https://github.com/googlecloudplatform/deviceconnect

https://deviceconnect.readthedocs.io/
https://github.com/googlecloudplatform/deviceconnect

bigquery cloudrun fitbit gcp

Last synced: 8 months ago
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https://deviceconnect.readthedocs.io/

• Host: GitHub
• URL: https://github.com/googlecloudplatform/deviceconnect
• Owner: GoogleCloudPlatform
• License: apache-2.0
• Created: 2022-06-14T17:35:37.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-12-11T00:30:01.000Z (10 months ago)
• Last Synced: 2024-12-18T08:40:24.047Z (10 months ago)
• Topics: bigquery, cloudrun, fitbit, gcp
• Language: CSS
• Homepage:
• Size: 3.94 MB
• Stars: 24
• Watchers: 14
• Forks: 29
• Open Issues: 9
• Metadata Files:
  • Readme: README.rst
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

README

          
.. raw:: html

.. image:: docs/source/_static/youtube.png

  :width: 100%

  :alt: youtube link

  :align: center

  :target: https://www.youtube.com/embed/OFCKEXGSE3A

`Device Connect for Fitbit`_ uses Google Cloud and `Fitbit web apis`_ to enable

developers to build clinical health applications that leverage data from users'

Fitbit activity trackers.  The tools provided in this repo are open source and build upon

the Google Cloud services.  These tools provide:

  * end-user enrollment, consent management and Fitbit device linking,

  * a data connecter that ingests data from the Fitbit web apis and

    pushes to Cloud BigQuery,

  * looker dashboards for visualizing participants data in specific or

    in aggregate.

Deploy the infrastructure to capture your patient's fitbit data in minutes using 

the provided terraform scripts.  Simply create your GCP project, install terraform,

and run ``terraform apply``.  

The infrastructure uses Cloud Run and Fire Store to manage user enrollment and 

consent; and Cloud BigQuery to store data from the Fitbit webapis.  Once the data

is in BQ, build dashboards with Looker (or other dashboarding tool), and develop 

ML models with AI Notebooks or Vertex AI (tutorials coming).

Dashboards

----------

The Fitbit data provides a unique 360-degree view of the patients' lives and

can be clinically valuable for physicians or health coaches.  It can also 

be integrated with other datasets like EHR data, or other device data.  

Here are some dashboard views that might be valuable:

  * the first view shows overview of stats.  In this case, the patient's Fitbit data

    has been enriched with the date of a past surgury.  It shows the percent of time she is

    wearing the Fitbit device, along with overall statistics.

    .. image:: docs/source/_static/user_overview.png

      :width: 90%

      :alt: user steps dashboard

      :align: center

  * Furter details about steps can also identify potential problems to recovery.

    .. image:: docs/source/_static/user_steps.png

      :width: 90%

      :alt: user steps dashboard

      :align: center

  * and more details about types and range of activity show more details for the 

    clincial teams:

    .. image:: docs/source/_static/user_activity_zones.png

      :width: 90%

      :alt: user steps dashboard

      :align: center

  * or more details on sleep:

     .. image:: docs/source/_static/user_sleep.png

      :width: 90%

      :alt: user steps dashboard

      :align: center

Machine Learning

----------------

While the dashboards can provide valuable insights about the patient's day to day,

more detailed models can be developed that provide both population-level clustering

across a patient population, and more predictive models that can help clinical teams

identify address problems early.

Fine Print

------------

  * First and foremost, *this is not a product!*  there is no support.  This

    is provided as is, with no warrantees, as an example.  Use at your own

    risk.  post issues if you run into any, fork and develop if it is useful

    for your needs.

  

  * By default, the code uses OIDC for user identities (seperate from Fitbit 

    identities).  

    The deployment instructions use `Google OIDC`_ but any OIDC can be

    configured.

  * Data is ingested daily by default (you can configure the Cloud Scheduler

    component, see Terraform scripts).  This

    is not intended for real-time use cases.

.. _Fitbit web apis:

  https://dev.fitbit.com/build/reference/web-api/

.. _Device Connect for Fitbit:

  https://cloud.google.com/device-connect

.. _Google OIDC:

  https://developers.google.com/identity/protocols/oauth2/openid-connect