Mobile Technologies Core
Empowering mental health research for improved treatment and prevention.
Mobile technologies have the potential to transform mental health research and precision treatments.
Combining mobile apps and devices such as wearables enables the collection of mental health health assessments alongside other objective physiological signals and social parameters, allowing long-term research to be done at scale with greater participation. These technologies also hold the promise to help develop more dynamic, real-time, individualized mental health treatments.
The Mobile Technologies Core facilitates effective, rigorous, equitable, and reproducible mental health research using mobile technologies. Our aim is to empower researchers across the University of Michigan to transform the future of mental health treatment and prevention by overcoming the barriers of incorporating mobile technologies in their studies. The Mobile Technologies Core is partnering across the University to build the infrastructure necessary to make this a reality.
Our Services
Our dedicated faculty and staff provide expert guidance and best practices for Eisenberg Family Depression Center members interested in using mobile technologies in their research:
Research Proposal Ideation and Development »
Providing resources and support in developing competitive, cutting-edge proposals.
Mobile Study Expertise: Technology Selection and Use »
Resources and expertise to help investigators select technologies that meet their research objectives.
Mobile Data Standardization, Processing, and Access »
Learnings on the collection, extraction, storage, processing, and display of the large amount of high resolution data acquired by mobile technologies.
Connection, Dissemination, and Education »
Get connected to collaborative networks and dedicated faculty and staff support.
Questions and topics to get started:
Why use mobile technologies in your research
Mobile health technologies offer advantages like the ability to assess various measures together, both objectively (e.g. wearable sensors) and with self-report (e.g. app acquired ecological momentary assessment).
Data collection methods of mobile technologies are unique compared to traditional research tools, and can acquire long-term data in free-living conditions, often with minimal effort on the part of the study participant. Meta-data is continually collected alongside the research parameters of interest which enrich the data with contextual information.
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Elements of research with mobile technologies
The Mobile Technologies Core will provide support and share expertise for the following technologies and technology applications.
- Off-the-shelf wearables and other mobile monitoring devices
- 3rd party apps and websites
- Smartphones
- Used to deploy apps
- Contain native sensors to collect data (microphone, gyroscope, etc).
- Artificial Intelligence (AI)
- Automate participant data collection and deploy interventions through apps
- ie: Chatbot
- Al algorithms
- Used by mobile technologies at multiple levels, including:
- AI analysis of wearable signals to derive meaningful quantities (i.e. total sleep times)
- AI analysis of health metrics (i.e. total sleep time) obtained from wearables combined with data derived from apps (i.e. self-report mood levels) along with other metadata (big data analysis)
- Used by mobile technologies at multiple levels, including:
- Automate participant data collection and deploy interventions through apps
- Telemedicine
- Studies using wearables and telemedicine for delivery of care.
Faculty interested in developing apps for commercialization should visit: UM Innovation Partners
Connect with the Mobile Technologies Core:
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