Reinforcement-induced movement therapy: A novel approach for overcoming learned non-use in chronic stroke patients

• Published in: 2015 International Conference on Virtual Rehabilitation (ICVR) pp. 183 - 190
• Main Authors: Ballester, Belen Rubio, Maier, Martina, San Segundo, Rosa, Castaneda Galeano, Victoria, Duff, Armin, Verschure, Paul F. M. J.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: IEEE 01.06.2015
• Subjects: Computational modeling; Conferences; Electronic mail; Mathematical models; Medical treatment; Neurons; Optimization; Patients; Planing; Predictive models; Rehabilitation; Reinforcement; Strokes; Therapy; Trajectory
• ISSN: 2331-9569
• DOI: 10.1109/ICVR.2015.7358586

An open question in stroke rehabilitation is, if and how chronic patients can still make improvements after they reached a plateau in motor recovery. Previous research has shown that Constraint-Induced Movement Therapy (CIMT) might be effective in treating hemiparesis and supporting functional improvements in chronic patients, but that it might also be associated with higher costs in terms of demand, resources and inconvenience for the patient. Here, we offer a new therapeutic approach that combines CIMT with a positive reinforcement component. We suggest that this new therapy, called Reinforcement-Induced Movement Therapy (RIMT), might be similarly effective as CIMT and could be suitable for a broader population of chronic stroke patients. We first implemented a computational model to study the potential outcome of different CIMT and RIMT therapy combinations. Then we present the results of an ongoing clinical trial that supports predictions from the model. We conclude that an optimally combined CIMT and RIMT therapy might propose a novel and powerful rehabilitation approach, addressing the specific needs of chronic stroke patients.