The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, Italy.
J Neural Eng. 2020 Apr 23;17(2):026034. doi: 10.1088/1741-2552/ab8277.
A major challenge in neuroprosthetics is the restoration of sensory-motor hand functions in upper-limb amputees. Neuroprostheses based on the direct re-connection of the peripheral nerves may be an interesting approach for re-establishing the natural and effective bidirectional control of hand prostheses. Recent results have shown that transverse intrafascicular multi-channel electrodes (TIMEs) can restore natural and sophisticated sensory feedback. However, the potential of using TIME-recorded motor intraneural signals to decode grasping tasks has not as yet been explored.
In this study, we show that several hand-movement intentions can be decoded from intraneural signals recorded using four TIMEs implanted in the median and ulnar nerves of an upper limb amputee. Experimental sessions were performed over a week, from day 16 to day 23 after the surgical operation. Intraneural activity was recorded during several hand motor tasks imagined by the subject and processed offline.
We obtained a very high decoding accuracy considering 11 class states (up to 83%). These results confirm that neural signals recorded by multi-channel intraneural electrodes can be used to decode several movement intentions with high accuracy. Moreover, we were able to use same TIME channels for decoding over one week within the first month, even if the stability has to be confirmed during long-term experiments.
Therefore, TIMEs could be used in the future to achieve a complete bidirectional approach exploiting neural pathways, to make a more natural and intuitive new generation of hand prostheses that have a closer resemblance to a healthy hand.
神经假肢领域的一个主要挑战是恢复上肢截肢者的感觉运动手功能。基于外周神经直接重新连接的神经假肢可能是重新建立手假肢的自然有效双向控制的一种有趣方法。最近的结果表明,横向束内多通道电极(TIMES)可以恢复自然而复杂的感觉反馈。然而,使用记录的 TIMES 记录的运动神经内信号来解码抓握任务的潜力尚未得到探索。
在这项研究中,我们展示了可以从植入在上肢截肢者的正中神经和尺神经中的四个 TIMES 记录的神经内信号中解码出几种手部运动意图。实验在手术后第 16 天至第 23 天进行了一周。在受测者想象的几个手部运动任务期间记录神经内活动,并在线下进行处理。
考虑到 11 个类别状态(高达 83%),我们获得了非常高的解码精度。这些结果证实,多通道神经内电极记录的神经信号可以高精度地解码出几种运动意图。此外,我们能够在第一个月内使用相同的 TIME 通道进行解码超过一周,即使在长期实验中必须确认稳定性。
因此,TIMES 将来可用于实现完全双向的神经通路方法,以制造更自然和直观的新一代手假肢,使其更接近健康的手。