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
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.

搜集汇总

背景与挑战

背景概述

VitalDB是一个高保真多参数生命体征数据库，专注于手术患者，包含6,388个病例的486,451个波形和数值数据轨道，涵盖196个术中监测参数、73个围手术期临床参数和34个时间序列实验室结果参数。数据以高分辨率记录（数值数据1-7秒，波形数据62.5-500 Hz），经过匿名化处理并存储在公共云中，旨在促进机器学习研究，特别是生命体征监测算法的开发。该数据集的特点是提供多参数、时间同步的高保真数据，并整合围手术期临床信息，以支持生物信号分析和临床决策研究。