Integrating ultrasound-based interface with human-inspired somatosensory control for advanced prosthetic systems

Recent advances in control methodologies have significantly improved prosthetic functionality. However, current systems are constrained by a limited number of controllable degrees of freedom and face challenges in effectively handling unexpected external events. Here, we propose a prosthesis interface system that combines ultrasound recording and intention decoding with a human-inspired somatosensory control, allowing the prosthesis to autonomously respond to thermal stimuli and slippage events. Ten participants without amputation and one person with amputation participated in the validation, which included an offline evaluation, three real-time functional tasks with increasing levels of complexity to assess system efficacy and user experience, and one sensory task to evaluate the system's capability to manage slip events and thermal stimuli. The offline analysis yielded an average gesture classification accuracy of 72% and 92% for participants with and without amputation, respectively. Real-time task analysis showed consistent performance among complexity levels. The sensory task showed an instantaneous response of the prosthesis to temperature stimuli ( \\(0.53\\pm 0.16\\) s) and slip events ( \\(0.43\\pm 0.13\\) s) that closely matched natural responses. Building upon previously validated studies, the integration of a human-inspired somatosensory control strategy with an ultrasound-based gesture decoding classifier paves the way for advancing prosthetic technology and improving user experience.