Likitlersuang Jirapat, Koh Ryan, Gong Xinyi, Jovanovic Lazar, Bolivar-Tellería Isabel, Myers Matthew, Zariffa José, Márquez-Chin César
Toronto Rehabilitation Institute - University Health Network, Toronto, Canada.
Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Canada.
Top Spinal Cord Inj Rehabil. 2018 Summer;24(3):265-274. doi: 10.1310/sci2403-265.
Functional electrical stimulation therapy (FEST) is a promising intervention for the restoration of upper extremity function after cervical spinal cord injury (SCI). This study describes and evaluates a novel FEST system designed to incorporate voluntary movement attempts and massed practice of functional grasp through the use of brain-computer interface (BCI) and computer vision (CV) modules. An EEG-based BCI relying on a single electrode was used to detect movement initiation attempts. A CV system identified the target object and selected the appropriate grasp type. The required grasp type and trigger command were sent to an FES stimulator, which produced one of four multichannel muscle stimulation patterns (precision, lateral, palmar, or lumbrical grasp). The system was evaluated with five neurologically intact participants and one participant with complete cervical SCI. An integrated BCI-CV-FES system was demonstrated. The overall classification accuracy of the CV module was 90.8%, when selecting out of a set of eight objects. The average latency for the BCI module to trigger the movement across all participants was 5.9 ± 1.5 seconds. For the participant with SCI alone, the CV accuracy was 87.5% and the BCI latency was 5.3 ± 9.4 seconds. BCI and CV methods can be integrated into an FEST system without the need for costly resources or lengthy setup times. The result is a clinically relevant system designed to promote voluntary movement attempts and more repetitions of varied functional grasps during FEST.
功能性电刺激疗法(FEST)是一种很有前景的干预方法,用于恢复颈脊髓损伤(SCI)后上肢的功能。本研究描述并评估了一种新型FEST系统,该系统旨在通过使用脑机接口(BCI)和计算机视觉(CV)模块,纳入自主运动尝试和功能性抓握的集中练习。基于脑电图的单电极BCI用于检测运动起始尝试。一个CV系统识别目标物体并选择合适的抓握类型。所需的抓握类型和触发命令被发送到一个FES刺激器,该刺激器产生四种多通道肌肉刺激模式之一(精确抓握、侧方抓握、掌侧抓握或蚓状肌抓握)。该系统在5名神经功能正常的参与者和1名完全性颈SCI参与者中进行了评估。展示了一个集成的BCI-CV-FES系统。当从一组8个物体中进行选择时,CV模块的总体分类准确率为90.8%。所有参与者中BCI模块触发运动的平均延迟为5.9±1.5秒。对于仅患有SCI的参与者,CV准确率为87.5%,BCI延迟为5.3±9.4秒。BCI和CV方法可以集成到一个FEST系统中,无需昂贵的资源或冗长的设置时间。结果是一个与临床相关的系统,旨在促进自主运动尝试,并在FEST期间增加各种功能性抓握的重复次数。