Mood Monitor

Mood Monitor is an Android application that users can use to track their daily activities like walking, jogging, sitting, standing, walking upstairs and walking downstairs. The application uses a Convolutional Neural Network (CNN) to predict user activity automatically and stores the information in a database stored on the phone. The users can then choose to visualize the statistics.

Java File Structure

1. MainActivity

   • Registers/unregisters event listener
   • Records readings from the accelerometers
   • Calls RecognitionActivity for prediction and chooses activity with highest confidence score
   • Inserts a predicted activity to a SQLite database in the background

2. RecognitionActivity

   • Initializes trained CNN classifier
   • Feeds normalized input into the classifier and sends output back to MainActivity

3. DisplayStatsActivity

   • Queries the SQLite database to display pie chart on the screen

4. Activity

   • Contains database schema in the form of objects (uses Room Persistence Library)

5. ActivityDao

   • Provides interface to modify and query the database (through Data Access Objects)

6. AppDatabase

   • Initializes an SQLite database for the application

7. Constants

   • Holds constant values used in all class files