Biosemi-Muse Resting-state Dataset

This dataset contains raw resting state EEG recordings collected from the same participants using two EEG systems: a low density wearable headset (MUSE) and a research grade 64 channel system (BIOSEMI ActiveTwo). Recordings were acquired during approximately 2 minutes of resting state in a laboratory environment, including eyes open and eyes closed conditions, with condition order alternated across participants to reduce order effects. MUSE recordings are provided in .csv format and were acquired using the MuseMonitor application on Chromebook laptops. These recordings include four dry active channels with approximate locations at AF7, AF8, TP9, and TP10, sampled at 256 Hz. Prior to recording, the skin was cleaned with alcohol wipes and a thin layer of water was applied to the dry electrodes to improve signal quality. BIOSEMI recordings are provided in .bdf format and were acquired using the ActiveTwo software. These recordings include 64 gel based channels positioned according to the international 10-20 system, with electrode placement guided by standard fiducial landmarks (nasion, inion, and left and right preauricular points). Data collection followed gold standard EEG procedures, including impedance checks, use of conductive gel, and appropriately sized headcaps for each participant. Only raw EEG time series and minimal acquisition metadata are included. No preprocessing, filtering, artifact rejection, or feature extraction has been applied to the shared data. All data are anonymized and contain no personally identifiable information. The dataset is intended for reuse in methodological validation, signal processing development, and benchmarking analyses comparing wearable and research grade EEG systems. Associated publication For detailed information on data collection procedures, experimental context, and validation analyses, please refer to the following publication. Please cite this paper when using this dataset. Cannard, C., Wahbeh, H., and Delorme, A. (2021). Validating the wearable MUSE headset for EEG spectral analysis and frontal alpha asymmetry. IEEE International Conference on Bioinformatics and Biomedicine (BIBM). https://doi.org/10.1109/BIBM52615.2021.9669778