The Application of Wearable Sensors and Machine Learning Algorithms in Rehabilitation Training: A Systematic Review

Area of Science:

• Integrative Medicine and Rehabilitation
• Biomedical Engineering
• Artificial Intelligence in Healthcare

Background:

• Wearable sensor technology and machine learning (ML) algorithms are revolutionizing intelligent medical rehabilitation.
• These technologies facilitate the collection of movement, muscle, and nerve data for enhanced patient monitoring.
• Objective evaluation of patient recovery and prediction of disease progression are improved by data-driven insights.

Approach:

• This systematic review analyzed 32 studies from Web of Science and IEEE Xplore.
• The review focused on wearable sensor types, ML algorithm applications, and rehabilitation training approaches for diverse medical conditions.

Key Points:

• Summarizes the usage and compares the effectiveness of various wearable sensors and ML algorithms in rehabilitation.
• Highlights the synergy between wearable sensors and ML for optimizing rehabilitation processes.
• Identifies sensor-algorithm combinations suitable for different disease rehabilitation needs.

Conclusions:

• The combination of wearable sensor technology and machine learning significantly enhances medical rehabilitation efficiency and personalization.
• Specific sensor-algorithm pairings show promise for tailored rehabilitation across different diseases.
• Future research should address current limitations and explore further integration for advanced home rehabilitation solutions.