학술논문
The effect of gamified robot-enhanced training on motor performance in chronic stroke survivors.
Document Type
Academic Journal
Author
Ozgur AG; Computer Human Interaction in Learning and Instruction (CHILI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.; Division of Robotics, Perception and Learning (RPL), EECS, KTH Royal Institute of Technology, Stockholm, Sweden.; Wessel MJ; Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Defitech Chair of Clinical Neuroengineering, Clinique Romande de Réadaptation, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Sion, Switzerland.; Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany.; Olsen JK; University of San Diego, San Diego, CA, USA.; Cadic-Melchior AG; Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Defitech Chair of Clinical Neuroengineering, Clinique Romande de Réadaptation, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Sion, Switzerland.; Zufferey V; Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Defitech Chair of Clinical Neuroengineering, Clinique Romande de Réadaptation, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Sion, Switzerland.; Johal W; School of Computing and Information Systems, University of Melbourne, Victoria, Australia.; Dominijanni G; Bertarelli Foundation Chair in Translational NeuroEngineering, Center for Neuroprosthetics and School of Engineering, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.; Turlan JL; Neurological Rehabilitation Department of Clinique Romande de Réadaptation (SUVA), Sion, Switzerland.; Mühl A; Neurological Rehabilitation Department of Clinique Romande de Réadaptation (SUVA), Sion, Switzerland.; Bruno B; Computer Human Interaction in Learning and Instruction (CHILI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.; Vuadens P; Neurological Rehabilitation Department of Clinique Romande de Réadaptation (SUVA), Sion, Switzerland.; Dillenbourg P; Computer Human Interaction in Learning and Instruction (CHILI), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.; Hummel FC; Defitech Chair of Clinical Neuroengineering, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland.; Defitech Chair of Clinical Neuroengineering, Clinique Romande de Réadaptation, Neuro-X Institute (INX) and Brain Mind Institute (BMI), École Polytechnique Fédérale de Lausanne (EPFL Valais), Sion, Switzerland.; Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland.
Source
Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101672560 Publication Model: eCollection Cited Medium: Print ISSN: 2405-8440 (Print) Linking ISSN: 24058440 NLM ISO Abbreviation: Heliyon Subsets: PubMed not MEDLINE
Subject
Language
English
ISSN
2405-8440
Abstract
Task-specific training constitutes a core element for evidence-based rehabilitation strategies targeted at improving upper extremity activity after stroke. Its combination with additional treatment strategies and neurotechnology-based solutions could further improve patients' outcomes. Here, we studied the effect of gamified robot-assisted upper limb motor training on motor performance, skill learning, and transfer with respect to a non-gamified control condition with a group of chronic stroke survivors. The results suggest that a gamified training strategy results in more controlled motor performance during the training phase, which is characterized by a higher accuracy (lower deviance), higher smoothness (lower jerk), but slower speed. The responder analyses indicated that mildly impaired patients benefited most from the gamification approach. In conclusion, gamified robot-assisted motor training, which is personalized to the individual capabilities of a patient, constitutes a promising investigational strategy for further improving motor performance after a stroke.
Competing Interests: The authors declare no conflict of interest.
(© 2022 The Author(s).)
Competing Interests: The authors declare no conflict of interest.
(© 2022 The Author(s).)