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Award details
- Awarding agency
- Department of Health and Human Services
- Branch
- National Institutes of Health
- Recipient company
- Neural Analytics, Inc.
- Proposal award date
- 2016-08-01
- Contract end date
- 2019-07-31
- UEI
- ZTWAFG7JB775
- Solicitation number
- PA15-269
- Topic code
- 101
Research abstract
Project Summary Abstract
Between and million people each year suffer a mild TBI in the US alone Reliable diagnosis and prompt
treatments are vital to managing the often serious short and long term sequelae resulting from mild TBI
However a reliable objective and accurate method for mild TBI diagnosis outside of a hospital setting and in
particular for determining RTP readiness has eluded the clinical community Current diagnosis and RTP
assessments are based on patient symptoms neurocognitive evaluations and or physical performance
testing Use of symptom scales are problematic for several reasons including subjectivity and reliability
Neurocognitive evaluations and physical tests such as balance tests although less subjective require pre
injury baseline testing of subjects due to inherently large subject to subject variations in evaluation
performances Due to these reasons current mild TBI diagnostic methods have limited applications and are
not suitable for a significant majority of patients who suffer mild TBI
This project is aimed at developing an objective diagnosis of mild traumatic brain injury mild TBI based on
physiologic changes in a patient after injury and providing a platform capable of RTP guidance The method is
based on quantification of well known physiologic changes after a concussion i e the impairment of autonomic
function and altered cerebral blood flow CBF as measured with transcranial Doppler TCD The novelty of
the proposed approach is the use of a recently developed analytical machine learning framework for the
analysis of the CBF velocity CBFV waveforms In contrast to previous methods used before the proposed
approach utilizes the entire shape of the complex CBFV waveform thus obtaining subtle changes in blood flow
that are lost in other analysis methods Additionally comprehensive verification between our platform and MRI
will be performed following injury resulting in the first scientific experiments of this kind
The ultimate goal of this Phase II SBIR is to commercialize an objective and accurate software algorithm for
reliable diagnosis and management of sports concussions which does not currently exist The outcome will be
a software suite integrated into existing TCD and will be marketed to emergency departments neurology
clinics and other healthcare providers involved in mild TBI diagnosis and RTP management Project Narrative
Traumatic brain injury TBI is a serious public health problem in the United States contributing to a
substantial number of deaths and cases of permanent disability Mild TBI concussions account for over
of all TBIs sustained and a major problem is the high rate of mis diagnosis due to lack of objective
measures and delayed onset of symptoms This project aims to develop the first objective concussion
evaluation method using a novel analysis platform that can obtain subtle physiologic changes in
cerebral hemodynamics Successful completion of this project will result in a portable diagnostic device
suitable for use in many scenarios where concussion diagnosis is inaccurate or unavailable today
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.
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
Research funding history
6 SBIR/STTR records share this UEI (2015–2020). Reported award amounts total $4,955,483. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Health and Human Services, National Science Foundation
Agency intelligence
Department of Health and Human Services
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