论文标题
现成的低成本可穿戴EEG耳机的校准用于现场研究
Calibration of off-the-shelf low-cost wearable EEG headset for application in field studies
论文作者
论文摘要
脑电图（EEG）是全球神经认知研究中不可或缺的工具。但是，研究级EEG（32/64CH）系统非常昂贵，并且具有繁琐的设置，该设置为临床使用而设计，不适合实验室外的野外研究环境。此外，脑电图的长时间设置可能会使那些不安的受试者（例如儿童或老年人）吓倒。已经提出了现成的，低成本的脑电图设备（LCDE）作为有希望的选择。但是，LCDE中的少量电极限制了检测头皮区域，将LCDE的效用仅减少到基于扫描的脑叶的特定认知任务中。本文提出了一种用于校准LCDE（例如DREEM头带）的新方法，以识别LCDE可能适合的特定认知任务。该方法涉及使用LCDE与EEG样信号（使用BESA Simulator软件）对录制数据进行比较分析，通过将偶极子嵌入脑叶中。模拟的头皮活性和相应的源分析有助于确定LCDE设备扫描的大脑的近似区域。在进一步的比较分析时，使用脑电源分析（BESA软件）本地化的脑叶来源有助于表征LCDE的认知任务。主要发现得出了可以使用各种LCDE进行心理学研究的列表，该研究能够替换内部和外部LAB设置中的传统且昂贵的湿EEG系统。
Electroencephalography (EEG) is an integral tool in neurocognitive research worldwide. However, research grade EEG (32/64ch) systems are expensive and have cumbersome setup designed for clinical usage not suited for rugged environment of field-studies outside lab. Further, the long setup-time of EEG can be intimidating to those who are restless subjects e.g., children or elderly. Off-the-shelf, low-cost, dry EEG devices (LCDE) have been proposed as promising options. However, small number of electrodes in LCDE limit the detection scalp-area reducing the utility of an LCDE only to a specific set of cognitive tasks based on the brain lobe scanned. This paper proposes a novel methodology for calibration of an LCDE (e.g., DREEM Headband) to identify the specific class of cognitive tasks a LCDE is likely suited for. The methodology involves comparative analysis of the recorded data using LCDE with EEG-like signals simulated (using BESA Simulator software) by embedding dipole in a brain lobe. The simulated scalp activity and corresponding source analysis helps identify the approximate regions of brain scanned by the LCDE device. On further comparative analysis of brain lobes source localized using Brain Electrical Source Analysis (BESA software) helps characterize LCDE for cognitive tasks. The major findings conclude a list of psychological studies which can be performed using various LCDE, capable of replacing traditional and expensive wet EEG systems in both inside and outside-lab settings.
