Upper-limb impedance parameters-based model for motor recovery - Htoon, Zaw Lay; Sidek, Shahrul Na'im (IIUM Press, International Islamic University Malaysia, 2017)
Estimation of patients’ muscle tones allow proper prescription of therapy and determination of physical recovery progress. The book proposes a strategy for the estimation of upper-limb mechanical impedance parameters as a mean for the prediction and assessment of subjects’ muscle tone level and recovery state. The human upper-limb is modeled as a mass-spring-damper system and represented as an Auto Regressive eXogenous (ARX) dynamic equation for the estimation of upper-limb mechanical impedance parameters. The estimated impedance parameters are then fed as inputs to a trained Artificial Neural Network (ANN) which is used to predict, the subjects’ muscle tone level and recovery state during rehabilitation exercise.