VitalDB, a high-fidelity multi-parameter vital signs database in surgical patients

In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for expe...

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Bibliographic Details
Published in:Scientific data Vol. 9; no. 1; pp. 279 - 9
Main Authors: Lee, Hyung-Chul, Park, Yoonsang, Yoon, Soo Bin, Yang, Seong Mi, Park, Dongnyeok, Jung, Chul-Woo
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 08.06.2022
Nature Publishing Group
Nature Portfolio
Subjects:
631/114/1305
692/308
Anesthesia
Data Descriptor
Databases, Factual
Datasets
Electronic health records
Electronic medical records
Humanities and Social Sciences
Humans
Interfaces
Learning algorithms
Machine Learning
Medical equipment
Medical records
Monitoring, Physiologic - methods
multidisciplinary
Patients
R&D
Research & development
Science
Science (multidisciplinary)
Vital Signs
ISSN:2052-4463, 2052-4463
Online Access:Get full text
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Summary:In modern anesthesia, multiple medical devices are used simultaneously to comprehensively monitor real-time vital signs to optimize patient care and improve surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even for experienced anesthesiologists. Recent advanced machine learning technologies have shown promising results in biosignal analysis, however, research and development in this area is relatively slow due to the lack of biosignal datasets for machine learning. The VitalDB (Vital Signs DataBase) is an open dataset created specifically to facilitate machine learning studies related to monitoring vital signs in surgical patients. This dataset contains high-resolution multi-parameter data from 6,388 cases, including 486,451 waveform and numeric data tracks of 196 intraoperative monitoring parameters, 73 perioperative clinical parameters, and 34 time-series laboratory result parameters. All data is stored in the public cloud after anonymization. The dataset can be freely accessed and analysed using application programming interfaces and Python library. The VitalDB public dataset is expected to be a valuable resource for biosignal research and development. Measurement(s) vital signs of patients during surgery • perioperative patient information Technology Type(s) Vital Signs Measurement • Electronic Medical Record Factor Type(s) vital signs data including various numeric and waveform data acquired from multiple patient monitors • perioperative patient information acquired from the electronic medical record system Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment hospital Sample Characteristic - Location South Korea
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ISSN:2052-4463
2052-4463
DOI:10.1038/s41597-022-01411-5