Mental Health : Sensing & Intervention (2018)

In this UbiComp 2018 workshop, we are hoping to bring researchers together to discuss requirements, opportunities, challenges and next steps in developing novel approaches for sensing and intervention in the context of mental health.

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UbiComp 2018 workshop

12th October, 2018


This workshop has already taken place. For the current year's workshop, please go here.

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. Toward this, 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 researchers interested in identifying, articulating, and addressing such issues and opportunities. Following the success of this workshop in the last two years, we aim to continue facilitating the UbiComp community in developing novel approaches for sensing and intervention in the context of mental health.

Call For Participation

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 well-being data.

  • Investigating new methodologies for intervention (e.g., conversational agents, AR and VR applications).

  • Automated inference from sensor data of high-level contexts (e.g., environmental, social) indicative of mental health status.

  • Design and implementation of feedback (e.g., reports, visualizations, proactive behavioral interventions, subtle or subconscious interventions) for both patients and caregivers.

  • Development of robust behavioral models that can handle data sparsity and mislabeling issues.

  • Integration of multimodal data from different sensor streams for personalized predictive modeling.

  • Methods for sustaining user adherence and engagement over long periods of time.

  • Devising privacy-preserving strategies for data collection, analysis, and management.

  • Deployment in low-income communities and countries.

  • Identifying ways to better integrate ubiquitous technologies into existing healthcare infrastructures and government policy.

Important Dates

  • Submission deadline: July 20th, 2018 (11:59 PM PDT)

  • Decisions to authors: August 8th, 2018

  • Camera-ready deadline: August 15th, 2018

Paper Format

Regular (up to 9 pages) or short (up to 5 pages) paper using SIGCHI Extended Abstract format. Papers should be in PDF format and not anonymized.

Submission Site

Submissions can be made at

Submission Options

All accepted papers will be included in the ACM Digital Library as part of the UbiComp conference supplemental proceedings. Papers will be reviewed by the workshop's technical program committee according to criteria regarding a submission's quality, relevance to the workshop's topics, and, foremost, its potential to spark discussions about directions, insights, and solutions in the context of mental health, sensing, and intervention. Research papers, case studies, and position papers are all welcome.

In particular, we encourage authors to keep the following options in mind when preparing submissions:

  • Works-In-Progress: To facilitate sharing of thought-provoking ideas and high-potential though preliminary research, authors are welcome to make submissions describing early-stage, in-progress, and/or exploratory work in order to elicit feedback, discover collaboration opportunities, and generally spark discussion.

  • Special Issue on Computing and Mental Health in the Journal of Medical Internet Research (JMIR): When submitting to the workshop, authors will have the option to specify if they would like an expanded version of their paper to be considered for inclusion in an upcoming special issue in JMIR dedicated to the topic of computing and mental health. Authors selected for inclusion would then be invited to expand their workshop submission to a full length manuscript of no more than 7,500 words, due in mid-Fall 2018. This JMIR special issue will also include manuscripts produced through a similar solitication from the related workshop on Computing and Mental Health held annually at CHI.


Time Event
9:30–10:00 Correlations between objective behavioral features and depression (Jakob E. Bardram)
10:00–10:30 Paper presentations
10:30–11:00 Coffee break
11:00–12:00 Poster session
12:00–13:30 Mentoring lunch with organizers and senior researchers
13:30–14:00 From mobile phone based monitoring and prediction of depressive states to data-driven behaviour interventions (Mirco Musolesi)
(coffee break at 15:00)
Focused session and group discussion
Potential themes:
  • Study design and evaluation
  • IoT and mental health
  • Integrating with clinical care
  • Long term engagement and adherence
  • Best practices for intervention design
16:00–17:30 Discussion
Potential topics:
  • Funding strategy
  • Publishing strategy
  • Entrepreneurship and commercialization
  • Interdisciplinary collaboration strategy
17:30–17:40 Closing remarks
19:00 Dinner

Program Committee

  • Hane Aung, Cornell University

  • Jean Costa, Cornell University

  • Szymon Fedor, MIT

  • Asma Ghandeharioun, MIT

  • Javier Hernandez Rivera, MIT

  • Hirohiko Suwa, NAIST

  • Sara Taylor, MIT

  • Mizumoto Teruhiro, NAIST

  • Terumi Umematsu, MIT/NEC Corporation

  • Oliver Wilder, MIT


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Saeed Abdullah

Assistant Professor, Penn State.

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Jakob E. Bardram

Professor, Technical University of Denmark.

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Sandra Servia

Research Associate, University of Cambridge.

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Akane Sano

Assistant Professor, Rice University.

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Elizabeth Murnane

Postdoctoral Scholar, Stanford University.

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Tanzeem Choudhury

Associate Professor in Information Science, Cornell University.

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Mirco Musolesi

Reader in Data Science, UCL.


If you have any questions, please feel free to send an email to