CfP: 5th International Workshop on Mental Health and Well-being: Sensing
and Intervention (MHSI)`
Mental health issues affect a significant portion of the world’s population
and can result in debilitating and life-threatening outcomes. To address
this increasingly pressing healthcare challenge, there is a need to
research novel approaches for early detection and prevention. In
particular, ubiquitous systems can play a central role in revealing and
tracking clinically relevant behaviors, contexts, and symptoms. Further,
such systems can passively detect relapse onset and enable the opportune
delivery of effective intervention strategies.
However, despite their clear potential, the uptake of ubiquitous
technologies into clinical mental healthcare is rare, and a number of
challenges still face the overall efficacy of such technology-based
solutions. The goal of this workshop is to bring together academic and
industry researchers interested in identifying, articulating, and
addressing such issues and potential opportunities. Following the success
of this workshop in the last four years, we aim to continue facilitating
the UbiComp community in developing a holistic approach for sensing and
intervention in the context of mental health.
*Topics of Interest*
We invite submissions in the areas and intersections of mental health,
well-being, ubiquitous computing, and human-centered design, including but
not limited to:
— Design and implementation of computational platforms (e.g., mobile
phones, instrumented homes, skin-patch sensors) to collect health and
— Investigating new methodologies for intervention (e.g., conversational
agents, AR/VR applications).
— Automated inference from sensor data of high-level contexts
(environmental, social) indicative of mental health status.
— Design and implementation of feedback (e.g., reports, visualizations,
proactive behavioral interventions, subtle or subconscious interventions
etc.) for both patients and caregivers.
— Development of robust behavioral models that can handle data sparsity and
— Integration of multimodal data from various sensor streams for
personalized predictive modeling.
— Methods for sustaining user adherence and engagement over long periods of
— Devising privacy-preserving strategies for data collection, analysis, and
— Deployment in low-income communities/countries.
— Identification of opportunities for UbiComp approaches (e.g., digital
phenotyping, predictive modeling, micro-randomized intervention trials,
adaptive interventions) to better understand factors related to addiction,
drug use, and treatment efficacy and devise a research agenda in this space.
— Identifying ways to better integrate ubiquitous technologies into
existing healthcare infrastructures and government policy.
— Applied ethical principles and frameworks for ubiquitous technologies for
As in the previous 4 years, we will accept regular (up to 6 pages) and
short (up to 3 pages) paper contributions that describe novel technologies,
approaches, and studies related to ubiquitous computing in mental health.
All papers should adhere to the UbiComp template policy:
All submitted papers will be reviewed and judged on originality, technical
correctness, relevance, and quality of presentation. We explicitly invite
submissions of papers that describe preliminary results or
work-in-progress. The accepted papers will appear in the UbiComp
supplemental proceedings and in the ACM Digital Library.
Submission deadline: July 06, 2020 at 11:59 PM HAST
Notification date: July 24, 2020
Camera-ready deadline: July 31, 2020
Virtual Conference: September 12, 2020
*Workshop website*: https://ubicomp-mental-health.github.io/
Varun Mishra, Dartmouth College
Akane Sano, Rice University
Saeed Abdullah, Pennsylvania State University
Jakob E. Bardram, Technical University of Denmark
Sandra Servia, University of Cambridge
Elizabeth L. Murnane, Stanford University
Tanzeem Choudhury Cornell University
Mirco Musolesi University, College London
Giovanna Nunes Vilaza, Technical University of Denmark
Rajalakshmi Nandakumar, Cornell Tech
Tauhidur Rahman, UMass Amherst
Akane Sano [log in to unmask]
Assistant Professor, Computational Wellbeing Group, Rice University
6100 Main Street, Houston, TX, 77005, Duncan Hall 2025, MS 380
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