Sensory feedback improves dexterous use of a bionic arm, and sensory signals that mimic natural ones are more intuitive and useful. We describe use of a bidirectional neuromyoelectric prosthetic hand that conveys biomimetic sensory feedback. Electromyographic recordings from residual arm muscles were decoded to provide independent and proportional control of a six-DOF prosthetic hand and wrist—the DEKA LUKE arm. Activation of contact sensors on the prosthesis resulted in intraneural microstimulation of residual sensory nerve fibers through chronically implanted Utah Slanted Electrode Arrays, thereby evoking tactile percepts on the phantom hand. With sensory feedback enabled, the participant exhibited greater precision in grip force and was better able to handle fragile objects. With active exploration, the participant was also able to distinguish between small and large objects and between soft and hard ones. When the sensory feedback was biomimetic—designed to mimic natural sensory signals—the participant was able to identify the objects significantly faster than with the use of traditional encoding algorithms that depended on only the present stimulus intensity. Thus, artificial touch can be sculpted by patterning the sensory feedback, and biologically inspired patterns elicit more interpretable and useful percepts.

中文翻译：

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通过周围神经刺激的仿生感觉反馈改善了仿生手的灵巧使用

感觉反馈改善了仿生手臂的灵巧使用，模仿自然信号的感觉信号更加直观和有用。我们描述了传达仿生感觉反馈的双向神经肌电假肢手的使用。对来自残余手臂肌肉的肌电图记录进行解码，以提供对六自由度假肢手和手腕-DEKA LUKE手臂的独立且成比例的控制。假体上接触传感器的激活导致通过慢性植入的犹他州倾斜电极阵列对残留的感觉神经纤维进行神经内微刺激，从而在幻像手上产生触觉感知。在启用了感官反馈的情况下，参与者表现出更高的抓地力精确度，并且能够更好地处理易碎物品。经过积极探索，参与者还能够区分大小物体以及软硬物体。当感觉反馈是仿生的（旨在模拟自然的感觉信号）时，与使用仅依赖于当前刺激强度的传统编码算法相比，参与者能够更快地识别出物体。因此，可以通过对感官反馈进行图案化来雕刻人造触摸，而生物学启发的图案可以引起更多可解释和有用的感知。