A dynamic decision network framework for online media adaptation in stroke rehabilitation

Abstract

In this article, we present a media adaptation framework for an immersive biofeedback system for stroke patient rehabilitation. In our biofeedback system, media adaptation refers to changes in audio/visual feedback as well as changes in physical environment. Effective media adaptation frameworks help patients recover generative plans for arm movement with potential for significantly shortened therapeutic time. The media adaptation problem has significant challenges-(a) high dimensionality of adaptation parameter space; (b) variability in the patient performance across and within sessions; (c) the actual rehabilitation plan is typically a non-first-order Markov process, making the learning task hard.Our key insight is to understand media adaptation as a real-time feedback control problem. We use a mixture-of-experts based Dynamic Decision Network (DDN) for online media adaptation. We train DDN mixtures per patient, per session. The mixture models address two basic questions-(a) given a specific adaptation suggested by the domain experts, predict the patient performance, and (b) given the expected performance, determine the optimal adaptation decision. The questions are answered through an optimality criterion based search on DDN models trained in previous sessions. We have also developed new validation metrics and have very good results for both questions on actual stroke rehabilitation data.

CAHR: A Contextually Adaptive Home-Based Rehabilitation Framework

“…The game adaptation is achieved through a simple accuracy test function that provides an accuracy ratio between the number of successful and unsuccessful trials. Chen [19] introduced a media adaptation framework that can be used in a multi-model biofeedback system [20] for stroke patients undergoing arm rehabilitation. The adaptation model is based on a pre-trained Dynamic Decision Network (DDN) that predicts the patient's performance and suggests an online optimal adaptation decision to the rehabilitation team (e.g.…”

Thoroughly Approach to Upper Limb Rehabilitation Using Serious Games for Intensive Group Physical Therapy or Individual Biofeedback Training

“…A new programming tool called PlayWrite was designed to enable mental health professionals to create social simulations for use in mental health settings [9]. To improve the communication between physical therapists and patients, requirements for an authoring tool to enable therapists to create exercise animations for home viewing were produced [10] The development of an application targeted to patients with motor disabilities called Kinerehab is described in [11]. It uses the Kinect sensor to evaluate and estimate the biomechanics of fundamental movements.…”

Digital-pheromone based difficulty adaptation in post-stroke therapeutic games

“…Furthermore, Chen Y. et al [2] propose a framework for media adaptation in task-oriented neuromotor rehabilitation based on biofeedback [9]. This technique is based on the adaptation of players' feedback according to their performances.…”