Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain-computer interface to a virtual reality avatar.
Gait adaptation to visual kinematic perturbations using a real-time closed-loop brain-computer interface to a virtual reality avatar.
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DOI：
10.1088/1741-2560/13/3/036006
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发表时间：
2016-06
影响因子：
4
通讯作者：
Contreras-Vidal JL
中科院分区：
文献类型：
--
作者：
Luu TP;He Y;Brown S;Nakagame S;Contreras-Vidal JL
人类双足运动的控制引起了用于步态康复的下半身脑机接口（BCIs）领域的极大兴趣。虽然闭环 BCI 系统用于控制下半身外骨骼的可行性最近已被证明，但在 BCI 虚拟现实 (BCI-VR) 环境中对人类步态进行多日闭环神经解码尚未得到证实。当由于医疗条件、成本、可及性、可用性或患者偏好而不需要可穿戴机器人时，BCI-VR 系统为运动康复提供了有价值的替代方案。在这项研究中，我们提出了一种实时闭环脑机接口，可以在跑步机行走期间从头皮脑电图（EEG）中解码下肢关节角度，以控制虚拟环境中的行走化身。脑电图 Delta 波段（0.1 – 3 Hz）的慢皮层电位振幅波动用于预测；因此，EEG 特征对应于 Delta 频带中的时域调幅 (AM) 电位。还引入了导致虚拟人物行走步态模式不对称的虚拟运动扰动，以使用闭环 BCI-VR 系统在八天内研究步态适应。我们的结果证明了使用闭环脑机接口来学习在正常和改变的视觉运动扰动下控制行走化身的可行性，这涉及皮质适应。所有受试者实时 BCI 的平均解码精度（皮尔逊 r 值）从第 1 天的（髋部：0.18 ± 0.31；膝部：0.23 ± 0.33；踝部：0.14 ± 0.22）增加到（髋部：0.40 ± 0.24；膝部：0.55 ± 0.20；踝部： 0.29 ± 0.22）第 8 天。这些发现对 开发基于实时闭环脑电图的 BCI-VR 系统，用于中风后的步态康复，并了解闭环 BCI-VR 系统引起的皮质可塑性。
The control of human bipedal locomotion is of great interest to the field of lower-body brain computer interfaces (BCIs) for gait rehabilitation. While the feasibility of closed-loop BCI systems for the control of a lower body exoskeleton has been recently shown, multi-day closed-loop neural decoding of human gait in a BCI virtual reality (BCI-VR) environment has yet to be demonstrated. BCI-VR systems provide valuable alternatives for movement rehabilitation when wearable robots are not desirable due to medical conditions, cost, accessibility, usability, or patient preferences. In this study, we propose a real-time closed-loop BCI that decodes lower limb joint angles from scalp electroencephalography (EEG) during treadmill walking to control a walking avatar in a virtual environment. Fluctuations in the amplitude of slow cortical potentials of EEG in the delta band (0.1 – 3 Hz) were used for prediction; thus, the EEG features correspond to time-domain amplitude modulated (AM) potentials in the delta band. Virtual kinematic perturbations resulting in asymmetric walking gait patterns of the avatar were also introduced to investigate gait adaptation using the closed-loop BCI-VR system over a period of eight days. Our results demonstrate the feasibility of using a closed-loop BCI to learn to control a walking avatar under normal and altered visuomotor perturbations, which involved cortical adaptations. The average decoding accuracies (Pearson’s r values) in real-time BCI across all subjects increased from (Hip: 0.18 ± 0.31; Knee: 0.23 ± 0.33; Ankle: 0.14 ± 0.22) on Day 1 to (Hip: 0.40 ± 0.24; Knee: 0.55 ± 0.20; Ankle: 0.29 ± 0.22) on Day 8. These findings have implications for the development of a real-time closed-loop EEG-based BCI-VR system for gait rehabilitation after stroke and for understanding cortical plasticity induced by a closed-loop BCI-VR system.
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影响因子：
5.1
作者：
Bruetsch, Karin;Schuler, Tabea;Meyer-Heim, Andreas
通讯作者：
Meyer-Heim, Andreas
影响因子：
2.5
作者：
Gwin, Joseph T.;Gramann, Klaus;Ferris, Daniel P.
通讯作者：
Ferris, Daniel P.
影响因子：
5.1
作者：
King CE;Wang PT;Chui LA;Do AH;Nenadic Z
通讯作者：
Nenadic Z
DOI：
10.1016/s0003-9993(03)00030-3
发表时间：
2003-08-01
影响因子：
4.3
作者：
Hsu, AL;Tang, PF;Jan, MH
通讯作者：
Jan, MH
影响因子：
4.2
作者：
Franceschini, Marco;Ceravolo, Maria Gabriella;Sale, Patrizio
通讯作者：
Sale, Patrizio