Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
Adaptive multichannel FES neuroprosthesis with learning control and automatic gait assessment
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DOI：
10.1186/s12984-020-0640-7
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发表时间：
2020-02-28
影响因子：
5.1
通讯作者：
Schauer, Thomas
中科院分区：
文献类型：
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作者：
Mueller, Philipp;del Ama, Antonio J.;Schauer, Thomas
背景FES（功能性电刺激）神经假体长期以来一直是中风或脊髓损伤（SCI）患者康复和步态支持的永久特征。随着时间的推移，众所周知的脚踏开关触发的垂足神经假体扩展到多通道全腿支撑神经假体，从而改善了支撑和康复。然而，这些神经假体必须手动调整，不能适应个人的需要。在最近的研究中，一个学习控制器被添加到垂足神经假体中，这样在摆动阶段的完整刺激模式可以通过测量先前步骤的关节角度来调整。方法本研究的目的是开始开发一种学习型全腿支持神经假体，该假体在步态的各个阶段控制膝关节屈曲和伸展以及踝关节背屈和跖屈的拮抗肌对。建立了一种方法，允许连续评估每一步的膝关节和足关节角度。该方法可以扭曲健康受试者的生理关节角度，以匹配受试者的个体病理步态，从而允许两者的直接比较。提出了一种新的迭代学习控制器（ILC），该控制器的工作与个体的步长无关，并使用生理关节角度参考带。在对四名不完全SCI患者的第一次测试中，结果表明，所提出的神经假体能够为其中三名参与者产生单独适合的刺激模式。另一名参与者受到更严重的影响，由于步态相位检测的错误触发而不得不被排除。对于其余三名参与者中的两名，可以观察到平均足部角度的轻微改善，对于一名参与者，平均膝盖角度略有改善。这些改善在峰值背屈、峰值跖屈或峰值膝关节屈曲时在4（circ）的范围内。结论所提出的方法可以实现对当前步态的直接适应。对SCI患者的初步首次测试表明，神经假体可以产生个人刺激模式。膝关节角度重置的敏感性、具有显著步态波动的参与者的计时问题以及自动ILC增益调谐是需要解决的剩余问题。随后，未来的研究应该比较改进，长期康复效果的神经假体，与传统的多通道FES神经假体。
Background FES (Functional Electrical Stimulation) neuroprostheses have long been a permanent feature in the rehabilitation and gait support of people who had a stroke or have a Spinal Cord Injury (SCI). Over time the well-known foot switch triggered drop foot neuroprosthesis, was extended to a multichannel full-leg support neuroprosthesis enabling improved support and rehabilitation. However, these neuroprostheses had to be manually tuned and could not adapt to the persons' individual needs. In recent research, a learning controller was added to the drop foot neuroprosthesis, so that the full stimulation pattern during the swing phase could be adapted by measuring the joint angles of previous steps. Methods The aim of this research is to begin developing a learning full-leg supporting neuroprosthesis, which controls the antagonistic muscle pairs for knee flexion and extension, as well as for ankle joint dorsi- and plantarflexion during all gait phases. A method was established that allows a continuous assessment of knee and foot joint angles with every step. This method can warp the physiological joint angles of healthy subjects to match the individual pathological gait of the subject and thus allows a direct comparison of the two. A new kind of Iterative Learning Controller (ILC) is proposed which works independent of the step duration of the individual and uses physiological joint angle reference bands. Results In a first test with four people with an incomplete SCI, the results showed that the proposed neuroprosthesis was able to generate individually fitted stimulation patterns for three of the participants. The other participant was more severely affected and had to be excluded due to the resulting false triggering of the gait phase detection. For two of the three remaining participants, a slight improvement in the average foot angles could be observed, for one participant slight improvements in the averaged knee angles. These improvements where in the range of 4(circ)at the times of peak dorsiflexion, peak plantarflexion, or peak knee flexion. Conclusions Direct adaptation to the current gait of the participants could be achieved with the proposed method. The preliminary first test with people with a SCI showed that the neuroprosthesis can generate individual stimulation patterns. The sensitivity to the knee angle reset, timing problems in participants with significant gait fluctuations, and the automatic ILC gain tuning are remaining issues that need be addressed. Subsequently, future studies should compare the improved, long-term rehabilitation effects of the here presented neuroprosthesis, with conventional multichannel FES neuroprostheses.