Baberwal Sonal Santosh, Magre Luz Alejandra, Gunawardhana K R Sanjaya D, Parkinson Michael, Ward Tomas, Coyle Shirley
Dublin City University, School of Electronic Engineering, Dublin City University, D09Y074 Dublin, Ireland, Dublin, D09Y074, IRELAND.
Dublin City University, School of Electronic Engineering, Dublin City University, D09Y074 Dublin, Ireland, Dublin, Dublin, D09Y074, IRELAND.
J Neural Eng. 2024 Sep 4. doi: 10.1088/1741-2552/ad775e.
Training plays a significant role in motor imagery (MI), particularly in applications such as Motor Imagery-based Brain-Computer Interface (MIBCI) systems and rehabilitation systems. Previous studies have investigated the intricate relationship between cues and MI signals. However, the medium of presentation still remains an emerging area to be explored, as possible factors to enhance Motor Imagery signals.. Approach: We hypothesise that the medium used for cue presentation can significantly influence both performance and training outcomes in MI tasks. To test this hypothesis, we designed and executed an experiment implementing no- feedback MI. Our investigation focused on three distinct cue presentation mediums -audio, screen, and virtual reality(VR) headsets-all of which have potential implications for BCI use in the Activities of Daily Lives. Main Results: The results of our study uncovered notable variations in MI signals depending on the medium of cue presentation, where the analysis is based on 3 EEG channels. To substantiate our findings, we employed a comprehensive approach, utilizing various evaluation metrics including Event- Related Synchronisation(ERS)/Desynchronisation(ERD), Feature Extraction (using Recursive Feature Elimination (RFE)), Machine Learning methodologies (using Ensemble Learning), and participant Questionnaires. All the approaches signify that Motor Imagery signals are enhanced when presented in VR, followed by audio, and lastly screen. Applying a Machine Learning approach across all subjects, the mean cross-validation accuracy (Mean ± Std. Error) was 69.24 ± 3.12, 68.69 ± 3.3 and 66.1±2.59 when for the VR, audio-based, and screen-based instructions respectively. Significance: This multi-faceted exploration provides evidence to inform MI- based BCI design and advocates the incorporation of different mediums into the design of MIBCI systems, experimental setups, and user studies. The influence of the medium used for cue presentation may be applied to develop more effective and inclusive MI applications in the realm of human-computer interaction and rehabilitation.
训练在运动想象（MI）中起着重要作用，特别是在基于运动想象的脑机接口（MIBCI）系统和康复系统等应用中。以往的研究已经探讨了线索与MI信号之间的复杂关系。然而，作为增强运动想象信号的可能因素，呈现媒介仍然是一个有待探索的新兴领域。
我们假设用于线索呈现的媒介会显著影响MI任务的表现和训练结果。为了验证这一假设，我们设计并实施了一项无反馈MI实验。我们的研究重点关注三种不同的线索呈现媒介——音频、屏幕和虚拟现实（VR）头戴式设备——所有这些对BCI在日常生活活动中的应用都有潜在影响。
我们的研究结果发现，根据线索呈现媒介的不同，MI信号存在显著差异，分析基于3个脑电图通道。为了证实我们的发现，我们采用了一种综合方法，使用了各种评估指标，包括事件相关同步（ERS）/去同步（ERD）、特征提取（使用递归特征消除（RFE））、机器学习方法（使用集成学习）和参与者问卷。所有方法都表明，运动想象信号在VR中呈现时增强，其次是音频，最后是屏幕。对所有受试者应用机器学习方法，当分别采用基于VR、音频和屏幕的指令时，平均交叉验证准确率（平均值±标准误差）分别为69.24±3.12、68.69±3.3和66.1±2.59。
这一多方面的探索为基于MI的BCI设计提供了证据，并提倡将不同媒介纳入MIBCI系统、实验设置和用户研究的设计中。用于线索呈现的媒介的影响可应用于在人机交互和康复领域开发更有效和包容性更强的MI应用程序。
