Rule based realtime motion assessment for rehabilitation exercises

Abstract

In this paper, we describe a rule based approach to realtime motion assessment of rehabilitation exercises. We use three types of rules to define each exercise: (1) dynamic rules, with each rule specifying a sequence of monotonic segments of the moving joint or body segment, (2) static rules for stationary joints or body segments, and (3) invariance rules that dictate the requirements of moving joints or body segments. A finite state machine based approach is used in dynamic rule specification and realtime assessment. In addition to the typical advantages of the rule based approach, such as realtime motion assessment with specific feedback, our approach has the following advantages: (1) increased reusability of the defined rules as well as the rule assessment engine facilitated by a set of generic rule elements; (2) increased customizability of the rules for each exercise enabled by the use of a set of generic rule elements and the use of extensible rule encoding method; and (3) increased robustness without relying on expensive statistical algorithms to tolerate motion sensing errors and subtle patient errors.