Journal Article

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

Park, Dongnyeok, Lee, Hyung-Chul, Park, Yoonsang, Jung, Chul-Woo, Yoon, Soo Bin, Yang, Seong Mi

2022

Overview

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

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 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