2304526
Project Grant
Overview
Grant Description
Sbir Phase I: Surgical Training Platform with Customizable Training Scenarios Enabled by 3D Printing and Artificial Intelligence -The Broader Impact /Commercial Potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a customizable surgical training platform supported by artificial intelligence.
Existing surgical simulators allow trainees to practice in safe environments prior to operating on patients. These simulators are limited in recreating the challenges of the operating room and providing feedback to assess trainees' performance.
The technology developed in this project focuses on forming a better understanding of methods and techniques to recreate synthetic patient anatomy and how to provide higher quality assessments of surgical training procedures.
The project will provide a platform for improved medical training of medical students, residents, and surgeons that results in better skilled medical practitioners that deliver higher quality patient outcomes.
This Small Business Innovation Research (SBIR) Phase I project focuses on raising the quality of surgical training platforms by improving the realism of recreated anatomy and enabling scenario customization during training.
The project uses techniques of 3D printing, mechanical testing, and machine learning to characterize the properties of synthetic anatomy and objectively assess trainees' surgical performance for each scenario.
The artificial intelligence will be trained by mechanical measurements of synthetic anatomy before/after training operations from users.
Comparisons of surgical performance will be conducted between experienced, practicing surgeons and inexperienced/less experienced medical students.
The anticipated results are the development of a customizable surgical platform that provides objective feedback on a personalized basis to improve the standards of surgical practice among trainees.
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.
Existing surgical simulators allow trainees to practice in safe environments prior to operating on patients. These simulators are limited in recreating the challenges of the operating room and providing feedback to assess trainees' performance.
The technology developed in this project focuses on forming a better understanding of methods and techniques to recreate synthetic patient anatomy and how to provide higher quality assessments of surgical training procedures.
The project will provide a platform for improved medical training of medical students, residents, and surgeons that results in better skilled medical practitioners that deliver higher quality patient outcomes.
This Small Business Innovation Research (SBIR) Phase I project focuses on raising the quality of surgical training platforms by improving the realism of recreated anatomy and enabling scenario customization during training.
The project uses techniques of 3D printing, mechanical testing, and machine learning to characterize the properties of synthetic anatomy and objectively assess trainees' surgical performance for each scenario.
The artificial intelligence will be trained by mechanical measurements of synthetic anatomy before/after training operations from users.
Comparisons of surgical performance will be conducted between experienced, practicing surgeons and inexperienced/less experienced medical students.
The anticipated results are the development of a customizable surgical platform that provides objective feedback on a personalized basis to improve the standards of surgical practice among trainees.
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=NSF22551
Grant Program (CFDA)
Awarding / Funding Agency
Place of Performance
Amarillo,
Texas
79119-5434
United States
Geographic Scope
Single Zip Code
Related Opportunity
22-551
Surgic was awarded
Project Grant 2304526
worth $275,000
from National Science Foundation in September 2023 with work to be completed primarily in Amarillo Texas United States.
The grant
has a duration of 1 year and
was awarded through assistance program 47.084 NSF Technology, Innovation, and Partnerships.
SBIR Details
Research Type
SBIR Phase I
Title
SBIR Phase I:Surgical training platform with customizable training scenarios enabled by 3D printing and artificial intelligence
Abstract
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is the development of a customizable surgical training platform supported by artificial intelligence.Existing surgical simulators allow trainees to practice in safe environments prior to operating on patients. These simulators are limited in recreating the challenges of the operating room and providing feedback to assess trainees’ performance.The technology developed in this project focuses on forming a better understanding of methods and techniques to recreate synthetic patient anatomy and how to provide higher quality assessments of surgical training procedures.The project will provide a platform for improved medical training of medical students, residents and surgeons that results in better skilled medical practitioners that deliver higher quality patient outcomes._x000D_ _x000D_ This Small Business Innovation Research (SBIR) Phase I project focuses on raising the quality of surgical training platforms by improving the realism of recreated anatomy and enabling scenario customization during training.The project uses techniques of 3D printing, mechanical testing, and machine learning to characterize the properties of synthetic anatomy and objectively assess trainees’ surgical performance for each scenario.The artificial intelligence will be trained by mechanical measurements of synthetic anatomy before/after training operations from users.Comparisons of surgical performance will be conducted between experienced, practicing surgeons and inexperienced/less experienced medical students.The anticipated results are the development of a customizable surgical platform that provides objective feedback on a personalized basis to improve the standards of surgical practice among trainees._x000D_ _x000D_ 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 22-551
Status
(Complete)
Last Modified 9/22/23
Period of Performance
9/15/23
Start Date
8/31/24
End Date
Funding Split
$275.0K
Federal Obligation
$0.0
Non-Federal Obligation
$275.0K
Total Obligated
Activity Timeline
Additional Detail
Award ID FAIN
2304526
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Small Business
Awarding Office
491503 TRANSLATIONAL IMPACTS
Funding Office
491503 TRANSLATIONAL IMPACTS
Awardee UEI
ZRTHKEQK7HB6
Awardee CAGE
None
Performance District
TX-13
Senators
John Cornyn
Ted Cruz
Ted Cruz
Budget Funding
| Federal Account | Budget Subfunction | Object Class | Total | Percentage |
|---|---|---|---|---|
| Research and Related Activities, National Science Foundation (049-0100) | General science and basic research | Grants, subsidies, and contributions (41.0) | $275,000 | 100% |
Modified: 9/22/23