Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables
The ACM International Conference on Mobile Human-Computer Interaction (MobileHCI)
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Searle, B., Spathis, D., Constantinides, M., Quercia, D., & Mascolo, C. Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables. The ACM International Conference on Mobile Human-Computer Interaction (MobileHCI). https://doi.org/10.1145/3447526.3472061
Body-focused repetitive behaviors (BFRBs), like face-touching or skin-picking, are hand-driven behaviors which can damage one's appearance, if not identified early and treated. Technology for automatic detection is still under-explored, with few previous works being limited to wearables with single modalities (e.g., motion). Here, we propose a multi-sensory approach combining motion, orientation, and heart rate sensors to detect BFRBs. We conducted a feasibility study in which participants (N=10) were exposed to BFRBs-inducing tasks, and analyzed 380 mins of signals under an extensive evaluation of sensing modalities, cross-validation methods, and observation windows. Our models achieved an AUC > 0.90 in distinguishing BFRBs, which were more evident in observation windows 5 mins prior to the behavior as opposed to 1-min ones. In a follow-up qualitative survey, we found that not only the timing of detection matters but also models need to be context-aware, when designing just-in-time interventions to prevent BFRBs.
This work is partially supported by Nokia Bell Labs through their donation to the Centre of Mobile, Wearable Systems and Augmented Intelligence at the University of Cambridge. D.S is additionally supported by the Embiricos Trust Scholarship of Jesus College Cambridge, and the EPSRC through Grant DTP (EP/N509620/1).
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External DOI: https://doi.org/10.1145/3447526.3472061
This record's URL: https://www.repository.cam.ac.uk/handle/1810/324592
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