Home-based upper extremity rehabilitation support using a contactless ultrasonic sensor.

Home-based rehabilitation protocols have been shown to improve outcomes amongst individuals with limited upper-extremity (UE) functionality. While approaches employing both video conferencing technologies and gaming platforms have been successfully demonstrated for such applications, concerns regarding patient privacy and technological complexity may limit further adoption. As an alternative solution for assessing adherence to prescribed UE rehabilitation protocols, the Echolocation Activity Detector, a linear array of first-reflection ultrasonic distance sensors, is proposed herein. To demonstrate its utility for home-based rehabilitation, a controlled experiment exploring the ability of the system to distinguish between various parameters of UE motion, including motion plane, range, and speed, was conducted for five participants. Activity classification is accomplished using a quadratic support vector machine classifier using time-domain features which exploit the known geometric relationships between the patient and the device, along with the ideal kinematics of the activities of interest. Average classification accuracy for the five classes of UE motion considered herein exceeds 91%.