The BIDMC dataset is a dataset of electrocardiogram (ECG), pulse oximetry (photoplethysmogram, PPG) and impedance pneumography respiratory signals acquired from intensive care patients. The dataset is intended to be used for evaluating the performance of algorithms in real-case operating conditions. This dataset is a very small subset of the Physionet’s MIMIC II Waveform Database Matched Subset, which contains all MIMIC II Waveform Database records that have been associated with the MIMIC II Clinical Database records. Read more about the overall dataset here.
The dataset comprises 53 8-minute recordings of ECG, PPG, and impedance pneumography signals (sampling frequency, fs = 125 Hz) acquired from adult patients (aged 19-90+, 32 females). Those in the dataset were randomly selected from a larger cohort of patients who were admitted to medical and surgical intensive care units at the Beth Israel Deaconess Medical Center (BIDMC), Boston, USA. Two sets of annotations (performed manually and independently by two research assistants) of individual breaths of the impedance pneumography signal can be used to derive reference respiratory rate values.
The dataset was used in this publication and the publication below for evaluating the performance of different respiratory rate estimation algorithms.Pimentel, M.A.F. et al. Towards a Robust Estimation of Respiratory Rate from Pulse Oximeters, IEEE Transactions on Biomedical Engineering, [In press], 2016
CitationWhen using this dataset please cite these two publications:
Saeed, M. et al. Multiparameter intelligent monitoring in intensive care II (MIMIC-II): A public-access ICU database, Critical Care Medicine, 39(5):952-960, 2011.
Goldberger A.L. et al. PhysioBank, PhysioToolkit, and PhysioNet: Components of a New Research Resource for Complex Physiologic Signals, Circulation, 101(23):e215-e220, 2000.
Link to download
A link to the dataset will be provided here upon publication.