High-fidelity interfacing for bionic rehabilitation

Bionic rehabilitation leverages advanced bionic technology to enhance mobility and functional abilities in individuals with limited sensorimotor capabilities. However, the development of bionic interfaces has not kept pace with the latest technological advancements. This chapter aims to examine the most recent efforts in establishing high-fidelity interfaces for bionic systems, with a focus on prosthetic limbs for upper limb impairments. It discusses the limitations of current bionic interfacing solutions, highlighting the suboptimal volitional control experienced by many prosthetic users. While direct interfacing with the brain and peripheral nerves poses challenges, muscle interfacing through electromyographic (EMG) controllers has emerged as a clinically viable neural solution. However, current EMG controllers offer limited functionality, prompting the exploration of machine learning-based approaches. The chapter also addresses the restoration of sensory feedback in bionic systems, which remains a complex and challenging task. While alternative approaches such as mechanical or electrical stimulation have been used, direct nerve and brain stimulations show promise but present technical and ethical challenges. Recent research efforts have focused on enhancing the quality and quantity of information transmitted via bionic interfaces. This involves decoding human neural drive and exploring adaptive algorithms for intuitive and robust control paradigms. Furthermore, the chapter emphasizes the need to unravel the mechanisms of sensory integration and perception to design more objective sensory interfaces. In summary, the chapter provides insights into user needs, technological approaches, and recent scientific and clinical advances in the field of bionic interfaces. By addressing the limitations and exploring novel solutions, the aim is to advance the field of bionic rehabilitation and improve the overall effectiveness and user satisfaction of bionic systems.