alexa Prediction of Stance Time and Force Symmetries using In
ISSN: 2155-9538

Journal of Bioengineering & Biomedical Science
Open Access

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Research Article

Prediction of Stance Time and Force Symmetries using Instrumented Shoe Insoles for Use in Rehabilitation and Weight-Bearing Regimens

K.O. Greenland, L. Yang, P.S. Dyer, R.J. Carson, J. B. Webster, A.S. Merryweather, K.B. Foreman and S.J.M. Bamberg*

University of Utah, USA

*Corresponding Author:
Stacy Bamberg
50 S. Central Campus Dr.
MEB Room 2110
Salt Lake City, UT 84112
Tel: 801 585 9081
Fax: 801 581 9826
E-mail: [email protected]

Received Date: November 05, 2011; Accepted Date: November 21, 2011; Published Date: November 22, 2011

Citation: Greenland KO, Yang L, Dyer PS, Carson RJ, Webster JB , et al. (2011) Prediction of Stance Time and Force Symmetries using Instrumented Shoe Insoles for Use in Rehabilitation and Weight-Bearing Regimens. J Bioeng Biomed Sci S1:005. doi:10.4172/2155-9538.S1-005

Copyright: © 2011 Greenland KO, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

Objective: Evaluate predictions of stance time symmetry and stance force symmetry from wireless bilateral instrumented shoe insoles designed for rehabilitation using smartphone applications to provide real-time feedback.

Design: Cross-sectional study.

Subjects: Five subjects with no known gait abnormalities.

Methods: Subjects performed ten trials of three conditions: walking without a limp, limping on the right foot, and limping on the left foot, with data captured simultaneously with two force plates and the instrumented shoe insoles. Linear regression analyses were used to develop prediction equations and significance.

Results: The regression between the instrumented shoe insole and the force plate resulted in R-squared values ranging from 0.952 to 0.998 for stance time symmetry using symmetry ratio, and from 0.936 to 0.994 for stance force symmetry using a cumulative loading measure for force. With peak and average loading measures, R-squared values were lower and more variable.

Conclusion: Symmetry based on stance times or stance forces was highly predicted using the instrumented shoe insoles. Instrumented shoe insoles and real-time feedback on a smartphone could be used in the future for improving patient compliance with weight-bearing regimens or other time or force based symmetry analyses outside of the gait laboratory setting.

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