MIT Media Lab, 75 Amherst St, Cambridge, MA, 02139, USA.
Department of Mechanical Engineering, MIT, 77 Massachusetts Ave, Cambridge, MA, 02139, USA.
J Neuroeng Rehabil. 2021 Feb 17;18(1):38. doi: 10.1186/s12984-021-00829-z.
Neuroprosthetic devices controlled by persons with standard limb amputation often lack the dexterity of the physiological limb due to limitations of both the user's ability to output accurate control signals and the control system's ability to formulate dynamic trajectories from those signals. To restore full limb functionality to persons with amputation, it is necessary to first deduce and quantify the motor performance of the missing limbs, then meet these performance requirements through direct, volitional control of neuroprosthetic devices.
We develop a neuromuscular modeling and optimization paradigm for the agonist-antagonist myoneural interface, a novel tissue architecture and neural interface for the control of myoelectric prostheses, that enables it to generate virtual joint trajectories coordinated with an intact biological joint at full physiologically-relevant movement bandwidth. In this investigation, a baseline of performance is first established in a population of non-amputee control subjects ([Formula: see text]). Then, a neuromuscular modeling and optimization technique is advanced that allows unilateral AMI amputation subjects ([Formula: see text]) and standard amputation subjects ([Formula: see text]) to generate virtual subtalar prosthetic joint kinematics using measured surface electromyography (sEMG) signals generated by musculature within the affected leg residuum.
Using their optimized neuromuscular subtalar models under blindfolded conditions with only proprioceptive feedback, AMI amputation subjects demonstrate bilateral subtalar coordination accuracy not significantly different from that of the non-amputee control group (Kolmogorov-Smirnov test, [Formula: see text]) while standard amputation subjects demonstrate significantly poorer performance (Kolmogorov-Smirnov test, [Formula: see text]).
These results suggest that the absence of an intact biological joint does not necessarily remove the ability to produce neurophysical signals with sufficient information to reconstruct physiological movements. Further, the seamless manner in which virtual and intact biological joints are shown to coordinate reinforces the theory that desired movement trajectories are mentally formulated in an abstract task space which does not depend on physical limb configurations.
由于标准肢体截肢者输出准确控制信号的能力以及控制系统从这些信号制定动态轨迹的能力均存在限制，因此由截肢者控制的神经假体设备往往缺乏生理肢体的灵活性。为了向截肢者恢复完整的肢体功能，首先必须推断和量化缺失肢体的运动性能，然后通过神经假体设备的直接、自主控制来满足这些性能要求。
我们为肌神经界面开发了一种神经肌肉建模和优化范例，这是一种用于控制肌电假肢的新型组织架构和神经接口，它能够在全生理相关运动带宽内生成与完整生物关节协调的虚拟关节轨迹。在这项研究中，首先在非截肢对照组的人群中建立性能基线([Formula: see text])。然后，提出了一种神经肌肉建模和优化技术，允许单侧 AMI 截肢受试者([Formula: see text])和标准截肢受试者([Formula: see text])使用受影响腿残肢内的肌肉产生的测量表面肌电图(sEMG)信号生成虚拟距下关节假肢关节运动学。
在仅具有本体感受反馈的闭眼条件下使用其优化的距下神经肌肉模型，AMI 截肢受试者的双侧距下协调准确性与非截肢对照组没有显著差异（柯尔莫哥洛夫-斯米尔诺夫检验，[Formula: see text]），而标准截肢受试者的表现则明显较差（柯尔莫哥洛夫-斯米尔诺夫检验，[Formula: see text]）。
这些结果表明，缺乏完整的生物关节不一定会消除产生具有足够信息来重建生理运动的神经物理信号的能力。此外，虚拟和完整生物关节协调的无缝方式进一步证实了这样一种理论，即所需的运动轨迹是在不依赖于物理肢体配置的抽象任务空间中在心理上制定的。
