TY - JOUR
T1 - Estimation of intrinsic and reflex contributions to muscle dynamics
T2 - A modeling study
AU - Perreault, E. J.
AU - Crago, P. E.
AU - Kirsch, R. F.
N1 - Funding Information:
Manuscript received April 22, 1999; revised July 10, 2000. This work was supported by the Department of Veteran Affairs Rehabilitation Research and Development Service, the National Institute of Health, and the Cleveland FES Institute. Asterisk indicates corresponding author. *E. J. Perreault was with with the Biomedical Engineering Department, Case Western Reserve University and the Louis Stokes VA Medical Center, Cleveland, OH 44106 USA. He is now with the Physiology Department, Ward 5-295, Northwestern University Medical School, 303 E. Chicago Ave., Chicago, IL 60611 USA (e-mail: [email protected]).
PY - 2000/11
Y1 - 2000/11
N2 - This work evaluated system identification-based approaches for estimating stretch reflex contributions to muscle dynamics. Skeletal muscle resists externally imposed stretches via both intrinsic stiffness properties of the muscle and reflexively mediated changes in muscle activation. To separately estimate these intrinsic and reflex components, system identification approaches must make several assumptions. We examined the impact of making specific structural assumptions about the intrinsic and reflex systems on the system identification accuracy. In particular, we compared an approach that made specific parametric assumptions about the reflex and intrinsic subsystems to another that assumed more general nonparametric subsystems. A simulation-based approach was used so that the 'true' characters of the intrinsic and reflex systems were known; the identification methods were judged on their abilities to retrieve these known system properties. Identification algorithms were tested on three experimentally based models describing the stretch reflex system. Results indicated that the assumed form of the intrinsic and reflex systems had a significant impact on the stiffness separation accuracy. In general, the algorithm incorporating nonparametric subsystems was more robust than the fully parametric algorithm because it had a more general structure and because it provided a better indication of the appropriateness of the assumed structure.
AB - This work evaluated system identification-based approaches for estimating stretch reflex contributions to muscle dynamics. Skeletal muscle resists externally imposed stretches via both intrinsic stiffness properties of the muscle and reflexively mediated changes in muscle activation. To separately estimate these intrinsic and reflex components, system identification approaches must make several assumptions. We examined the impact of making specific structural assumptions about the intrinsic and reflex systems on the system identification accuracy. In particular, we compared an approach that made specific parametric assumptions about the reflex and intrinsic subsystems to another that assumed more general nonparametric subsystems. A simulation-based approach was used so that the 'true' characters of the intrinsic and reflex systems were known; the identification methods were judged on their abilities to retrieve these known system properties. Identification algorithms were tested on three experimentally based models describing the stretch reflex system. Results indicated that the assumed form of the intrinsic and reflex systems had a significant impact on the stiffness separation accuracy. In general, the algorithm incorporating nonparametric subsystems was more robust than the fully parametric algorithm because it had a more general structure and because it provided a better indication of the appropriateness of the assumed structure.
KW - Muscle
KW - Simulation
KW - Stiffness
KW - Stretch reflex
KW - System identification
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U2 - 10.1109/TBME.2000.880092
DO - 10.1109/TBME.2000.880092
M3 - Article
C2 - 11077734
AN - SCOPUS:0034327893
SN - 0018-9294
VL - 47
SP - 1413
EP - 1421
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
IS - 11
ER -