This paper presents a new method to investigate the multivariable time-varying behavior of the ankle during human walking, and provides the first experimental results from treadmill walking. A wearable ankle robot with an ensemble-based linear time-varying system identification method enabled identification of transient ankle mechanical impedance in 2 degrees of freedom, both in the sagittal and frontal planes. Several important issues of the ensemble-based identification method in practical measurements are discussed, especially a strategy to solve the limitation of the method which assumes that the system undergoes the same time-varying behavior on every stride. The suggested method was successfully applied to 15 minutes of human walking on a treadmill. Experiments with 10 young healthy subjects showed clear time-varying behavior of ankle impedance across the gait cycle, except the mid-stance phase. Interestingly, most subjects increased ankle impedance just before heel strike in both degrees of freedom. Interpretation of impedance changes was consistent with analysis of electromyographic signals from major muscles related to ankle movements.
- Dynamic Systems and Control Division
Linear Time-Varying Identification of Ankle Mechanical Impedance During Human Walking
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Lee, H, Krebs, HI, & Hogan, N. "Linear Time-Varying Identification of Ankle Mechanical Impedance During Human Walking." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 1: Adaptive Control; Advanced Vehicle Propulsion Systems; Aerospace Systems; Autonomous Systems; Battery Modeling; Biochemical Systems; Control Over Networks; Control Systems Design; Cooperative and Decentralized Control; Dynamic System Modeling; Dynamical Modeling and Diagnostics in Biomedical Systems; Dynamics and Control in Medicine and Biology; Estimation and Fault Detection; Estimation and Fault Detection for Vehicle Applications; Fluid Power Systems; Human Assistive Systems and Wearable Robots; Human-in-the-Loop Systems; Intelligent Transportation Systems; Learning Control. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 753-758. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8674
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