An Intelligent Body Posture Analysis Model Using Multi-Sensors for Long-Term Physical Rehabilitation
Chin-Feng Lai1, Ren-Hung Hwang2, Ying-Hsun Lai3
1Department of Engineering Science, National Cheng Kung University, Tainan, 701, Taiwan, Republic of China. cinfon@ieee.org.
Journal of Medical Systems
|March 16, 2017
Summary
This study introduces an Intelligent Body Posture Analysis Model using sensors to track body motion. This technology aids in personalized physical rehabilitation by analyzing individual limb characteristics.
Area of Science:
- Biomedical Engineering
- Human-Computer Interaction
- Rehabilitation Science
Background:
- Human posture analysis is complex due to gravity, individual body structures, and motion.
- Existing methods struggle to account for diverse limb characteristics and gravitational forces.
- Personalized physical rehabilitation requires accurate, individualized body state detection.
Purpose of the Study:
- To propose a novel "Intelligent Body Posture Analysis Model" for computer diagnosis.
- To detect and analyze body motion patterns considering individual limb characteristics.
- To enable long-term physical rehabilitation tailored to unique patient needs.
Main Methods:
- Utilized multiple acceleration sensors and gyroscopes to capture body motion data.
- Developed a model to interpret sensor data for body posture identification.
- Incorporated analysis of individual limb characteristics and gravitational forces.
Main Results:
- The "Intelligent Body Posture Analysis Model" effectively detects body motion patterns.
- Experimental validation confirmed the scheme's effectiveness across various postures.
- The model demonstrates potential for accurate body state diagnosis.
Conclusions:
- The proposed model offers a viable solution for intelligent body posture analysis.
- This approach facilitates personalized physical rehabilitation strategies.
- Further research can refine the model for broader clinical applications.
