Project D1; R3
Objective: To demonstrate the feasibility of using a mobile-phone application (app) to assess mobility and social interactions of stroke survivors within their communities.
Stroke is the leading cause of adult-onset disabilities. Returning to prior levels of function, specifically independent mobility both at home and in the community, remains a priority to most stroke survivors. In addition, recovery of mobility is a significant factor in determining the level of disability following stroke.
For non-institutionalized stroke survivors living in the United States, rehabilitation is focused on physical therapy interventions aimed at improving mobility and walking performance. The overall goal is to reintegrate stroke survivors into society, employment, and economic and social independence. However, development of therapeutic interventions is limited by a lack of quantitative, informative outcome measures.
Currently, self-selected walking speed
is considered the most important measure of stroke rehabilitation and is thought to be a predictor of health status, community mobility, social interaction, and overall quality of life.
However, numerous advanced therapeutic interventions for stroke survivors have not resulted in statistically significant changes in walking speed. This suggests that walking speed might not be a sensitive enough measure to quantify all functional improvements following therapy.
Furthermore, deficits in balance, coordination, and cognition and visuospatial changes that affect mobility following stroke may not be reflected by gait speed measures. Stroke is a very heterogeneous condition with a large population of non-ambulatory stroke survivors who use assistive technology for mobility in the community but would be deemed non-mobile if evaluated using gait speed.
Finally, community and home mobility are affected by other social, environmental, and personal factors. Thus, to determine the effectiveness of rehabilitation interventions following stroke, there is a compelling need to accurately quantify mobility and assess social interactions at home and in the community.
Our study will focus on measuring home and community mobility in stroke survivors; however, the mobile phone technology we develop could be used in any population of individuals with any mobility-limiting disability.
We will update this page periodically with research news and related interviews.
Jayaraman A., “Monitoring Health Using Wearable Technology.” Cyberinfrastructure & Center on Health, Aging, and Disability, University of Illinois at Urbana-Champaign, May 2015.
Miller C, and Poellabauer C., "Configurable Integrated Monitoring System for Mobile Devices", Proc. of the 11th International Conference on Mobile Systems and Pervasive Computing (MobiSPC), Niagara Falls, Canada, August 2014.
"Assessing Quality of Life Using Smartphone Sensing" (2014 RESNA Conference Presentation PDF)
Arun Jayaraman, PT, PhD, Principal Investigator Dr. Jayaraman is director of the Max Nader Center for Rehabilitation Technologies & Outcomes within the Center for Bionic Medicine, and an assistant professor in the departments of Physical Medicine & Rehabilitation and Medical Social Sciences at Northwestern University. His research focuses on developing and executing both industry-sponsored and investigator-initiated research in rehabilitation robotics, prosthetics, and other assistive and adaptive technologies to treat physical disability. He specifically focuses on using quantitative outcome measures to improve the real-world use of rehabilitation technology. Dr. Jayaraman received his PhD in Rehabilitation Sciences from the University of Florida.
Konrad Kording, PhD, Co-Investigator Dr. Kording is a research scientist within the Sensory Motor Performance Program (SMPP) at RIC, Director of the Bayesian Behavior Lab, and an Associate Professor in the Departments of Physical Medicine & Rehabilitation and Biomedical Engineering at Northwestern University. His work includes studying how people move and how their movements are affected by uncertainty. He builds computational models using Bayesian statistics to calculate how people could move optimally or learn to move optimally. He has constructed algorithms that analyze movements, neural connectivity, and everyday life. Dr. Kording obtained his PhD from ETH Zurich, Switzerland.
Christian Poellabauer, PhD, Co-Investigator Dr. Poellabauer is an Associate Professor in the department of Computer Science and Engineering at the University of Notre Dame and co-founder of CloverApps LLC, Contect, Inc., and CNVRS LLC, three software development companies focusing on mobile communication systems, mobile health, and social networking. His research interests are in the areas of mobile computing, wireless networks, sensor networks, pervasive computing, and healthcare technologies. He has published more than 100 papers in these areas and he has co-authored a textbook on Wireless Sensor Networks. Dr. Poellabauer received his Diplom-Ingenieur degree from the Vienna University of Technology, Austria and Ph.D. degree from the Georgia Institute of Technology, both in Computer Science.
Chaithanya Mummidisetty, MS, Engineering Project Leader.
Mr. Mummidisetty is a research engineer at the Center for Bionic Medicine. He received his bachelor's degree in biomedical engineering from Osmania University in India and an MS in biomedical engineering from the University of Miami. His research interests include gait rehabilitation for Stroke & Spinal Cord Injury patients, signal processing, new technology development, and outcomes research.
Additional staff members
Luca Lonini, PhD; Lori McGee Koch, Research Coordinator