Research on Sports Injury Rehabilitation Detection Based on IoT Models for Digital Health Care

Area of Science:

• Digital Health
• Internet of Things (IoT)
• Sports Rehabilitation

Background:

• Sports rehabilitators manage common sports injuries and work-related musculoskeletal issues.
• Digital health care leverages technology for accessible and sustainable medical treatment.
• IoT enables real-time monitoring of medical equipment and resource management.

Purpose of the Study:

• To design a health care IoT-enabled body area network (HIoT-BAN) for improved sports injury rehabilitation detection.
• To address challenges in digital health care for sports rehabilitation, including player position, game strategies, and cybersecurity.
• To enhance the speed and accuracy of sports injury rehabilitation detection within digital health care frameworks.

Main Methods:

• Development of a health care IoT-enabled body area network (HIoT-BAN).
• Integration of IoT sensors for real-time monitoring of medical equipment and patient data.
• Experimental analysis comparing HIoT-BAN with traditional IoT methods for performance metrics.

Main Results:

• The HIoT-BAN system effectively predicts and indicates sports injury rehabilitation detection.
• Experimental analysis demonstrates superior performance of HIoT-BAN over standard IoT methods.
• Key performance improvements include higher accuracy, better prediction ratios, and reduced mean square error.

Conclusions:

• The HIoT-BAN is a viable and effective solution for advancing sports injury rehabilitation detection in digital health care.
• The proposed system enhances patient safety and optimizes health care investment management.
• HIoT-BAN technology offers a pathway to faster and more accurate digital health care delivery for sports injuries.