Development of a Shoulder Disarticulation Prosthesis System Intuitively Controlled With the Trunk Surface...

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Prosthetics

Background:

• Shoulder disarticulation presents significant challenges for prosthetic control.
• Existing systems often require extensive user training and adaptation.

Purpose of the Study:

• To develop an intuitively operational shoulder disarticulation prosthesis system.
• To enable prosthesis control using surface electromyogram (EMG) signals from the trunk.
• To minimize the need for long-term user training.

Main Methods:

• Developed a prosthesis with four degrees of freedom joints.
• Implemented a user-adapting control system utilizing machine learning and trunk surface EMG.
• Identified optimal EMG measurement sites on the chest and back using principal component analysis.
• Evaluated system performance with healthy subjects and a bilateral shoulder disarticulation amputee.

Main Results:

• Healthy subjects successfully grasped and moved objects in horizontal and vertical planes using the EMG-controlled prosthesis.
• A bilateral shoulder disarticulation amputee demonstrated comparable performance to healthy subjects in evaluation tasks.
• The system proved to be intuitively operational, requiring minimal training.

Conclusions:

• The developed shoulder disarticulation prosthesis system offers intuitive control via trunk EMG.
• This technology has the potential to significantly improve the quality of life for individuals with shoulder disarticulation.
• The machine learning-based adaptive control system enhances usability and reduces training requirements.