlation, respectively. We also incorporated model diversity as a fourth optional criterion to narrow down the solution space of key parameters. We applied this approach to head position tracking in axial rotation and flexion/extension. Forty healthy subjects performed the tasks during two visits. With variability and reliability measures ≤0.35 and ≥0.75 respectively, we selected three key parameters out of twelve with goodness of fit >69%. The key parameters were associated with at least two neuromuscular pathways out of four modeled pathways (visual, proprioceptive, vestibular, and intrinsic), which is a measure of model diversity. Therefore, it is feasible to incorporate reliability and diversity in system identification of key neuromuscular pathways in our application.
AB - To study complex neuromuscular control pathways in human movement, biomechanical parametric models and system identification methods are employed. Although test-retest reliability is widely used to validate outcomes of motor control tasks, it was not incorporated in system identification methods. This study investigates the feasibility of incorporating test-retest reliability in our previously published method of selecting sensitive parameters. We consider the selected parameters via this novel approach to be the key neuromuscular parameters because they meet three criteria: reduced variability, improved goodness of fit, and excellent reliability. These criteria ensure that parameter variability is below a user-defined value, the number of these parameters is maximized to enhance goodness of fit, and their test-retest reliability is above a user-defined value. We measured variability, goodness of fit, and reliability using Fisher information matrix, variance accounted for, and intraclass correlation, respectively. We also incorporated model diversity as a fourth optional criterion to narrow down the solution space of key parameters. We applied this approach to head position tracking in axial rotation and flexion/extension. Forty healthy subjects performed the tasks during two visits. With variability and reliability measures ≤0.35 and ≥0.75 respectively, we selected three key parameters out of twelve with goodness of fit >69%. The key parameters were associated with at least two neuromuscular pathways out of four modeled pathways (visual, proprioceptive, vestibular, and intrinsic), which is a measure of model diversity. Therefore, it is feasible to incorporate reliability and diversity in system identification of key neuromuscular pathways in our application.
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U2 - 10.1109/TNSRE.2019.2891525
DO - 10.1109/TNSRE.2019.2891525
M3 - Article
C2 - 30629508
AN - SCOPUS:85059803533
JO - IEEE Transactions on Neural Systems and Rehabilitation Engineering
JF - IEEE Transactions on Neural Systems and Rehabilitation Engineering
SN - 1534-4320
ER -