SBIR/STTR Research Award
CorBand A novel wearable wrist sensor for heart failure remote monitoring
Award amount
$1,499,469Program and phase
SBIR · Phase IIAward year
2016Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- RETHINK MEDICAL, INC.
- Proposal award date
- 2016-08-22
- Contract end date
- 2019-07-31
- UEI
- Not reported
- Solicitation number
- PA15-269
- Topic code
- NHLBI
Research abstract
ReThink Medical Inc proposes to develop an ambulatory version of the physiologic monitoring technology it
validated in Phase I the CorBand The CorBand is designed to track key physiologic parameters that are
predictive of cardiac decompensation to detect the early stages of decompensation and to relay both the
physiologic data and generated alerts to relevant caregivers with the end goal of reducing hospitalizations by
enabling proactive preventative care in the heart failure population Heart failure effects million individuals
in the US and the costs associated are approaching $ billion annually This technology will not only improve
the quality of life for heart failure patients but also help to reduce this massive burden on the US healthcare
system Our long term objective is to help drive the transformation from the reactive pay for service healthcare
paradigm to one that puts emphasis on preventative care through health monitoring technologies Our specific
aims include manufacturing a robust version of the device for use in two large long term ambulatory
studies It will be validated using patients who have cardiac implantable electronic devices CIEDs Heart
rate HR heart rate variability HRV activity levels and fluid index derived from the CorBand will be
compared with data collected from CIEDs manufactured by Medtronic and Boston Scientific and analyzed for
correlation The CorBand will be deployed in a large ambulatory population of HF patients We will collect
the patientandapos s clinical notes and note hospitalization events along with remote physiologic data from the
CorBand We will use this data to further build a predictive model for cardiac decompensation using a number
of machine learning approaches In aim we will perform a controlled study on a population of HF patients
All the subjects will wear the CorBand we will use the data from half the subjects to predict decompensation
events provide that information to subjectandapos s caregiver in order to provide preventative care The other half will
receive usual care We will then examine the number of HF related hospitalizations in both groups to evaluate
the ability of the CorBand to reduce hospitalizations Our goal is to simplify the management of heart failure while improving the quality of care of the patients and
reducing the associated costs We will investigate the benefits of a novel non invasive multi parameter sensor
with telemetry for monitoring patients with heart failure combined with an algorithm for detecting early stage
cardiac decompensation with a goal of preventing hospitalizations
Technology keywords
Not reported
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