The National Institutes of Health (NIH) has awarded an $10.8 million grant to launch a new initiative, called Mobile Sensor Data-to-Knowledge (MD2K), which will see a team of researchers working to better understand and develop tools that leverage data from health sensors and wearables. The team of researchers will be led by University of Memphis computer scientist Dr. Santosh Kumar.
This investment was a portion of a larger grant the NIH award as part of its Big Data to Knowledge (BD2K) initiative, which received a total of $32 million to find more uses for biomedical research data.
The MD2K team consists of computer science, engineering, statistical, and biomedical researchers from 11 universities. The researchers will use five wearable devices, mostly developed in-house, to study triggers and eventually develop tools to help reduce readmissions for congestive heart failure patients and to help prevent abstinent smokers from lighting up again. The study will take place over the next four years.
The wearable devices include a chest strap called AutoSense that measures ECG, respiration, and skin temperature; a wristworn activity tracker; radiofrequency sensor; smart glasses that offer near real-time tracking of the eye and its field of view; and GPS available through smartphones. All devices except the GPS-embedded smartphone were developed by the researchers.
During the first year of the initiative, Kumar told MobiHealthNews in an interview, the team plans to develop a platform on which to conduct the study.
"You should think of it as computational research," he said. "Multidisciplinary research that requires innovation in computer science, engineering, statistics, and health research. When you say a study, it seems much more like the biomedical discovery part, which is our goal -- to be able to facilitate discovery. But our goal is also to develop the tools that will facilitate discovery. The studies that we are doing are to collect the right data, develop these tools, and to do their evaluation. So, yes, we will be doing a study and our study will commence from year two when the first version of the system is ready."
The team's goal is to aggregate data from all the sensors and then develop analytic methods that turn this data into a reliable prediction of a person's risk of readmission or relapse.
"By doing this we will hopefully be able to avoid serious adverse health events," Kumar said. "We would like to go back in time even further and see what factors in the health behavior and environment precipitate these adverse health events and move towards prevention. Which means once we can discover those predictors in the environment that make a health situation worse, we can intervene way earlier, before someone becomes at risk for congestive heart failure. This applies to both congestive heart failure as well as smoking cessation."
After the first year, the researchers aim to be finished with their platform and at begin recruiting participants for the study.
In the second year of the study, the team will recruit 75 participants for congestive heart failure and 75 participants for smoking cessation. The researchers then plan to recruit another 75 each for the third and fourth year of the study so that by the end of four years, 225 people will have participated in the congestive heart failure study and 225 will have participated in the smoking cessation study.