Brain Machine Interfaces for the Control of Prosthetic Fingers

This chapter delves into the challenges of controlling prosthetic fingers for individuals with upper limb amputations. It critiques current commercial systems that rely on surface electromyography, highlighting their limitations in real-world settings. The authors introduce two innovative approaches: the Regenerative Peripheral Nerve Interface (RPNI) and brain-machine interfaces (BMIs). The RPNI surgical technique amplifies nerve signals, creating high-amplitude signals with favorable signal-to-noise ratios. Animal and human studies demonstrate the stability and effectiveness of RPNI signals for controlling thumb movements and various grasp types. Meanwhile, BMIs using brain signals show promise for precise finger control, with performance surpassing that of EMG signals. The chapter also discusses the translational potential and future directions for these technologies in improving prosthetic hand function.