NDLI: Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis

Content Provider	ACM Digital Library
Author	Canzian, Luca Musolesi, Mirco
Abstract	One of the most interesting applications of mobile sensing is monitoring of individual behavior, especially in the area of mental health care. Most existing systems require an interaction with the device, for example they may require the user to input his/her mood state at regular intervals. In this paper we seek to answer whether mobile phones can be used to unobtrusively monitor individuals affected by depressive mood disorders by analyzing only their mobility patterns from GPS traces. In order to get ground-truth measurements, we have developed a smartphone application that periodically collects the locations of the users and the answers to daily questionnaires that quantify their depressive mood. We demonstrate that there exists a significant correlation between mobility trace characteristics and the depressive moods. Finally, we present the design of models that are able to successfully predict changes in the depressive mood of individuals by analyzing their movements.
Starting Page	1293
Ending Page	1304
Page Count	12
File Format	PDF
ISBN	9781450335744
DOI	10.1145/2750858.2805845
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2015-09-07
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Mobile sensing Gps traces Depression Spatial statistics
Content Type	Text
Resource Type	Article

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Trajectories of depression: unobtrusive monitoring of depressive states by means of smartphone mobility traces analysis