A5075473434- Behavioral Health and Interventions
- Mobile Health and mHealth Applications
- Physical Activity and Health
- Innovative Human-Technology Interaction
- Digital Mental Health Interventions
- Diabetes Management and Research
- Persona Design and Applications
- Recommender Systems and Techniques
- Mental Health Research Topics
- Innovative Approaches in Technology and Social Development
- Context-Aware Activity Recognition Systems
- Community Health and Development
- Design Education and Practice
- Obesity, Physical Activity, Diet
- Pancreatic function and diabetes
- Technology Use by Older Adults
- Mobile Learning in Education
- Behavioral and Psychological Studies
- Genomics and Phylogenetic Studies
- Diabetes and associated disorders
- Green IT and Sustainability
- Speech and dialogue systems
- Digital Innovation in Industries
- Team Dynamics and Performance
- Health, Environment, Cognitive Aging
Arizona State University
2017-2020
University of California, San Diego
2019
Phoenix Houses of New England
2018
American College of Surgeons
2018
Georgetown University
2017
Background: Adaptive behavioral interventions are individualized that vary support based on a person's evolving needs. Digital technologies enable these adaptive to function at scale. show great promise for producing better results compared with static related health outcomes. Our central thesis is more likely succeed helping individuals meet and maintain targets if its elements can be iteratively improved via data-driven testing (ie, optimization). Control systems engineering discipline...
Fungal infections are a global problem imposing considerable disease burden. One of the unmet needs in addressing these is rapid, sensitive diagnostics. A promising molecular diagnostic approach high-resolution melt analysis (HRM). However, there has been little effort leveraging HRM data for automated, objective identification fungal species. The purpose studies was to assess utility distance methods developed comparison time series classify curves as means species identification. Dynamic...
There is significant evidence to show that physical activity reduces the risk of many chronic diseases. With rise mobile health (mHealth) technologies, one promising approach design interventions are responsive an individual's changing needs. This overarching goal Just Walk, intensively adaptive intervention has been designed on basis system identification and control engineering principles. Features this include use multisine signals as pseudo-random inputs for providing daily step goals...
Although group-level evidence supports the use of behavioral interventions to enhance cognitive and emotional well-being, different may be more acceptable or effective for people. N-of-1 trials are single-patient crossover designed estimate treatment effectiveness in a single patient. We mobile health (mHealth) supported trial platform permitting US adult volunteers conduct their own 30-day self-experiments testing intervention choice (deep breathing/meditation, gratitude journaling,...
Background: A method to calculate changes in insulin needs was developed the OpenAPS (Open Source Artificial Pancreas System) community. Individuals have natural fluctuations needs, but excessive periods of sensitivity or resistance may indicate ongoing physiological trends and therefore impact T1D management. Methods: Autosens analyzes each CGM data point for 24 hours, comparing observed change expected from insulin. calculates deviation median last 8 hours points determines ratio (SR)...
As the DIS community increasingly seeks to address social impact issues, it becomes important examine assumptions behind our methods increase likelihood of positive effects and reduce negative unintended consequences. The purpose this workshop is engage design in exploring, defining, and, if deemed valuable, advancing community-driven design. We invite members submit 1-page responses concept Our hope that a research agenda can emerge from for community.
This book will give you a practical overview of several methods and approaches for designing mobile technologies conducting user research, including how to understand behavior evaluate
Many behavioral interventions can improve health and wellbeing. However, behavior change is complex multifaceted, not all work for everyone. Most evidence popular from group-based studies, which poorly predict whether a given intervention would s
PURPOSE: The study aimed to (a) examine the effect of momentary affective states on workplace sedentary behavior (WSB); and (b) test proximal effects email-based prompts WSB. METHODS: Office workers with sit-stand desks were recruited in a two-part 20-workday study. In part A, participants completed ecological assessments (EMA; at 3 random times/day) states. Each EMA response was matched behavioral outcomes (i.e., time spent sedentary, standing, or moving proceeding each response). Part B...