This Small Business Innovation Research (SBIR) Phase I project will demonstrate a continuous ambulatory human health monitoring system. The system is comprised of a wearable wireless sensing device and an advanced nonparametric machine learning algorithm called Similarity Based Modeling (SBM). SBM is applied to multivariate biosignals from humans (e.g., vital signs) gathered from the wearable device to provide unmatched real-time visibility into health status and sensitivity to incipient health problems. The SBM technology is trained to be specific to each individual?s normal vital signs characteristics. This ?personalization? capability of SBM increases the sensitivity at which subtle deviations from normality can be detected. SBM overcomes the monumental hurdle of digesting and autonomously monitoring massive data streams that will be generated as continuous ambulatory telehealth gains widespread acceptance. Traditional medical monitoring will fail at this, due to highly dynamic variation of continuous biosignals both for the individual (e.g., diurnal, activity-based variation) and across populations. Variation masks incipient anomalies and creates massive false-alert problem for conventional medical alert limits (the proverbial ICU alert overload). SBM learns normal personal human baseline to overcome this.

If successful the proposed work will address the existing problems in the ambulatory monitoring market. Current commercial telehealth devices and services are underpowered and technologically outdated, and furthermore do nothing to anticipate the problem of who will monitor the massive data streams that will come from widespread deployment of ambulatory monitoring. Home telehealth markets are poised to grow at a 5-year CAGR of 56% (compared to 9% for the clinical market), and exceed $8 Billion globally by 2012. The proposed solution will fit squarely into this space, as a cornerstone to an infrastructure that is actually able to service this incredible demand. The target customer base would include: Current home/ambulatory care services; hospitals (post-discharge and post-operative monitoring); ambulatory device manufacturers/vendors and related service companies; self-insureds (GM, LeapFrog members); the Veterans Administration; and the like. Furthermore, it is anticipated that a growing trend will emerge in the retail consumer market, with ordinary citizens investing in over-the-counter devices and monthly services enabling them to take charge of their own healthcare.

Agency
National Science Foundation (NSF)
Institute
Division of Industrial Innovation and Partnerships (IIP)
Type
Standard Grant (Standard)
Application #
0810751
Program Officer
Juan E. Figueroa
Project Start
Project End
Budget Start
2008-07-01
Budget End
2008-12-31
Support Year
Fiscal Year
2008
Total Cost
$87,362
Indirect Cost
Name
Venture Gain, LLC
Department
Type
DUNS #
City
Naperville
State
IL
Country
United States
Zip Code
60565