Lakshminarayanan Kishor, Shah Rakshit, Daulat Sohail R, Moodley Viashen, Yao Yifei, Sengupta Puja, Ramu Vadivelan, Madathil Deepa
Neuro-Rehabilitation Lab, Department of Sensors and Biomedical Engineering, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
Department of Chemical and Biomedical Engineering, Cleveland State University, Cleveland, OH 44115, USA.
Brain Sci. 2023 Apr 13;13(4):656. doi: 10.3390/brainsci13040656.
: The purpose of this study was to investigate the cortical activity and digit classification performance during tactile imagery (TI) of a vibratory stimulus at the index, middle, and thumb digits within the left hand in healthy individuals. Furthermore, the cortical activities and classification performance of the compound TI were compared with similar compound motor imagery (MI) with the same digits as TI in the same subjects. Twelve healthy right-handed adults with no history of upper limb injury, musculoskeletal condition, or neurological disorder participated in the study. The study evaluated the event-related desynchronization (ERD) response and brain-computer interface (BCI) classification performance on discriminating between the digits in the left-hand during the imagery of vibrotactile stimuli to either the index, middle, or thumb finger pads for TI and while performing a motor activity with the same digits for MI. A supervised machine learning technique was applied to discriminate between the digits within the same given limb for both imagery conditions. Both TI and MI exhibited similar patterns of ERD in the alpha and beta bands at the index, middle, and thumb digits within the left hand. While TI had significantly lower ERD for all three digits in both bands, the classification performance of TI-based BCI (77.74 ± 6.98%) was found to be similar to the MI-based BCI (78.36 ± 5.38%). The results of this study suggest that compound tactile imagery can be a viable alternative to MI for BCI classification. The study contributes to the growing body of evidence supporting the use of TI in BCI applications, and future research can build on this work to explore the potential of TI-based BCI for motor rehabilitation and the control of external devices.
本研究的目的是调查健康个体左手食指、中指和拇指在振动刺激的触觉意象（TI）过程中的皮层活动和手指分类表现。此外，还将复合TI的皮层活动和分类表现与同一受试者中与TI相同手指的类似复合运动意象（MI）进行了比较。12名无上肢损伤、肌肉骨骼疾病或神经系统疾病史的健康右利手成年人参与了本研究。该研究评估了在对食指、中指或拇指指腹进行振动触觉刺激的意象过程中以及在对相同手指进行运动活动以进行MI时，左手手指辨别方面的事件相关去同步化（ERD）反应和脑机接口（BCI）分类表现。应用监督机器学习技术来区分两种意象条件下同一给定肢体中的手指。TI和MI在左手食指、中指和拇指的α和β频段均表现出相似的ERD模式。虽然TI在两个频段中所有三个手指的ERD均显著较低，但基于TI的BCI的分类表现（77.74±6.98%）与基于MI的BCI（78.36±5.38%）相似。本研究结果表明，复合触觉意象可作为MI用于BCI分类的可行替代方案。该研究为支持在BCI应用中使用TI的越来越多的证据做出了贡献，未来的研究可以在此基础上探索基于TI的BCI在运动康复和外部设备控制方面的潜力。
