Abstract
We present an e-therapy framework that collects live therapeutic context by analyzing body joint data in a noninvasive way. Using our proposed framework, a therapist can model complex gestures by mapping them to a set of primitive gesture sequences and generate high-level serious game-based therapies. As a proof of concept, we have developed scenarios to express a hemiplegic patient's behavior into a set of trackable primitive gestures. We have used Second Life and Map browsing based serious game environment for immersive experience. The initial feedback from the therapists who have tested our developed framework is encouraging. Finally, we share the implementation details and analysis of test results.
Highlights
A context-aware e-therapy system assumes that each patient is surrounded by a smart 3D space, which will be able to identify him/her at home or outdoors, recognize his/her behaviors, therapeutic activities, and health conditions, and assist the patient according to his/her individual preferences anytime and anywhere
Since the entire test data we present in this paper is collected from either a therapist or a healthy subject, in this case, we assume all therapies to be active therapies, that is, a therapist or a caregiver family member sitting outside the view of the
We have proposed a therapy modeling framework which facilitates for the therapist to design a complex and high-level therapy by combining a set of primitive therapies
Summary
A context-aware e-therapy system assumes that each patient is surrounded by a smart 3D space, which will be able to identify him/her at home or outdoors, recognize his/her behaviors, therapeutic activities, and health conditions, and assist the patient according to his/her individual preferences anytime and anywhere. E-therapy related research has been a center point of many entities such as patients, caregiver social networks, government, research, healthcare and medical institutions, and software industry [1] This is because context-aware e-therapy research domain offers high quality healthcare by leveraging recent advancements in multidisciplinary research domains such as health sensors, smart body area networks, cloud computing, online games, and computer vision techniques. The therapy data originated from each therapy session needs to be stored in a network repository that is accessible to the caregiver institution, medical professional, and the therapists to analyze quality of improvement metrics. These four aspects form the basis of the research presented in this paper. A therapist can define different levels (e.g., simple, intermediate, and advanced levels) of therapy sessions where each unique therapy session is designed for each unique type of disability and the types of activities to be monitored during the session
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