Name: Harvard Electroencephalography Database
Published: June 15, 2023
License: https://github.com/bdsp-core/bdsp-license-and-dua

Database Restricted Access

Sahar Zafar , Tobias Loddenkemper , Jong Woo Lee , Andrew Cole , Daniel Goldenholz , Jurriaan Peters , Alice Lam , Edilberto Amorim , Catherine Chu , Sydney Cash , Valdery Moura Junior , Aditya Gupta , Manohar Ghanta , Marta Fernandes , Haoqi Sun , Jin Jing , M Brandon Westover

Published: June 15, 2023. Version: 1.0 <View latest version>

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When using this resource, please cite: (show more options)
Zafar, S., Loddenkemper, T., Lee, J. W., Cole, A., Goldenholz, D., Peters, J., Lam, A., Amorim, E., Chu, C., Cash, S., Moura Junior, V., Gupta, A., Ghanta, M., Fernandes, M., Sun, H., Jing, J., & Westover, M. B. (2023). Harvard Electroencephalography Database (version 1.0). Brain Data Science Platform. https://doi.org/10.60508/7651-3337.

MLA	Zafar, Sahar, et al. "Harvard Electroencephalography Database" (version 1.0). Brain Data Science Platform (2023), https://doi.org/10.60508/7651-3337.
APA	Zafar, S., Loddenkemper, T., Lee, J. W., Cole, A., Goldenholz, D., Peters, J., Lam, A., Amorim, E., Chu, C., Cash, S., Moura Junior, V., Gupta, A., Ghanta, M., Fernandes, M., Sun, H., Jing, J., & Westover, M. B. (2023). Harvard Electroencephalography Database (version 1.0). Brain Data Science Platform. https://doi.org/10.60508/7651-3337.
Chicago	Zafar, Sahar, Loddenkemper, Tobias, Lee, Jong Woo, Cole, Andrew, Goldenholz, Daniel, Peters, Jurriaan, Lam, Alice, Amorim, Edilberto, Chu, Catherine, Cash, Sydney, Moura Junior, Valdery, Gupta, Aditya, Ghanta, Manohar, Fernandes, Marta, Sun, Haoqi, Jing, Jin, and M Brandon Westover. "Harvard Electroencephalography Database" (version 1.0). Brain Data Science Platform (2023). https://doi.org/10.60508/7651-3337.
Harvard	Zafar, S., Loddenkemper, T., Lee, J. W., Cole, A., Goldenholz, D., Peters, J., Lam, A., Amorim, E., Chu, C., Cash, S., Moura Junior, V., Gupta, A., Ghanta, M., Fernandes, M., Sun, H., Jing, J., and Westover, M. B. (2023) 'Harvard Electroencephalography Database' (version 1.0), Brain Data Science Platform. Available at: https://doi.org/10.60508/7651-3337.
Vancouver	Zafar S, Loddenkemper T, Lee J W, Cole A, Goldenholz D, Peters J, Lam A, Amorim E, Chu C, Cash S, Moura Junior V, Gupta A, Ghanta M, Fernandes M, Sun H, Jing J, Westover M B. Harvard Electroencephalography Database (version 1.0). Brain Data Science Platform. 2023. Available from: https://doi.org/10.60508/7651-3337.

Abstract

The Harvard EEG Database will encompass data gathered from four hospitals affiliated with Harvard University: Massachusetts General Hospital (MGH), Brigham and Women's Hospital (BWH), Beth Israel Deaconess Medical Center (BIDMC), and Boston Children's Hospital (BCH). The EEG data includes three types:

rEEG: "routine EEGs" recorded in the outpatient setting.
EMU: recordings obtained in the inpatient setting, within the Epilepsy Monitoring Unit (EMU).
ICU: recordings obtained from acutely and critically ill patients within the intensive care unit (ICU).

Background

Electroencephalography (EEG) signals are valuable for diagnosing various conditions such as epilepsy, identifying the causes of encephalopathy, predicting the chances of consciousness recovery in patients with prolonged coma after cardiac arrest, assessing the level of consciousness in patients under anesthesia, and assessing sleep quality, among many other medical applications. This repository offers a large and diverse collection of real-world EEG data, serving as a resource for researchers to develop more effective methods for analyzing EEG signals. By sharing this data, our goal is to facilitate broader access to accurate EEG interpretation worldwide and foster research advancements in neurologic disorders. We hope that this repository will lead to broader access to EEG and to new knowledge that improves brain health for all.

Methods

Most EEG data in this repository is recorded using the International 10-20 system for scalp electrode placement. Sampling rates of recordings are provided in the EEG header files.

Data Description

Data is currently stored in .mat format. In the future we will be transferring data to the EEG-BIDS format.

Usage Notes

Code for loading the EEG data is available in the associated GitHub repository (https://github.com/bdsp-core/Harvard-EEG-Database-Tools).

Ethics

In this dataset, all data were anonymized with all identifiable patient information removed.

Acknowledgements

Thanks to the EEG technologists, attending physicians, and fellows who provide EEG diagnostic services.

Conflicts of Interest

This work was supported by grants from the NIH (R01NS102190, R01NS102574, R01NS107291, RF1AG064312, RF1NS120947, R01AG073410, R01HL161253, R01NS126282, R01AG073598).