Ultimately, I hope to predict the onset of depression by feeding this data into a neural network, and perhaps even preempt it by teaching the neural net to recommend/enforce interventions. As a preliminary exercise, I've trained a couple ML models to predict mood with only a month of data; see the documentation here.
Below are visualizations of a week's worth of data collected by my homemade python trackers. The brush at the bottom of the page controls the time domain of all the charts.
I choose these variables as an attempt to measure mindwandering, a marker strongly correlated with depression. The emojis were included to illustrate the concept of valence (also just for funsies).