Biological System Modeling Laboratory, Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran.
Sci Rep. 2024 Aug 14;14(1):18846. doi: 10.1038/s41598-024-69919-x.
Performing mathematical calculations is a cognitive activity that can affect biological signals. This study aims to examine the changes in electroencephalogram (EEG) and electrocardiogram (ECG) signals of 36 healthy subjects during the performance of arithmetic tasks. To process EEG signals in different frequency bands, the energy and entropy of entropy (EoE) were extracted from the power spectrum and phase spectrum, respectively. Statistical analysis was conducted to determine meaningful features. These features were sent into support vector machine (SVM) and multi-layer perception (MLP) classifiers to assess their capability in separating math and rest classes. Results indicated the highest classification accuracy of 98.4% for classifying good counters in math and rest state using the MLP method. Based on the majority of features selected for each EEG channel, discriminative brain areas were identified. Analyzing EEG signals proved that math calculation may have multiple influences on various parts of the brain. By comparing good counters' brain activities to those in a resting state, prominent changes were observed in the F, C, T, T, P, and O areas. However, O and O channels showed significant changes in the brain of bad counters compared to the resting state. Considering ECG signals also demonstrated that during math calculation the number of heart rates per minute surpasses the rest state. These alterations can occur due to cognitive abilities or emotional processes which were observed to be prominent in subjects who performed more accurate calculations.
进行数学计算是一种认知活动，可能会影响生物信号。本研究旨在观察 36 名健康受试者在进行算术任务时脑电图（EEG）和心电图（ECG）信号的变化。为了在不同的频带中处理 EEG 信号，从功率谱和相位谱中分别提取了能量和熵的熵（EoE）。进行了统计分析以确定有意义的特征。这些特征被送入支持向量机（SVM）和多层感知器（MLP）分类器，以评估它们在区分数学和休息类别的能力。结果表明，使用 MLP 方法对数学和休息状态下的优秀计数者进行分类的准确率最高为 98.4％。基于为每个 EEG 通道选择的大多数特征，确定了具有判别力的大脑区域。分析 EEG 信号表明，数学计算可能对大脑的各个部位产生多种影响。通过将优秀计数者的大脑活动与休息状态进行比较，在 F、C、T、T、P 和 O 区域观察到明显的变化。然而，与休息状态相比，O 和 O 通道在表现不佳的计数者的大脑中显示出显著的变化。考虑到心电图信号也表明，在数学计算期间，每分钟的心率超过了休息状态。这些变化可能是由于认知能力或情绪过程引起的，在那些进行更准确计算的受试者中观察到这些变化更为明显。
