Modeling long-term human activeness using recurrent neural networks for biometric data.
Journal:
BMC medical informatics and decision making
Published Date:
May 18, 2017
Abstract
BACKGROUND: With the invention of fitness trackers, it has been possible to continuously monitor a user's biometric data such as heart rates, number of footsteps taken, and amount of calories burned. This paper names the time series of these three types of biometric data, the user's "activeness", and investigates the feasibility in modeling and predicting the long-term activeness of the user.