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

In modern anesthesia, multiple medical devices are used simultaneously tocomprehensively monitor real-time vital signs to optimize patient care andimprove surgical outcomes. However, interpreting the dynamic changes of time-series biosignals and their correlations is a difficult task even forexperienced anesthesiologists. Recent advanced machine learning technologieshave shown promising results in biosignal analysis, however, research anddevelopment in this area is relatively slow due to the lack of biosignaldatasets for machine learning. The VitalDB (Vital Signs DataBase) is an opendataset created specifically to facilitate machine learning studies related tomonitoring vital signs in surgical patients. This dataset contains high-resolution multi-parameter data from 6,388 cases, including 486,451 waveformand numeric data tracks of 196 intraoperative monitoring parameters, 73perioperative clinical parameters, and 34 time-series laboratory resultparameters. All data is stored in the public cloud after anonymization. Thedataset can be freely accessed and analysed using application programminginterfaces and Python library. The VitalDB public dataset is expected to be avaluable resource for biosignal research and development.