Development of Bioadaptive Smart Prosthetics: Integrating Neuromuscular Interfaces and AI for Personalized Mobility Restoration

Neuromuscular interfaces (NMIs) are emerging as powerful technologies for restoring specific functions in individuals suffering from neurological and functional motor disorders. People who have lost the ability to move their extremities due to various conditions such as spinal cord injury (SCI), stroke, and muscular dystrophy, and those suffering from limb amputations, desire assistive technologies that can restore lost abilities and enhance their quality of life. To address such needs, significant advances in technologies are being recently made, which augur well for better and more human-like restoration of movement abilities .

Motor-intent NATs, designed to ensure a seamless and natural interface with the nervous system, passively monitor neural activity using micro/milli-scale sensors for so-called ‘read-out’ approaches, or, conversely, stimulate the nervous system using electrodes for ‘write-in’ approaches. System intelligence NATs consist of physiologically inspired computing architectures and bioinspired computational approaches, such as artificial hormonal memory, and deep layer inference mechanisms, which are inherently optimized for real-time user-specific operation. Smart system NATs are adaptive, enhancing system intelligence and improving reliability by fusing imaging, sensing, and communication modalities to match expected task complexity.

To create disbursed smart organ-like bioadaptive systems, strong collaborative research and development efforts across fields such as neurophysiology, neural and muscle interfacing technologies, system intelligence, and artificial intelligence/machine learning are now urgently needed. An initial effort to push the grand vision of bioadaptive organ-like systems was undertaken through the four international workshops and master classes. They targeted especially Ph.D. students and early-career researchers. The workshops focused on teaching from both the human and the technology sides related to NMIs and AI for neuromuscular rehabilitation, respectively, whereas others invited participants to design tailored and personalized solutions starting from a user-centric challenge. Along with classroom lectures from leading experts, participants were introduced to tools to model the challenge and proposed designs.