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.