Harness big data and develop remote health technologies to study the multi-complexities of mobility loss with the Digital Health and Artificial Intelligence (DIAL-AI) Core.
The DIAL-AI Core helps you meet the evolving needs of digital health approaches that include big data, health technologies and the exciting realm of mobile health. Imagine a digital fusion of geriatrics, gerontology, computer science, and biomedical engineering – that’s DIAL-AI in action. DIAL-AI drives innovation by:
- Developing, validating, and evaluating mobile health technology | We’re on a mission to pioneer new mobile health technologies, ensuring they stand up to scrutiny and deliver real benefits.
- Harvesting, warehousing, and analyzing complex digital data | We apply complex data analysis, where we gather and dissect data to promote mobility and independence in older adults.
- Apply artificial intelligence approaches: We work with dense datasets that are ideal for designing AI predictive tools that reduce mobility loss in late life.
Our goals align with major national strategies for advancing artificial intelligence R&D and other emerging technologies to support an aging population.
The DIAL-AI Core specializes in mobile-based software development and modeling multimodal data, including high-resolution sensor data and “unstructured data,” like physician notes. These unique capabilities are becoming essential tools in clinical research.
Connectivity and Assessment
DIAL-AI plays a pivotal role by developing customized applications for remote-based data collection and mHealth interventions. One standout achievement is the Real-time Online Assessment and Mobility Monitor (ROAMM) platform, offering continuous connectivity and bidirectional interactivity through a smartwatch. This innovative app not only captures mobility with sensors but also provides valuable contextual information and insights through ecological momentary assessments.
In the age of COVID-19, remote health technology has gained widespread acceptance and is expected to play a critical role in large-scale assessments of mobility and symptom surveillance.
Wearable technology validation and remote health and mHealth services
- Mobile health software development and solutions – see ROAMM app
- Validation against “gold-standard” measures of energy expenditure via indirect calorimetry and visual observation
- The core conducts focus groups and key informant interviewing to evaluate the acceptance of new technology. These groups help to optimize the adherence and retention in future studies utilizing this technology.
- The core possesses two k5 Cosmed Indirect calorimeters for validation of wearable technology
DIAL-AI
The ROAMM Study
ROAMM is a customizable mobile platform designed for smartwatches that currently exist. Our approach is to bypass ownership of a device, by providing all hardware to participants. Broadly, the ROAMM platform consists of the watch and server applications developed by the UF Data Science & Applied Technology Core.
Mobility and activity measures using wearable technology
- Summary measures of physical activity include:
- Total physical activity time (any type of activity at any intensity)
- Time spent at specific intensities of physical activities
- Sedentary
- Light
- Light-moderate
- Moderate
- Moderate-vigorous
- Vigorous
- Mobility characterization
- Total steps per day
- Cadence (steps/min during active bout)
- Step bouts – steps taken at a specific pre-determined cadence
- Basic GPS monitoring and tracking
- Excursion size – average of maximum distance from the home for each excursion away from home
- Excursion span – average daily maximum distance between all recorded locations away from home. Measures travel clusters, independent of maximal distance traveled.
- Geographical information systems for combining mobility patterns with the contextual environment
- Geocoding and mapping according to CDC tracts
- Adjacency/distance measures – for measuring distances between places and mobility patterns
- Overlays – Points of interest (crime locations, walkways, sidewalks, parks, transportation services)
Core Leadership
Todd Manini, PhD
Professor; Division Chief
Clinical And Population Health Integration
Health Outcomes and Biomedical Informatics
Sanjay Ranka, PhD
Distinguished Professor,
Computer & Information Science & Engineering,
Herbert Wertheim College of Engineering
Please contact us with any specific concerns or requests.