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An intelligent, adaptive, performance‐sensitive, and virtual reality‐based gaming platform for the upper limb
Author(s) -
Dhiman Ashish,
Solanki Dhaval,
Bhasin Ashu,
Das Abhijit,
Lahiri Uttama
Publication year - 2018
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1800
Subject(s) - virtual reality , physical medicine and rehabilitation , task (project management) , rehabilitation , upper limb , stroke (engine) , computer science , activities of daily living , lower limb , weakness , human–computer interaction , medicine , physical therapy , anatomy , mechanical engineering , surgery , management , engineering , economics
Stroke is a leading cause of adult disability, characterized by a spectrum of muscle weakness and movement abnormalities related to the upper limb. About 80% of individuals who had a stroke suffer from upper limb dysfunction. Conventional rehabilitation aims to improve one's ability to use paralyzed limbs through repetitive exercise under one‐on‐one supervision by physiotherapists. This poses difficulty given the limited availability of healthcare resources and the high cost of availing specialized services at healthcare centers, particularly in developing countries like India. Thus, the design of cost‐effective, home‐based, and technology‐assisted individualized rehabilitation platform that can deliver real‐time feedback on one's skill progress is critical. This paper describes the design of a novel, multimodal, virtual reality (VR)‐based, and performance‐sensitive exercise platform that can intelligently adapt its task presentation to one's performance. Here, we aim to address unilateral shoulder abduction and adduction that are essential for the performance of daily living activities. We designed an experimental study in which six individuals who had chronic stroke (post‐stroke period: >6 months) participated. While they interacted with our VR‐based tasks, we recorded their physiological signals in a synchronized manner. Preliminary results indicate the potential of our VR‐based, adaptive individualized system in the performance of individuals who had a stroke suffering from upper limb movement disorders.