The National Institute for Disability, Independent Living, and Rehabilitation Research (NIDILRR
) awarded the LiveWell Rehabilitation Engineering Research Center Program (RERC
) to a team
from Duke University
, Shepherd Center
, and Northeastern University
. This program funds advanced engineering research and development of innovative technologies to solve rehabilitation problems or remove environmental barriers for people with disabilities. A multidisciplinary team of clinicians, engineers and researchers collaborate with Pratt School of Engineering, School of Medicine, Center for Cognitive Neuroscience, Center for the Study of Aging & Human Development, Durham Veterans Administration Medical Center, Navy Air Warfare Center Training Systems Division, and the Southeastern Federal Laboratory Consortium. The R&D program merges engineering and clinical aspects of ICT/AT technology design with outcomes research supported by federal, state, industry and philanthropic/development grants.Kevin Caves, ME ATP RET
, of the Physical Measures Core and his research colleagues, including Leighanne Jarvis, Sarah Moninger, Juliessa Pavon, MD
, and Chandra (Sandy) Throckmorton, PhD
, are defining and refining new technologies to assist in real-time assessment of physical activity. Here are samples of their research:
The Ecological Momentary Assessment
(EMA) App utilizes an accelerometer in a watch to monitor individual activity levels in people who have difficulty delivering accurate self-reports to their clinical team. Individuals may also respond to personalized activity surveys on their watch or smartphone to record type and time of activity.
[Ecological Momentary Assessment (EMA) App Poster]
Gait or walking speed
is a strong predictor of functional status and survival among older adults, but traditional measurement techniques may be prone to error between timers and trials. The Duke team is working to develop a low cost device that uses a LIDAR (Light Detection and Ranging) sensor and micro-controller to measure and display walking speed.
[Walking Speed Monitor Poster]
Movement and posture
have been found to be predictors of hospital re-admission. Researchers are fine-tuning algorithms used to classify posture, with particular attention to elderly populations.
may also be relayed to patients at risk of falling, e.g. Parkinson’s Disease patients, to improve posture. A trial study is planned for this population.
[Body Position Tracker poster]
[Accelerometer-based Positional Classification System poster]