Surface EMG-Validated Multi-DoF Wheelchair-Based Rehabilitation Device

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Internet of Things (IoT)

Background:

• Rehabilitation is crucial for motor function recovery after neurological injury.
• Current robotic systems often focus on single limb types or have limited motion capabilities.
• Therapist-assisted rehabilitation can be resource-intensive and may not suit all recovery phases.

Purpose of the Study:

• To engineer an integrated, IoT-enabled robotic system for both upper and lower limb rehabilitation.
• To incorporate electromyography (EMG) signals for enhanced movement characterization and personalization.
• To provide a versatile assistive solution for patients with hemiplegia, paraplegia, and tetraplegia.

Main Methods:

• Development of a wheelchair-based robotic assistive system for simultaneous upper and lower limb movement.
• Integration of a novel electromyography (EMG) signal processing module for movement analysis.
• Implementation of an IoT framework for remote monitoring and control, enabling home-based rehabilitation.

Main Results:

• Successful development and prototyping of the dual-limb assistive robotic system.
• Demonstration of EMG signal utilization for characterizing diverse muscle movements.
• Validation of the system's potential for personalized and accessible rehabilitation.

Conclusions:

• The developed system offers a novel, integrated approach to robotic limb rehabilitation.
• IoT enablement and EMG integration enhance personalization and remote accessibility.
• This technology holds promise for improving recovery outcomes for patients with various forms of paralysis.