Machine Learning in Robot Assisted Upper Limb Rehabilitation: A Focused Review

Robot-assisted rehabilitation, which can provide repetitive, intensive and high-precision physics training, has a positive influence on motor function recovery of stroke patients. Current robots need to be more intelligent reliable in clinical practice. Machine learning algorithms (MLAs) are able learn from data predict future unknown conditions, is benefit improve the effectiveness robot-assisted rehabilitation. In this paper, we conduct focused review machine learning-based methods for upper limb Firstly, current status rehabilitation presented. Then, outline analyze designs applications MLAs movement intention recognition, human-robot interaction control quantitative assessment function. Meanwhile, discuss directions MLAs-based robotic This article provides summary contributes design development advanced medical devices.