A Synergetic Voluntary Control for Exoskeleton based on Spinal Cord Mapping of Peripheral Bioelectric Activity
A Synergetic Voluntary Control for Exoskeleton based on Spinal Cord Mapping of Peripheral Bioelectric Activity
复制标题
基于外周生物电活动脊髓图谱的外骨骼协同自主控制
DOI：
10.1109/iros.2018.8593695
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Suzuki Kenji
中科院分区：
文献类型：
--
作者：
Ishikawa Shotaro;Kadone Hideki;Suzuki Kenji
步行康复必须基于自主运动意图进行，为此，研究了基于自主意图的外骨骼机器人控制方法的发展。本研究提出一种外骨骼机器人控制的方法，以估计脊髓损伤（SCI）后失去的下肢肌肉活动。该方法基于剩余肌肉活动的脊髓映射及其与从健康参与者获得的映射的匹配，考虑在步行运动期间全身的肌肉协同作用。通过在脊髓图水平上实施匹配程序并基于诊断结合可靠和不可靠的脊髓水平的信息，该方法具有为SCI患者提供最大自主运动的潜力。我们报告了一个分析的协同作用的全身肌肉活动在步行和脊髓映射使用非负矩阵分解和计算的转换矩阵估计预期的下肢肌肉活动，从剩余的脊髓活动。所提出的方法使用的混合辅助肢体和步行实验与健康参与者的右腿的实施也有报道。
Walking rehabilitation must be performed based on voluntary motion intention, and for this purpose, the development of a control method for an exoskeleton robot based on voluntary intention is investigated. This study proposes a method of exoskeleton robot control to estimate the voluntary lower limb muscle activities lost after a spinal cord injury (SCI). This method is based on the spinal cord mapping of the remaining muscle activities and its matching to the one obtained from healthy participants considering the muscle synergy of the whole body during the walking motion. By implementing the matching procedure at the spinal cord map level and incorporating information of reliable and unreliable spinal cord levels based on a diagnosis, the method has the potential to provide a maximally voluntary locomotion for people with SCI. We report an analysis of the synergy of the whole-body muscle activity during walking and its spinal cord mapping using non-negative matrix factorization and the computation of the transformation matrix to estimate the intended lower limb muscle activity from the remaining spinal cord activity. The implementation of the proposed method using the right leg of the hybrid assistive limb and walking experiments with a healthy participant are also reported.
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影响因子：
3.2
作者：
Behmran, AL;Harkema, SJ
通讯作者：
Harkema, SJ
影响因子：
1.7
作者：
Kubota, Shigeki;Abet, Tetsuya;Yamazaki, Masashi
通讯作者：
Yamazaki, Masashi
影响因子：
3.7
作者：
Sylos-Labini F;Ivanenko YP;Maclellan MJ;Cappellini G;Poppele RE;Lacquaniti F
通讯作者：
Lacquaniti F
影响因子：
2.5
作者：
Ivanenko, YP;Poppele, RE;Lacquaniti, F
通讯作者：
Lacquaniti, F
影响因子：
3.4
作者：
Ivanenko, Y. P.;Cappellini, G.;Lacquaniti, F.
通讯作者：
Lacquaniti, F.