UbiWell Lab

The Ubiquitous Computing for Health and Well-being (UbiWell) Lab is an interdisciplinary research group at the Khoury College of Computer Sciences and the Bouvé College of Health Sciences at Northeastern University.
We work on developing data-driven solutions to enable effective sensing and interventions for mental- and behavioral-health outcomes with mobile and ubiquitous technologies.

Research Areas

Our interdisciplinary team works at the intersection of mobile/wearable sensing, data science, human-centered computing, and behavioral science.

We work on exploring and advancing the complete "lifecycle" of mental- and behavioral-health sensing and intervention, which includes (a) accurately sensing and detecting a mental or behavioral health condition, like stress and opioid use; (b) after detecting a particular condition, determining the right time to deliver the intervention or support, such that the user is most likely to be receptive to the interventions provided; and (c) choosing the best intervention delivery mechanism and modality to ensure just-in-time delivery and reachability.

Sensing to intervention lifecycle

A simplified representation of the sensing to intervention lifecycle.

Current Projects

Causal modeling for physiological stress

Stress predictions from physiological signals

We are working on various projects to leverage multimodal data and understand the contextual and behavioral factors that lead to physiological stress, and evaluate its association with the perception of stress.

Predicting relapse during OUD treatment

Stress predictions from physiological signals

We are working on a longitudinal study to detect at-risk indicators, e.g., stress, craving, and mood, among patients undergoing Opioid Use Disorder (OUD) treatment, using passively collected contextual and sensor data from smartphones and wearables.

States-of-receptivity for digital health interventions

Stress predictions from physiological signals

We have multiple projects currently underway to better evaluate the contexts where people are willing and able to engage with and use digital health interventions. These range from behavior-change interventions in free-living situations to interventions during specific scenarios, e.g., driving.


(September 2022) Hello UbiWell!
The Ubiquitous Computing for Health and Well-being (UbiWell) lab is set up at Northeastern University.

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Recent Publications

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The Feasibility and Utility of Harnessing Digital Health to Understand Clinical Trajectories in Medication Treatment for Opioid Use Disorder: D-TECT Study Design and Methodological Considerations Lisa A. Marsch , Ching-Hua Chen , Sara R. Adams , Asma Asyyed , Monique B. Does , Saeed Hassanpour , Emily Hichborn , Melanie Jackson-Morris , Nicholas C. Jacobson , Heather K. Jones , David Kotz , Chantal A. Lambert-Harris , Zhiguo Li , Bethany McLeman , Varun Mishra , Catherine Stanger , Geetha Subramaniam , Weiyi Wu , Cynthia I. Campbell , Frontiers in Psychiatry 2022
Detecting Receptivity for mHealth Interventions in the Natural Environment Varun Mishra , Florian Künzler , Jan-Niklas Kramer , Elgar Fleisch , Tobias Kowatsch , David Kotz , Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT) 2021
When Do Drivers Interact with In-vehicle Well-being Interventions? An Exploratory Analysis of a Longitudinal Study on Public Roads Kevin Koch , Varun Mishra , Shu Liu , Thomas Berger , Elgar Fleisch , David Kotz , Felix Wortmann , Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT) 2021
FLIRT: A Feature Generation Toolkit for Wearable Data Simon Föll , Martin Maritsch , Federica Spinola , Varun Mishra , Filipe Barata , Tobias Kowatsch , Elgar Fleisch , Felix Wortmann. , Computer Methods and Programs in Biomedicine 2021
Evaluating the Reproducibility of Physiological Stress Detection Models Varun Mishra , Sougata Sen , Grace Chen , Tian Hao , Jeffrey Rogers , Ching-Hua Chen , David Kotz , Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. (IMWUT) 2020
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