Developing RPC-Net: Leveraging High-Density Electromyography and Machine Learning for Improved Hand Position Estimation

Conclusion: The results demonstrate that RPC-Net is capable of accurately translating forearm electromyographic activity into hand position, offering a practical and adaptable tool that may be accessible in clinical settings. Significance: The development of RPC-Net represents a significant advancement. In clinical settings, its application could enable prosthetic devices to be controlled in a way that feels more natural, improving the quality of life for individuals with limb loss.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research