MEFAR Dataset: Neurophysiological and Biosignal Data

The dataset was carefully generated with the purpose of investigating mental fatigue through the analysis of physiological signals. The signals that are included are as follows: Electroencephalography (EEG) is a technique utilized to assess the electrical activity of the brain. The blood volume pulse (BVP) is a measurement technique that records fluctuations in blood volume inside the peripheral blood vessels. Electrodermal activity (EDA) is a physiological measure that monitors variations in the electrical conductivity of the skin. The heart rate (HR) is data that measures the frequency of heartbeats within a given timeframe, typically expressed as the number of beats per minute. The temperature sensor is responsible for monitoring the body temperature of the participants. The 3-axis accelerometer (ACC) data quantifies the rate of change in velocity experienced by the individuals involved. Data was gathered from a sample of 23 individuals during both morning and evening sessions. The Chalder Fatigue Scale was employed in order to assess the levels of mental weariness among the participants. The scale utilized in this study offers a numerical score to each participant, which is determined based on their responses. A score of 12 or above on this scale is indicative of a positive mental fatigue condition. The dataset includes both unprocessed/raw and processed data. The term "raw data" pertains to unaltered recorded signals, whereas "processed data" generally includes signal preprocessing methods such as filtering, artifact removal, and feature extraction. The processed data comprises data that has been processed using various sampling frequencies, namely 1 Hz, 32 Hz, and 64 Hz. The operations encompass downsampling, midsampling, and upsampling. The datasets that have undergone processing are denoted as MEFAR_DOWN, MEFAR_MID, and MEFAR_UP, representing the treated data with downsampling, midsampling, and upsampling, respectively. Furthermore, comprehensive demographic data pertaining to the participants can be found in an Excel spreadsheet named "general_info." Maintaining the identity and privacy of participants is crucial in order to adhere to ethical requirements. This dataset can be shared among researchers that are interested in analyzing mental exhaustion, enabling them to conduct more investigations, develop algorithms, and validate their findings.

本数据集为探究精神疲劳而精心构建，核心研究方法为生理信号分析。所涵盖的生理信号如下：脑电图（Electroencephalography, EEG）是一种用于评估大脑电活动的技术；血容量脉冲（Blood Volume Pulse, BVP）是记录外周血管内血容量波动的测量技术；皮肤电活动（Electrodermal Activity, EDA）是监测皮肤电导率变化的生理指标；心率（Heart Rate, HR）是记录特定时段内心跳频率的数据，通常以每分钟心跳数为单位；体温传感器数据用于监测受试者的身体体温；三轴加速度计（3-axis accelerometer, ACC）数据用于量化受试者所经历的速度变化率。
本数据集的采集对象为23名受试者，采集时段覆盖晨间与晚间。研究采用查尔达疲劳量表（Chalder Fatigue Scale）评估受试者的精神疲劳程度，该量表通过受试者的作答为每名参与者生成量化评分，评分≥12分即判定为存在阳性精神疲劳症状。
本数据集包含未处理原始数据（raw data）与预处理后数据（processed data）两类。其中“raw data”指未经修改的原始记录信号；“processed data”通常涵盖滤波、伪影去除、特征提取等信号预处理流程。预处理后数据基于1 Hz、32 Hz、64 Hz三种不同采样频率生成，涉及下采样、中采样与上采样三类操作。三类预处理后的数据集分别命名为MEFAR_DOWN、MEFAR_MID与MEFAR_UP，分别对应经下采样、中采样与上采样处理的数据。
受试者的完整人口统计学信息可在名为"general_info"的Excel表格中查看。为遵循伦理规范，本数据集严格保障受试者的身份与隐私。本数据集可向致力于精神疲劳分析的研究人员开放共享，以支持相关算法开发、实验验证与拓展研究。

搜集汇总

背景与挑战

背景概述

MEFAR数据集是一个专注于精神疲劳研究的神经生理和生物信号数据集，包含23名参与者的多种生理信号（EEG、BVP等）的原始和处理版本（1Hz、32Hz、64Hz采样频率）。数据集还提供详细的人口统计信息，遵循CC BY 4.0许可，适合用于精神疲劳分析和算法开发。