Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:203-207. doi: 10.1109/EMBC48229.2022.9871411.
Improving user performances is one of the major issues for Motor Imagery (MI) - based BCI control. MI-BCIs exploit the modulation of sensorimotor rhythms (SMR) over the motor and sensorimotor cortices to discriminate several mental states and enable user interaction. Such modulations are known as Event-Related Desynchronization (ERD) and Synchronization (ERS), coming from the mu (7-13 Hz) and beta (15-30 Hz) frequency bands. This kind of BCI opens up promising fields, particularly to control assistive technologies, for sport training or even for post-stroke motor rehabilitation. However, MI - BCIs remain barely used outside laboratories, notably due to their lack of robustness and usability (15 to 30% of users seem unable to gain control of an MI-BCI). One way to increase user performance would be to better understand the relationships between user traits and ERD/ERS modulations underlying BCI performance. Therefore, in this article we analyzed how cerebral motor patterns underlying MI tasks (i.e., ERDs and ERSs) are modulated depending (i) on nature of the task (i.e., right-hand MI and left-hand MI), (ii) the session during which the task was performed (i.e., calibration or user training) and (iii) on the characteristics of the user (e.g., age, gender, manual activity, personality traits) on a large MI-BCI data base of N=75 participants. One of the originality of this study is to combine the investigation of human factors related to the user's traits and the neurophysiological ERD modulations during the MI task. Our study revealed for the first time an association between ERD and self-control from the 16PF5 questionnaire.
提高用户表现是基于运动想象 (MI) 的脑机接口 (BCI) 控制的主要问题之一。MI-BCIs 利用运动和感觉运动皮层上的感觉运动节律 (SMR) 的调制来区分几种心理状态并实现用户交互。这种调制被称为事件相关去同步 (ERD) 和同步 (ERS),来自 mu (7-13 Hz) 和 beta (15-30 Hz) 频段。这种 BCI 开辟了有前途的领域,特别是用于控制辅助技术、运动训练甚至中风后的运动康复。然而,MI-BCI 除了实验室之外几乎没有被使用,主要是因为它们缺乏稳健性和可用性(15%到 30%的用户似乎无法控制 MI-BCI)。提高用户表现的一种方法是更好地理解用户特征与 BCI 表现背后的 ERD/ERS 调制之间的关系。因此,在本文中,我们分析了 MI 任务(即 ERDs 和 ERSs)下的大脑运动模式是如何根据(i)任务的性质(即右手 MI 和左手 MI)、(ii)执行任务的会话(即校准或用户训练)以及(iii)用户的特征(例如年龄、性别、手动活动、个性特征)进行调制的,这是在一个包含 75 名参与者的大型 MI-BCI 数据库上进行的。这项研究的一个创新之处在于将与用户特征相关的人类因素与 MI 任务期间的神经生理 ERD 调制结合起来进行研究。我们的研究首次揭示了 ERD 与 16PF5 问卷中自我控制之间的关联。