2432686
Project Grant
Overview
Grant Description
SBIR Phase I: ECG-AID: Electrocardiogram with Advanced Interpretation and Diagnosis
The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an advanced software system for automated electrocardiogram (ECG) analysis.
By integrating a large dataset with a clear delineation of normal and abnormal values and innovative machine-learning models, this technology could improve the accuracy and accessibility of ECG interpretation.
The ECG-AID software is an inexpensive and user-friendly solution that provides accurate and reproducible automated ECG interpretation that may lead to timely diagnosis of heart disease.
The market for this innovation is significant, given that over 300 million ECGs are performed annually in the United States alone.
The commercial potential is projected revenues of $25 million by the third year of operation.
ECG-AID aims to promote national health and welfare by prioritizing rural healthcare facilities.
This Small Business Innovation Research (SBIR) Phase I project targets a pressing issue in the medical field: the potential inaccuracy of the diagnoses of heart conditions due to 1) a lack of specialized medical expertise leading to highly variable and inaccurate ECG interpretation and 2) outdated automated systems with poor predictive values.
The project proposes to develop an innovative software prototype that significantly enhances ECG diagnostic capabilities by integrating a comprehensive ECG database, Z-score-based assessments, and novel machine-learning techniques.
This project aims to facilitate the detection of subtle cardiac conditions that are often overlooked, resulting in earlier and more accurate clinical decisions.
Through a structured approach involving the design of algorithm sequences, user-friendly interpretations, and automated data extraction, the anticipated technical results in a state-of-the-art ECG analytic system could improve the overall diagnostic accuracy of ECG.
This prototype adds tremendous value to an inexpensive and fast test: allowing the development of large-scale high-throughput screenings, it will transform the role of ECGs in standard practice.
By fulfilling these objectives, the ECG-AID project is positioned to revolutionize cardiovascular diagnostics, ultimately leading to better patient outcomes and a substantial societal impact.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an advanced software system for automated electrocardiogram (ECG) analysis.
By integrating a large dataset with a clear delineation of normal and abnormal values and innovative machine-learning models, this technology could improve the accuracy and accessibility of ECG interpretation.
The ECG-AID software is an inexpensive and user-friendly solution that provides accurate and reproducible automated ECG interpretation that may lead to timely diagnosis of heart disease.
The market for this innovation is significant, given that over 300 million ECGs are performed annually in the United States alone.
The commercial potential is projected revenues of $25 million by the third year of operation.
ECG-AID aims to promote national health and welfare by prioritizing rural healthcare facilities.
This Small Business Innovation Research (SBIR) Phase I project targets a pressing issue in the medical field: the potential inaccuracy of the diagnoses of heart conditions due to 1) a lack of specialized medical expertise leading to highly variable and inaccurate ECG interpretation and 2) outdated automated systems with poor predictive values.
The project proposes to develop an innovative software prototype that significantly enhances ECG diagnostic capabilities by integrating a comprehensive ECG database, Z-score-based assessments, and novel machine-learning techniques.
This project aims to facilitate the detection of subtle cardiac conditions that are often overlooked, resulting in earlier and more accurate clinical decisions.
Through a structured approach involving the design of algorithm sequences, user-friendly interpretations, and automated data extraction, the anticipated technical results in a state-of-the-art ECG analytic system could improve the overall diagnostic accuracy of ECG.
This prototype adds tremendous value to an inexpensive and fast test: allowing the development of large-scale high-throughput screenings, it will transform the role of ECGs in standard practice.
By fulfilling these objectives, the ECG-AID project is positioned to revolutionize cardiovascular diagnostics, ultimately leading to better patient outcomes and a substantial societal impact.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.
Subawards are planned for this award.
Awardee
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "NSF SMALL BUSINESS INNOVATION RESEARCH (SBIR)/ SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAMS PHASE I", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF23515
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Honolulu,
Hawaii
96821-1009
United States
Geographic Scope
Single Zip Code
KAI Tech was awarded
Project Grant 2432686
worth $275,000
from National Science Foundation in September 2024 with work to be completed primarily in Honolulu Hawaii United States.
The grant
has a duration of 8 months and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
The Project Grant was awarded through grant opportunity NSF Small Business Innovation Research / Small Business Technology Transfer Phase I Programs.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I: ECG-AID: Electrocardiogram with Advanced Interpretation and Diagnosis
Abstract
The broader impact / commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to develop an advanced software system for automated electrocardiogram (ECG) analysis. By integrating a large dataset with a clear delineation of normal and abnormal values and innovative machine-learning models, this technology could improve the accuracy and accessibility of ECG interpretation. The ECG-AID software is an inexpensive and user-friendly solution that provides accurate and reproducible automated ECG interpretation that may lead to timely diagnosis of heart disease. The market for this innovation is significant, given that over 300 million ECGs are performed annually in the United States alone. The commercial potential is projected revenues of $25 million by the third year of operation. ECG-AID aims to promote national health and welfare by prioritizing rural healthcare facilities.
This Small Business Innovation Research (SBIR) Phase I project targets a pressing issue in the medical field: the potential inaccuracy of the diagnoses of heart conditions due to 1) a lack of specialized medical expertise leading to highly variable and inaccurate ECG interpretation and 2) outdated automated systems with poor predictive values. The project proposes to develop an innovative software prototype that significantly enhances ECG diagnostic capabilities by integrating a comprehensive ECG database, Z-score-based assessments, and novel machine-learning techniques. This project aims to facilitate the detection of subtle cardiac conditions that are often overlooked, resulting in earlier and more accurate clinical decisions. Through a structured approach involving the design of algorithm sequences, user-friendly interpretations, and automated data extraction, the anticipated technical results in a state-of-the-art ECG analytic system could improve the overall diagnostic accuracy of ECG. This prototype adds tremendous value to an inexpensive and fast test: allowing the development of large-scale high-throughput screenings, it will transform the role of ECGs in standard practice. By fulfilling these objectives, the ECG-AID project is positioned to revolutionize cardiovascular diagnostics, ultimately leading to better patient outcomes and a substantial societal impact.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Topic Code
DH
Solicitation Number
NSF 23-515
Status
(Complete)
Last Modified 9/25/24
Period of Performance
9/15/24
Start Date
5/31/25
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2432686
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
J3YRPULEXSF6
Awardee CAGE
90W20
Performance District
HI-01
Senators
Mazie Hirono
Brian Schatz
Brian Schatz
Modified: 9/25/24