Review on Machine Learning Applications in Assisted Treadmill for Stroke Rehabilitation

摘要

In the era of internet of things, the demand of machine learning has been increasing rapidly. Especially, the abilities to solve complex problem, classification and automated decision making, become more effective and efficient. One of the application of machine learning is intelligent devices for health-care that provide integrated solutions for patients. This review paper investigates some methodologies for assisted gait training for stroke rehabilitation using treadmill applying machine learning in the applications. Some works such as body weight supported treadmill, automatic synchronization for hardware and software for robotic assisted treadmill training, visual feedback for motor learning, feedback control of oxygen uptake, and control of human heart rate response during exercise, are considered to achieve smart system for stroke rehabilitation. Future work is to implement deep learning for stroke rehabilitation system. The work aims for helping the recovery for after stroke patients.