Neural Engineering Center, Biomedical Engineering, Case Western Reserve University, Cleveland, USA.
Department of Biomedical Engineering, Jordan University of Science and Technology, Irbid, Jordan.
Sci Rep. 2018 Sep 20;8(1):14149. doi: 10.1038/s41598-018-32357-7.
Interfaces with the peripheral nerve provide the ability to extract motor activation and restore sensation to amputee patients. The ability to chronically extract motor activations from the peripheral nervous system remains an unsolved problem. In this study, chronic recordings with the Flat Interface Nerve Electrode (FINE) are employed to recover the activation levels of innervated muscles. The FINEs were implanted on the sciatic nerves of canines, and neural recordings were obtained as the animal walked on a treadmill. During these trials, electromyograms (EMG) from the surrounding hamstring muscles were simultaneously recorded and the neural recordings are shown to be free of interference or crosstalk from these muscles. Using a novel Bayesian algorithm, the signals from individual fascicles were recovered and then compared to the corresponding target EMG of the lower limb. High correlation coefficients (0.84 ± 0.07 and 0.61 ± 0.12) between the extracted tibial fascicle/medial gastrocnemius and peroneal fascicle/tibialis anterior muscle were obtained. Analysis calculating the information transfer rate (ITR) from the muscle to the motor predictions yielded approximately 5 and 1 bit per second (bps) for the two sources. This method can predict motor signals from neural recordings and could be used to drive a prosthesis by interfacing with residual nerves.
与外周神经的接口提供了从截肢患者身上提取运动激活并恢复感觉的能力。从周围神经系统中长时间提取运动激活的能力仍然是一个未解决的问题。在这项研究中，使用平面接口神经电极 (FINE) 进行慢性记录，以恢复受神经支配的肌肉的激活水平。FINE 被植入犬的坐骨神经上，并在动物在跑步机上行走时获得神经记录。在这些试验中，同时记录周围的半腱肌的肌电图 (EMG)，并且神经记录显示没有来自这些肌肉的干扰或串扰。使用新颖的贝叶斯算法，恢复了各个神经束的信号，然后将其与下肢的相应目标 EMG 进行比较。从提取的胫骨神经束/内侧腓肠肌和腓神经束/胫骨前肌中获得了高相关系数（0.84±0.07 和 0.61±0.12）。从肌肉到运动预测的信息传输率 (ITR) 的分析得出，这两个来源的约为 5 和 1 比特每秒 (bps)。该方法可以从神经记录中预测运动信号，并可以通过与残留神经接口来驱动假肢。
