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. 2016 May;23(3):538-43.
doi: 10.1093/jamia/ocv200. Epub 2016 Mar 14.

Automatic detection of social rhythms in bipolar disorder

Saeed Abdullah  1 , Mark Matthews  2 , Ellen Frank  3 , Gavin Doherty  4 , Geri Gay  2 , Tanzeem Choudhury  2
Affiliations

Automatic detection of social rhythms in bipolar disorder

Saeed Abdullah et al. J Am Med Inform Assoc. 2016 May.

Abstract

Objective: To evaluate the feasibility of automatically assessing the Social Rhythm Metric (SRM), a clinically-validated marker of stability and rhythmicity for individuals with bipolar disorder (BD), using passively-sensed data from smartphones.

Methods: Seven patients with BD used smartphones for 4 weeks passively collecting sensor data including accelerometer, microphone, location, and communication information to infer behavioral and contextual patterns. Participants also completed SRM entries using a smartphone app.

Results: We found that automated sensing can be used to infer the SRM score. Using location, distance traveled, conversation frequency, and non-stationary duration as inputs, our generalized model achieves root-mean-square-error of 1.40, a reasonable performance given the range of SRM score (0-7). Personalized models further improve performance with mean root-mean-square-error of 0.92 across users. Classifiers using sensor streams can predict stable (SRM score ≥3.5) and unstable (SRM score <3.5) states with high accuracy (precision: 0.85 and recall: 0.86).

Conclusions: Automatic smartphone sensing is a feasible approach for inferring rhythmicity, a key marker of wellbeing for individuals with BD.

Keywords: bipolar disorder; mHealth; mobile sensing; ubiquitous computing.

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Conflict of interest statement

M.M., E.F., and T.C. co-founded and have equity interest in HealthRhythms. G.G. serves on the advisory board for HealthRhythms.

Figures

Figure 1:
Figure 1:
Sample paper-based Social Rhythm Metric form that is used as part of Interpersonal Social Rhythm Therapy.
Figure 2:
Figure 2:
Screens from the MoodRhythm app used by participants for this study.
See this image and copyright information in PMC

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