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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
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Past research in the field that you’re building upon
A large number of subjects have signed up for this study to download and run a smartphone app (Android and iOS) on their personal devices and allow specific and partially-prompted data acquisition that ranges from their answers to survey question to sensor data recording at various activity contexts.
The effect of mood and mental on human activity, whether it is smartphone use activity or actual physical activity, has been an active research track for decades. Human activity modeling and recognition may be performed using wearable sensors and/or smartphone sensors, and our study deals with the latter.
This research was inspired by the fact that almost everyone nowadays has a smartphone that they are constantly using, which makes our access to valuable data to assess and improve people's health an easy-to-achieve task using state-of-the-art data analytics and machine learning. Research that inspired you to start this project
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