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关于混合脑机接口的一个实例:结合光学和电学模式可提高准确性。

A case for hybrid BCIs: combining optical and electrical modalities improves accuracy.

作者信息

Almajidy Rand Kasim, Mottaghi Soheil, Ajwad Asmaa A, Boudria Yacine, Mankodiya Kunal, Besio Walter, Hofmann Ulrich G

机构信息

Faculty of Medicine, University of Freiburg, Freiburg im Breisgau, Germany.

Section for Neuroelectronic Systems, Department of Neurosurgery, Medical Center University of Freiburg, Freiburg im Breisgau, Germany.

出版信息

Front Hum Neurosci. 2023 Jun 7;17:1162712. doi: 10.3389/fnhum.2023.1162712. eCollection 2023.

Abstract

Near-infrared spectroscopy (NIRS) is a promising research tool that found its way into the field of brain-computer interfacing (BCI). BCI is crucially dependent on maximized usability thus demanding lightweight, compact, and low-cost hardware. We designed, built, and validated a hybrid BCI system incorporating one optical and two electrical modalities ameliorating usability issues. The novel hardware consisted of a NIRS device integrated with an electroencephalography (EEG) system that used two different types of electrodes: Regular gelled gold disk electrodes and tri-polar concentric ring electrodes (TCRE). BCI experiments with 16 volunteers implemented a two-dimensional motor imagery paradigm in off- and online sessions. Various non-canonical signal processing methods were used to extract and classify useful features from EEG, tEEG (EEG through TCRE electrodes), and NIRS. Our analysis demonstrated evidence of improvement in classification accuracy when using the TCRE electrodes compared to disk electrodes and the NIRS system. Based on our synchronous hybrid recording system, we could show that the combination of NIRS-EEG-tEEG performed significantly better than either single modality only.

摘要

近红外光谱技术(NIRS)是一种很有前景的研究工具,已进入脑机接口(BCI)领域。脑机接口严重依赖于最大化的可用性,因此需要轻便、紧凑且低成本的硬件。我们设计、构建并验证了一种混合脑机接口系统,该系统结合了一种光学模式和两种电学模式,改善了可用性问题。这种新型硬件由一个与脑电图(EEG)系统集成的近红外光谱设备组成,该脑电图系统使用两种不同类型的电极:常规凝胶金盘电极和三极同心环电极(TCRE)。对16名志愿者进行的脑机接口实验在离线和在线环节中实施了二维运动想象范式。使用了各种非传统信号处理方法从脑电图、经三极同心环电极脑电图(tEEG,即通过三极同心环电极采集的脑电图)和近红外光谱中提取并分类有用特征。我们的分析表明,与盘状电极和近红外光谱系统相比,使用三极同心环电极时分类准确率有提高的迹象。基于我们的同步混合记录系统,我们可以证明近红外光谱 - 脑电图 - 经三极同心环电极脑电图的组合表现明显优于任何单一模式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27a5/10282188/d2116e3e1c9c/fnhum-17-1162712-g001.jpg

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