Description:
This project is a smartphone sensor data analytics project that deals with a full set of heterogeneous datasets to be correlated with mood analysis and mental health. The acquired data includes periodically-prompted user survey entries, light sensor output, Bluetooth and WiFi status, GPS data, and multivariate IMU time series e.g. 3-axis accelerometer and 3-axis gyroscope output at simple and complex activity contexts.
Background/History
Any information that can help understand the project better
Past research in the field that you’re building upon
Research that inspired you to start this project
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Purpose
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Benefits
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How
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Further reading
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Additional information
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What:
https://healthstudy.tozny.com/help
Resource Stack
| Resource | Location |
|---|---|
| Point of Contact | Unknown User (abhishek_pratap) Ramzi HalabiUnknown User (calvin_herd) (sensor data) Unknown User (sophia_li)(survey data) |
| Admin | |
| Contractor | |
| Tech JIRA Project | |
| Code Repo | https://github.com/aid4mh/washdata_analysis (data analysis related) https://github.com/aid4mh/washstudy_ops (operational related) |
| Timeline | https://docs.google.com/spreadsheets/d/1-6ShkuSEzzxG1QlJQ7nX-KytWkFWNzGvuKQdymgqLkA/edit?usp=sharing (WASH Compliance Study 2022Q1 Timeline) |
| Other Public Websites | https://psychiatry.uw.edu/project/hippocratic-app-study/ |
| Enrollment Website | https://healthstudy.tozny.com/help |
Reference papers
- Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants (retention study)
- https://github.com/Sage-Bionetworks/digitalHealth_RetentionAnalysis_PublicRelease (code associated with the above study)
- https://github.com/Sage-Bionetworks/digitalHealth_RetentionAnalysis_PublicRelease/blob/master/analysis/timeToEvent_TRUE.Right.CensoringApproach.R (code associated with the above study)
- An Alternative to the Light Touch Digital Health Remote Study: The Stress and Recovery in Frontline COVID-19 Health Care Workers Study (compliance study)