A Multimodal Stimulation System for Conveying Diverse Feedback in Hand Prosthetics: Preliminary Assessment

Artificial somatosensory feedback plays a crucial role in compensating for tactile and proprioceptive loss in prosthesis users. Although modern prosthetic systems can acquire rich sensory data, effectively conveying this multimodal information to the user remains a significant challenge. This study presents a wearable somatosensory feedback armband with two configurations: a multimodal version using combined vibrotactile-electrotactile (VEC) stimulation, and a unimodal version based on vibrotactile-only (VO) stimulation. In both configurations, proprioceptive feedback is conveyed via spatiotemporal vibrotactile patterns, while tactile and proximity feedback are transmitted using electrotactile stimulation in VEC and vibrotactile cues in VO. The novel system was evaluated in ten transradial amputees in psychophysical experiments, and in seven additional participants (two amputees and five non-disabled) who performed object grasping and manipulation tasks (OGMT) under four conditions. Results showed that both configurations enabled accurate recognition of multiple sensory variables, with average accuracies exceeding 90% across all conditions, and success rates above 80% in OGMT. The success rate of the proposed system was not significantly different compared to that achieved with natural visual-auditory feedback (VA). However, VA resulted in significantly lower time to perform the task. The participants reported that VEC reduced cognitive fatigue under multi-modal feedback, and VO was linked to greater willingness for long-term use. These findings demonstrate that the proposed system offers a novel, flexible, and precise platform for prosthetic sensory feedback. By leveraging multiple stimulation modalities and spatio-temporal encoding, the VEC configuration expands the range of sensory inputs, enabling more diverse, and accurate stimulation for users requiring enhanced feedback. Meanwhile, the VO configuration effectively meets most sensory feedback needs with simpler integration, making it well-suited for broader applications.