Wang Zhuang, Liu Yuan, Huang Shuaifei, Qiu Shiyin, Zhang Yujian, Huang Huimin, An Xingwei, Ming Dong
IEEE J Biomed Health Inform. 2024 Dec;28(12):7078-7089. doi: 10.1109/JBHI.2024.3452701. Epub 2024 Dec 5.
Adding supernumerary robotic limbs (SRLs) to humans and controlling them directly through the brain are main goals for movement augmentation. However, it remains uncertain whether neural patterns different from the traditional inherent limbs motor imagery (MI) can be extracted, which is essential for high-dimensional control of external devices. In this work, we established a MI neo-framework consisting of novel supernumerary robotic sixth-finger MI (SRF-MI) and traditional right-hand MI (RH-MI) paradigms and validated the distinctness of EEG response patterns between two MI tasks for the first time. Twenty-four subjects were recruited for this experiment involving three mental tasks. Event-related spectral perturbation was adopted to supply details about event-related desynchronization (ERD). Activation region, intensity and response time (RT) of ERD were compared between SRF-MI and RH-MI tasks. Three classical classification algorithms were utilized to verify the separability between different mental tasks. And genetic algorithm aims to select optimal combination of channels for neo-framework. A bilateral sensorimotor and prefrontal modulation was found during the SRF-MI task, whereas in RH-MI only contralateral sensorimotor modulation was exhibited. The novel SRF-MI paradigm enhanced ERD intensity by a maximum of 117% in prefrontal area and 188% in the ipsilateral somatosensory-association cortex. And, a global decrease of RT was exhibited during SRF-MI tasks compared to RH-MI. Classification results indicate well separable performance among different mental tasks (88.1% maximum for 2-class and 88.2% maximum for 3-class). This work demonstrated the difference between the SRF-MI and RH-MI paradigms, widening the control bandwidth of the BCI system.
给人类增加多余的机器人肢体(SRLs)并通过大脑直接控制它们是运动增强的主要目标。然而,与传统固有肢体运动想象(MI)不同的神经模式是否能够被提取仍不确定,而这对于外部设备的高维控制至关重要。在这项工作中,我们建立了一个由新型多余机器人第六指运动想象(SRF-MI)和传统右手运动想象(RH-MI)范式组成的MI新框架,并首次验证了两个MI任务之间脑电图反应模式的差异性。本实验招募了24名受试者,涉及三项心理任务。采用事件相关频谱扰动来提供有关事件相关去同步化(ERD)的详细信息。比较了SRF-MI和RH-MI任务之间ERD的激活区域、强度和反应时间(RT)。利用三种经典分类算法来验证不同心理任务之间的可分离性。遗传算法旨在为新框架选择最佳通道组合。在SRF-MI任务期间发现了双侧感觉运动和前额叶调制,而在RH-MI中仅表现出对侧感觉运动调制。新型SRF-MI范式使前额叶区域的ERD强度最大增强了117%,同侧体感联合皮层增强了188%。并且,与RH-MI相比,SRF-MI任务期间RT出现了整体下降。分类结果表明不同心理任务之间具有良好的可分离性能(二分类最高为88.1%,三分类最高为88.2%)。这项工作证明了SRF-MI和RH-MI范式之间的差异,拓宽了脑机接口系统的控制带宽。