SBIR/STTR Research Award

SBIR Phase I: Intelligent Personalized Monitoring of Ambulatory Human Biosignals

Award identifier d94cd3c1106b3d5354e2122e340e82314307675197ab7be525515793c5fb640bAwarding agency National Science Foundation

Award amount

$87,362

Program and phase

SBIR · Phase I

Award year

2008

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
Venture Gain
Proposal award date
Not reported
Contract end date
Not reported
UEI
CYNPDLHBJ2B5
Solicitation number
NSF 07-586
Topic code
EO

Research abstract

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 Current commercial telehealth devices and services are underpowered and technologically outdated, and furthermore do nothing to anticipate the problem of who will monitor the massive data streams that will come from widespread deployment of ambulatory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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

5 SBIR/STTR records share this UEI (2008–2009). Reported award amounts total $1,526,941. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation, Department of Health and Human Services

Agency intelligence

National Science Foundation

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