An analytical approach to test and design upper limb prosthesis

Area of Science:

• Biomedical Engineering
• Rehabilitation Engineering
• Neuroprosthetics

Background:

• Surface electromyogram (SEMG) signals offer a non-invasive method for detecting intended limb movements in amputees.
• Accurate interpretation of SEMG signals is crucial for the effective control of advanced prosthetic limbs.
• Existing prosthetic control systems often face challenges in discriminating complex or subtle intended motions.

Purpose of the Study:

• To present signal acquisition techniques, analysis models, and design protocols for an advanced artificial hand prosthesis.
• To evaluate the efficacy of time and frequency domain parameters for estimating amputee's intended motion from SEMG signals.
• To develop and demonstrate a functional hand prosthesis that enhances the daily living capabilities of amputees.

Main Methods:

• Acquisition of SEMG signals using a dual-channel setup.
• Analysis of SEMG signals utilizing time and frequency domain parameters to decode intended movements.
• Design and fabrication of an artificial hand prosthesis, encompassing both electronics and mechanical assembly.

Main Results:

• The employed SEMG analysis techniques demonstrated significant capability in discriminating between four distinct amputee intended activities.
• Experimental results validated the effectiveness of the chosen signal processing methods for prosthetic control.
• The developed artificial hand prosthesis was successfully designed and assembled, integrating sophisticated electronics and mechanics.

Conclusions:

• The developed SEMG-based motion estimation techniques are effective for controlling prosthetic devices.
• The artificial hand prosthesis facilitates the performance of daily routine activities for amputees.
• This research contributes to the advancement of neuroprosthetic technology for improved limb function restoration.