Estimating Human Predictability From Mobile Sensor Data

Bjørm Sand Jensen, Jakob Eg Larsen, Kristian Jensen, Jan Larsen, Lars Kai Hansen

AbstractQuantification of human behavior is of prime interest in many applications ranging from behavioral science to practical applications such as GSM resource planning and context-aware services. As proxies for humans, we apply multiple mobile phone sensors all conveying information about human behavior. Using a recent, information theoretic approach it is demonstrated that the trajectories of individual sensors are highly predictable given complete knowledge of the infinite past. We suggest using a new approach to time scale selection which demonstrates that participants have even higher predictability of non-trivial behavior on smaller timer scale than previously considered.
TypeConference paper [With referee]
ConferenceIEEE International Workshop on Machine Learning for Signal Processing
Year2010    Month August
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing


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