mCerebrum is a configurable smartphone software platform for mobile and wearable sensors. It provides support for reliable data collection from mobile and wearable sensors, and offers real-time processing of these data.
StreamProcessor is a real-time processing pipeline for AutoSense chest and wrist sensors. It implements the following algorithms:
- cStress: A continuous stress assessment algorithm
You can find more information about MD2K software on our software website or the MD2K organization on our MD2K website.
- UbiComp 2015 cStress: Towards a Gold Standard for Continuous Stress Assessment in the Mobile Environment Karen Hovsepian, Mustafa al'absi, Emre Ertin, Thomas Kamarck, Motoshiro Nakajima, Santosh Kumar pdf
Download and install the latest AutoSense and StreamProcessor applications.
- Go to Settings.
- Select Security.
- On the list, Find Unknown Sources and CHECK the box.
- When done, go back to the folder.
- Tap on the apk file and select Open/Install. It should be able to install.
Please read our Contributing Guidelines for details on the process for submitting pull requests to us.
We use the Google Java Style Guide.
Our Code of Conduct is the Contributor Covenant.
Bug reports can be submitted through JIRA.
Our discussion forum can be found here.
git clone https://github.com/MD2Korg/mCerebrum-Utilities.git
git clone https://github.com/MD2Korg/mCerebrum-DataKitAPI.git
git clone https://github.com/MD2Korg/mCerebrum-StreamProcessor.git
We use Semantic Versioning for versioning the software which is based on the following guidelines.
MAJOR.MINOR.PATCH (example: 3.0.12)
- MAJOR version when incompatible API changes are made,
- MINOR version when functionality is added in a backwards-compatible manner, and
- PATCH version when backwards-compatible bug fixes are introduced.
For the versions available, see this repository's tags.
Link to the list of contributors who participated in this project.
This project is licensed under the BSD 2-Clause - see the license file for details.
- National Institutes of Health - Big Data to Knowledge Initiative
- Grants: R01MD010362, 1UG1DA04030901, 1U54EB020404, 1R01CA190329, 1R01DE02524, R00MD010468, 3UH2DA041713, 10555SC
- National Science Foundation
- Grants: 1640813, 1722646
- Intelligence Advanced Research Projects Activity
- Contract: 2017-17042800006