Control of Multifunctional Prosthetic Hands by Processing the Electromyographic Signal

Area of Science:

• Biomedical Engineering
• Neuroscience
• Rehabilitation Technology

Background:

• The human hand possesses numerous degrees of freedom (DoFs) and sophisticated sensory feedback, enabling complex movements with minimal user effort after training.
• Current prosthetic hands offer limited grasping capabilities and lack sensory feedback, failing to replicate natural hand function.

Purpose of the Study:

• To review traditional methods for controlling artificial hands using electromyographic (EMG) signals.
• To discuss the limitations of current EMG-based prosthetic hand control, particularly the inability to achieve natural control of more than two DoFs.
• To introduce potential future developments in prosthetic hand control strategies.

Main Methods:

• Review of existing literature on electromyographic (EMG) signal control for prosthetic hands.
• Analysis of traditional control techniques in both clinical and research settings.
• Identification of limitations in current multi-DoF prosthetic hand control.

Main Results:

• Traditional EMG-based prosthetic hand control methods are limited, typically allowing control of no more than two DoFs.
• Existing prosthetic hands fail to provide sensory feedback to the user, unlike natural hands.
• A significant gap exists between the capabilities of natural hands and current prosthetic replications.

Conclusions:

• Advancements in EMG signal processing and control algorithms are crucial for developing more functional prosthetic hands.
• Future research should focus on enabling intuitive, multi-DoF control and restoring sensory feedback in prosthetic devices.
• Overcoming the limitations of current prosthetic technology is essential for improving the quality of life for individuals with limb loss.