Adaptive Interface for Personalized Center of Mass Self-Identification in Home Rehabilitation

Abstract

As the center of mass (CoM) position can be used to determine stability, current rehabilitation standards may be improved by tracking it. A personalized CoM estimate can be obtained using the statically equivalent serial chain (SESC) once the model parameters are identified. The identification phase can be completed using low-cost sensors (Kinect and WBB) outside the laboratory making CoM estimation feasible in a patient’s home. This work focuses on: (1) improving the SESC identification quality and speed, and (2) using the estimated CoM to determine stability. Identification time is reduced by creating a visual adaptive interface where the subject’s limbs are colored based on the convergence of the SESC parameters. A study was conducted on eight subjects and showed a faster convergence and lower root mean square error (rmse) when the adaptive interface was used. We found that a model capable of estimating the CoM position with an rmse of 27 mm could be obtained after only 90 s of identification when the interface was used, whereas twice as much time was needed when the interface was not used. The interface that was developed can be used by a subject to track his/her CoM position in a self-directed way. Stability was determined for a squat task using a dynamic index obtained from the estimated CoM trajectory and using only Kinect measurements. This shows one potential application for home rehabilitation and monitoring.