Assessment of motor imagery in gamma band using a lower limb exoskeleton
Assessment of motor imagery in gamma band using a lower limb exoskeleton
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使用下肢外骨骼评估伽玛波段运动想象
DOI：
10.1109/smc.2019.8914483
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
J. Azorín
中科院分区：
文献类型：
--
作者：
M. Ortíz;E. Iáñez;J. A. Gaxiola;A. Kilicarslan;J. Contreras;J. Azorín
脑机接口（BMI）与动力外骨骼的结合使用可以帮助下肢残疾患者再次行走。这些神经机器人系统通常基于运动想象，但它们的性能可能会受到缺乏用户参与任务或由于多任务处理而产生的认知负荷的影响。本论文展示了一种基于伽马谱带的新型算法，使用斯托克韦尔变换和一组平滑滤波器，来评估BMI-Rex外骨骼系统使用期间运动想象的质量并改进其解码。在一个伪在线的情况下计算的结果表明，具有很低的误报率的高精度。
The use of a brain-machine interface (BMI) in combination with powered exoskeletons can assist patients with lower limb disabilities to walk again. These neurorobotic systems are commonly based on motor imagery, but their performance may suffer from lack of user engagement in the task or from cognitive load due to multi-tasking. The present paper shows a novel algorithm based on the gamma spectral band, using the Stockwell transform and a set of smoothing filters, to assess the quality of and improve the decoding of motor imagery during the use of a BMI-Rex exoskeleton system. The results computed in a pseudo-online scenario reveal a high accuracy with a very low false positive ratio.