SignalFlowEEG Example Data

The SignalFlowEEG Example Data dataset contains sample EEG recordings that demonstrate the capabilities and usage of the SignalFlowEEG Python package. This package provides a comprehensive set of tools for processing, analyzing, and visualizing electroencephalography (EEG) data, with a focus on neuroscience research applications.The example dataset includes EEG recordings from various paradigms:Resting-state EEG: A 5-minute recording where the subject relaxed with eyes closed.Auditory chirp stimulation: EEG recorded while the subject listened to chirp sounds with varying frequencies.Visual evoked potentials: EEG recorded as the subject viewed checkerboard pattern stimuli to elicit visual responses.These recordings were collected at the Cincinnati Children's Hospital Medical Center and are made available for educational and testing purposes.SignalFlowEEG builds upon MNE-Python, a popular open-source library for EEG analysis, and offers additional functionality tailored for clinical research workflows. This example dataset allows users to explore SignalFlowEEG's features and gain hands-on experience analyzing EEG data with this powerful Python package.The dataset consists of .set files, a format used by the EEGLAB toolbox. Each file contains raw EEG data, channel info, and event markers for a specific experimental paradigm. Files can be loaded using mne.io.read_raw_eeglab() from MNE-Python, a SignalFlowEEG dependency. The dataset has no missing data or special abbreviations. Channel names and event markers follow standard EEGLAB conventions.

SignalFlowEEG示例数据集（SignalFlowEEG Example Data）包含示例脑电（electroencephalography，EEG）记录，用于展示SignalFlowEEG Python工具包的功能与使用方法。该工具包提供了一套完整的脑电数据处理、分析与可视化工具，聚焦神经科学研究应用场景。

本示例数据集涵盖多种实验范式下的脑电记录：
静息态脑电：受试者闭眼放松状态下采集的5分钟脑电记录；
听觉啁啾刺激：受试者聆听不同频率啁啾声音时采集的脑电记录；
视觉诱发电位：受试者观看棋盘格视觉刺激以诱发视觉反应时采集的脑电记录。

上述脑电记录均由辛辛那提儿童医院医疗中心采集，仅用于教学与测试用途。

SignalFlowEEG基于当前主流的开源脑电分析库MNE-Python开发，并针对临床研究工作流定制了额外功能。本示例数据集可帮助用户全面探索SignalFlowEEG的功能，并通过这款强大的Python工具包积累脑电数据分析的实操经验。

该数据集采用EEGLAB工具箱的.set文件格式存储，每个文件均包含对应实验范式下的原始脑电数据、通道信息与事件标记。用户可通过SignalFlowEEG的依赖库MNE-Python中的`mne.io.read_raw_eeglab()`函数加载这些文件。本数据集无缺失数据或特殊缩写，通道名称与事件标记均遵循EEGLAB的标准规范。