AI-Driven Innovations in Neuroprosthetics: Improving Motor Control and Sensory Feedback

Abstract

The field of neuroprosthetics has witnessed significant advancements with the integration of artificial intelligence (AI), promising enhanced motor control and sensory feedback for individuals with limb loss or neurological impairments. AI-driven neuroprosthetic devices leverage machine learning algorithms and neural network models to decode complex neural signals and translate them into precise motor commands, enabling more natural and intuitive prosthetic movements. Additionally, AI facilitates improved sensory feedback mechanisms, allowing users to experience a sense of touch and proprioception. This paper reviews recent AI-driven innovations in neuroprosthetics, focusing on developments in neural signal processing, real-time adaptation, and personalized control strategies. We explore the challenges and future directions in deploying AI technologies for neuroprosthetics, aiming to highlight their potential in transforming patient care and quality of life.