Sample data associated with the Aurora-BP study

Overview

The Aurora-BP Study and Dataset

This repository contains sample code, sample data, and explanatory information for working with the Aurora-BP dataset released alongside the publication of the Aurora-BP study, i.e., Mieloszyk, Rebecca, et al. "A Comparison of Wearable Tonometry, Photoplethysmography, and Electrocardiography for Cuffless Measurement of Blood Pressure in an Ambulatory Setting." IEEE Journal of Biomedical and Health Informatics (2022). The dataset includes de-identified participant information, raw sensor data aligned with each measurement, and a wide variety of features derived from sensor data. The publishing of this dataset as well as the characterization of multiple feature groups across a broad population and multiple settings are intended to aid future cardiovascular research.

Note that the data contained in this repository represent a very small sample of the full dataset, meant only to illustrate the structure of the files and allow testing with the sample code. For access to the full dataset, see the Data Use Application section below.

Navigation:

  • docs:
    • Data file descriptions, a detailed overview of the Aurora-BP Study protocol, and supplemental results not included in the Aurora-BP Study publication
  • notebooks:
    • Sample Jupyter notebooks and environment files for basic analyses using Aurora-BP Study data
  • sample:
    • Example data files, to run sample Jupyter notebooks and provide researchers a direct look at the data format before application for full data access.

Citation

If you use this repository, part or all of the full dataset, and/or our paper as part of your research, please refer to the dataset as the Aurora-BP dataset and cite the publication as below:


Data Access

Data Access Committee

Requests for data access are reviewed by the Data Access Committee. During review, the submitting investigator and primary investigator may be contacted for verification. The information you will need to gather to submit a Data Use Application as well as a link to the form are listed below. For additional questions regarding data access, contact: [email protected]


Data Use Application

Full data files are stored separately from this repo within an Azure data lake. To gain access to these data files, a data use application (detailed below and on the data lake landing page) must be submitted. Any researcher may submit a data use application, which includes:

  • Principal investigator information
    • Academic credentials, affiliation, contact information, curriculum vitae, signature attesting accuracy of data use application
  • Additional investigator information
    • Academic credentials, affiliation, contact information
  • Research proposal
  • Acknowledgement to comply with data use agreement. Key points are listed below:
    • No sharing of data with anyone outside of approved PI and other specified investigators. New investigators must be reviewed.
    • No data use outside of stated proposal scope
    • No joining of data with other data sources
    • No attempt to identify participants, contact participants, or reconstruct PII
    • Storage with appropriate access control and best practices
    • You may publish (or present papers or articles) on your results from using the data provided that no confidential information of Microsoft and no Personal Information are included in any such publication or presentation
    • Any publication or presentation resulting from use of the data should include reference to the Aurora-BP Study, with full reference to the source publication when appropriate
    • Aurora-BP Study authors and Microsoft are under no obligation to provide any support or additional materials related to the use of these data
    • Aurora-BP Study authors and Microsoft are not liable for any losses, damages, or harms of any kind in connection to the use of these data
    • Aurora-BP Study authors and Microsoft are not responsible or liable for the accuracy, usefulness or availability of these data
    • Primary Investigator will provide a signature of attestation that they have read, understood, and accept the data use agreement
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Comments
  • This repo is missing important files

    This repo is missing important files

    There are important files that Microsoft projects should all have that are not present in this repository. A pull request has been opened to add the missing file(s). When the pr is merged this issue will be closed automatically.

    Microsoft teams can learn more about this effort and share feedback within the open source guidance available internally.

    Merge this pull request

    opened by microsoft-github-policy-service[bot] 0
  • Adding Microsoft SECURITY.MD

    Adding Microsoft SECURITY.MD

    Please accept this contribution adding the standard Microsoft SECURITY.MD :lock: file to help the community understand the security policy and how to safely report security issues. GitHub uses the presence of this file to light-up security reminders and a link to the file. This pull request commits the latest official SECURITY.MD file from https://github.com/microsoft/repo-templates/blob/main/shared/SECURITY.md.

    Microsoft teams can learn more about this effort and share feedback within the open source guidance available internally.

    opened by microsoft-github-policy-service[bot] 0
  • Feature/dataprovenance

    Feature/dataprovenance

    Replaced the old data provenance figure with a new one: one participant's discard step was misclassified. The new figure represents the actual data files in the full dataset.

    opened by twede 0
  • Environment lock files

    Environment lock files

    Changes:

    • Modified notebooks to use sample data in the repo
    • Renamed SAMPLE_DIR to DATA_DIR
    • Sorted import statements
    • Changed python version from 3.6 to 3.8
    • Generated conda-lock files for x64 Windows, Linux, and Mac in additional to ARM Mac.
    • Added README for setting up environment and running Jupyter

    Testing:

    • Tested by creating the environment using lock files, running Jupyter and executing all cells of all notebooks
    • Tested on the following environments:
      • Windows (x64)
      • WSL2 Ubuntu (x64)
      • Mac OSX (x64)
    opened by gabe-microsoft 0
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