A Mini review on Effectiveness of Reinforcement learning in Stroke Rehabilitation

Abstract

This review focuses on the Development of Reinforcement based therapies in the field of Rehabilitation of Post -Stroke Patients. The process through which a system's (or organism's) reaction to a stimulus is increased by reward and diminished by punishment (Positive and Negative Reinforcement, respectively) is referred to as reinforcement learning. [1] A plausible set of methods for recreating this reward distribution from experience has been discovered following recent breakthroughs in machine learning. Integration of Reinforcement learning through a Physiotherapeutic perspective is presented in this review. The Brain-Machine interface is a relatively newer as well as potential field which can be used for stroke rehabilitation based on the principles of reinforcement learning which is a subset of Machine Learning.