Felton E A, Radwin R G, Wilson J A, Williams J C
Department of Biomedical Engineering, University of Wisconsin-Madison, 53706, USA.
J Neural Eng. 2009 Oct;6(5):056002. doi: 10.1088/1741-2560/6/5/056002. Epub 2009 Aug 21.
A brain-computer interface (BCI) is a communication system that takes recorded brain signals and translates them into real-time actions, in this case movement of a cursor on a computer screen. This work applied Fitts' law to the evaluation of performance on a target acquisition task during sensorimotor rhythm-based BCI training. Fitts' law, which has been used as a predictor of movement time in studies of human movement, was used here to determine the information transfer rate, which was based on target acquisition time and target difficulty. The information transfer rate was used to make comparisons between control modalities and subject groups on the same task. Data were analyzed from eight able-bodied and five motor disabled participants who wore an electrode cap that recorded and translated their electroencephalogram (EEG) signals into computer cursor movements. Direct comparisons were made between able-bodied and disabled subjects, and between EEG and joystick cursor control in able-bodied subjects. Fitts' law aptly described the relationship between movement time and index of difficulty for each task movement direction when evaluated separately and averaged together. This study showed that Fitts' law can be successfully applied to computer cursor movement controlled by neural signals.
脑机接口(BCI)是一种通信系统,它获取记录的脑信号并将其转化为实时动作,在本案例中是计算机屏幕上光标的移动。这项工作将菲茨定律应用于基于感觉运动节律的脑机接口训练期间目标获取任务的性能评估。菲茨定律在人体运动研究中一直被用作运动时间的预测指标,在此用于确定基于目标获取时间和目标难度的信息传递速率。信息传递速率用于在相同任务上对控制方式和受试者组进行比较。分析了来自8名身体健全和5名运动功能障碍参与者的数据,这些参与者佩戴电极帽,将他们的脑电图(EEG)信号记录并转化为计算机光标移动。对身体健全和残疾受试者之间,以及身体健全受试者中脑电图和操纵杆光标控制之间进行了直接比较。当分别评估并求平均值时,菲茨定律恰当地描述了每个任务运动方向的运动时间与难度指数之间的关系。这项研究表明,菲茨定律可以成功应用于由神经信号控制的计算机光标移动。