Analysis of Recoverable Falls Via MICROSOFT KINECT: Identification of Third-Order Ankle Dynamics

作者：Segura Mauricio E; Coronado Enrique; Maya Mauro; Cardenas Antonio; Piovesan Davide

来源：Journal of Dynamic Systems Measurement and Control-Transactions of the ASME, 2016, 138(9): 091006.

DOI：10.1115/1.4032878

This work combines the kinematics estimate of human standing with a hybrid identification algorithm to identify a set of ankle dynamics mechanical parameters. We used the hold and release (H&R) experimental paradigm to model a set of recoverable falls on a population of unimpaired adults. Body kinematics was acquired with a MICROSOFT KINECT (MK) version 2 after benchmarking its position accuracy to a camera-based vision system (CVS). The system identification algorithm, combining an extended Kalman filter (EKF) and a genetic algorithm (GA), allowed to identify the effect of tendon and muscle stiffness at the ankle joint, separately. This work highlights that, when associated to soft-computing techniques, affordable tracking devices developed for the gaming industry can be used for the reliable assessment of neuromechanical parameters in clinical settings.

• 出版日期2016-9