We demonstrate the idea of "Thermometer for the Mind":
the mental state estimating system by a user’s activity log
derived from wearable devices. While it is well known that
physical and social activities are correlated with the mental
state, our aim is to build an application which tracks daily
activities automatically, estimates the mental state and visualizes
it in an easily understandable way. As a preliminary
experiment, we investigated how information about physical
activity from a smartphone (step counts) and social activity
from a Web service (Twitter post counts) can be used to
estimate a user’s mental state. The method is evaluated on
one participant’s 5 months recording. The classification accuracy
for 3 classes (mood is low, middle and high) is 60%.
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