Brain-Computer interface control of stepping from invasive electrocorticography upper-limb motor imagery in a patient with quadriplegia.
Brain-Computer interface control of stepping from invasive electrocorticography upper-limb motor imagery in a patient with quadriplegia.
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DOI：
10.3389/fnhum.2022.1077416
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发表时间：
2022
影响因子：
2.9
通讯作者：
中科院分区：
文献类型：
--
作者：
简介：大多数脊髓损伤（SCI）导致下肢瘫痪，从而减少截肢。使用脑机接口（BCI），患者可以使用驱动辅助设备的神经信号重新获得腿部控制。在这里，我们提出了一个案例的主题与植入皮层电图（ECoG）设备的颈椎脊髓损伤，并确定该系统是否能够在辅助步行机运动图像启动行走。研究方法：一名24岁的男性颈椎脊髓损伤患者（C5 ASIA A）在研究前在大脑的感觉运动手区域植入ECoG传感装置。受试者使用运动想象（MI）训练解码器分类感觉运动节律。随后进行了15次闭环试验，受试者每周在机器人辅助的重量支持跑步机上行走一小时，一至三次。我们评估了性能最佳的解码器随时间的稳定性，以通过解码上肢（UL）MI来启动在跑步机上行走。结果：在线袋装树分类器表现最好，在9周内平均准确率为84.15%。在整个闭环数据收集过程中，解码器精度保持稳定。讨论：这些结果表明，解码UL MI是一种可行的控制信号，用于下肢运动控制。设计用于上肢运动控制的侵入式BCI系统可以扩展用于控制仅上肢控制之外的系统。重要的是，所使用的解码器能够在几周内使用侵入性信号来准确地将MI与侵入性信号分类。需要更多的工作来确定UL MI和由此产生的下肢控制之间的长期后果。
Introduction: Most spinal cord injuries (SCI) result in lower extremities paralysis, thus diminishing ambulation. Using brain-computer interfaces (BCI), patients may regain leg control using neural signals that actuate assistive devices. Here, we present a case of a subject with cervical SCI with an implanted electrocorticography (ECoG) device and determined whether the system is capable of motor-imagery-initiated walking in an assistive ambulator. Methods: A 24-year-old male subject with cervical SCI (C5 ASIA A) was implanted before the study with an ECoG sensing device over the sensorimotor hand region of the brain. The subject used motor-imagery (MI) to train decoders to classify sensorimotor rhythms. Fifteen sessions of closed-loop trials followed in which the subject ambulated for one hour on a robotic-assisted weight-supported treadmill one to three times per week. We evaluated the stability of the best-performing decoder over time to initiate walking on the treadmill by decoding upper-limb (UL) MI. Results: An online bagged trees classifier performed best with an accuracy of 84.15% averaged across 9 weeks. Decoder accuracy remained stable following throughout closed-loop data collection. Discussion: These results demonstrate that decoding UL MI is a feasible control signal for use in lower-limb motor control. Invasive BCI systems designed for upper-extremity motor control can be extended for controlling systems beyond upper extremity control alone. Importantly, the decoders used were able to use the invasive signal over several weeks to accurately classify MI from the invasive signal. More work is needed to determine the long-term consequence between UL MI and the resulting lower-limb control.
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影响因子：
5.1
作者：
King CE;Wang PT;Chui LA;Do AH;Nenadic Z
通讯作者：
Nenadic Z
影响因子：
1.4
作者：
Gant, Katie;Guerra, Santiago;Prasad, Abhishek
通讯作者：
Prasad, Abhishek
影响因子：
2
作者：
Ang, Kai Keng;Chua, Karen Sui Geok;Guan, Cuntai
通讯作者：
Guan, Cuntai
DOI：
10.1080/2326263x.2013.876724
发表时间：
2014-01
期刊：
Brain computer interfaces (Abingdon, England)
影响因子：
--
作者：
Huggins JE;Guger C;Allison B;Anderson CW;Batista A;Brouwer AM;Brunner C;Chavarriaga R;Fried-Oken M;Gunduz A;Gupta D;Kübler A;Leeb R;Lotte F;Miller LE;Müller-Putz G;Rutkowski T;Tangermann M;Thompson DE
通讯作者：
Thompson DE
影响因子：
4.3
作者：
K端bler, A;Neumann, N;Birbaumer, NP
通讯作者：
Birbaumer, NP