针对截肢者的手功能康复具有重大社会意义和需求，假肢手为他们提供了智能康复的全新手段。但目前最先进的肌电假肢手仍因缺乏触觉感知反馈和如人体般的柔和抓力。我们前期发现了截肢末端的“诱发指感”现象，据此开发了表面电刺激感知反馈技术；还根据脊髓神经反射原理建立了“虚拟反射”式柔顺运动模型。进一步的关键问题是获取中枢神经的控制信号，驱动假肢手的仿生柔顺运动。人手的灵巧操作依赖连续感觉反馈与运动控制输出。假肢手感知与控制的科学问题是如何依机械触觉在大脑皮层诱发特定的感觉效应，进而引导皮层可塑性向提高截肢者控制功能的方向进行。本项目将开展创新的表面电刺激诱发指感及神经控制和接口技术的基础研究，建立假肢手感知反馈及前馈控制的双向通道；采用新兴的碳纳米线微电极，在外周神经提取大脑的前馈控制信号；并利用最新的神经拟态芯片脊髓虚拟反射技术，实现假肢手的仿生柔顺控制。集成这些技术将大幅提高假肢手的功能和灵巧操作。

Rehabilitation of hand functions for amputee caters to significant social benefits and demand, for which intelligent prosthetic hands seem to provide innovative solutions. Yet, even the most advanced myoelectric prosthetic hand still lacks tactile feedback and human-like compliant grip. We previously found that the amputation stumps exist a phenomenon of “evoked tactile sensation”, from which we could develop a technology of artificial sensory feedback using transcutaneous electrical nerve stimulation (TENS). Moreover, based on the principle of spinal reflex we developed a “virtual reflex” model for compliant movement control. The subsequent key issue is to obtain a control signal from the central nervous system, and produce compliant movements on prosthetic hands. The dexterous manipulation of human hand relies on continuous feedback from sensory receptors and regulation of motor outputs. Therefore when creating sensation and motion for prosthetic hands, the scientific questions of interest are how to convey specific sensory information to somatosensory cortex according to the mechanical pressure at prosthetic fingers, and how to guide cortical plasticity toward improving the controllability of amputee. This project will conduct innovative fundamental research on sensory feedback based on evoked-tactile-sensation using TENS, and virtual reflex control of compliant movement coupled with novel neural interface technology. This study will establish a two-way communication between prosthetic hand and amputee for exchanging information of sensory feedback and motor feedforward control. We seek to acquire control command signal of the central nervous system from peripheral nerve recording using the recently available carbon nanowire microelectrodes. Leveraging on the latest technology of neuromorphic model of “virtual reflex”, we aim to achieve human-like control of compliant movements in prosthetic hands. Integrating these technologies will significantly enhance the functionality and performance of neural prosthetic hand.