课题基金 / 基金详情

SBIR Phase II: Quantification of Operative Performance via Simulated Surgery, Capacitive Sensing, and Machine Learning to Improve Surgeon Performance & Medical Device Develop

SBIR Phase II: Quantification of Operative Performance via Simulated Surgery, Capacitive Sensing, and Machine Learning to Improve Surgeon Performance & Medical Device Develop
SBIR 第二阶段:通过模拟手术、电容传感和机器学习量化手术表现,以提高外科医生的表现
批准号:
2223976
负责人:
Hannah Eherenfeldt
金额:
$99.64万
依托单位:
依托单位国家:
美国
项目类别:
Cooperative Agreement
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-03-01 至 2025-02-28

项目摘要

项目成果

Hannah Eherenfeldt的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve surgical skill acquisition, assessment of surgical performance, and medical device training. The apprenticeship-based model of surgical training has created inefficiencies in the medical device and healthcare industries. This problem is exacerbated by the evolving complexity and specialization of surgical procedures and devices. The proposed technology combines lifelike, physical simulated procedures, novel sensing technologies, and machine-learned data analytics to address a universal market need for data-driven training. The technology developed during this project will result in surgical simulation platforms to improve procedural competency and the ability to practice device deployment outside of the operating room, while providing critical data-driven insight into surgical performance and quantitative evaluation. Ultimately, this solution could reduce patient costs, improve outcomes, and expedite medical device development and adoption. The proposed project will result in the development of a comprehensive system that collects data and evaluates vascular surgical operative performance in both the open and endovascular fields. An open vascular surgery simulation platform previously developed to train surgeons will be expanded to include endovascular procedures and the integration of capacitive sensors to capture a comprehensive set of operative performance data. This project aims to use artificial intelligence to classify key performance metrics from the collected dataset to build a comprehensive model to classify operative performance. A data-driven platform for surgical training and medical device development is not currently commercially available and the industry currently relies on increasingly cost-prohibitive means to provide vital surgical training.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.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
SBIR Phase I: Open Vascular Surgical Training System for Skill Acquisition and Evaluation
  • 批准号:
    2035945
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.35万
  • 财政年份:
    2021
  • 负责人:
    Hannah Eherenfeldt
  • 依托单位:
国内基金
海外基金
Baryogenesis, Dark Matter and Nanohertz Gravitational Waves from a Dark Supercooled Phase Transition
  • 批准号:
    24ZR1429700
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    YUICHIRO NAKAI
  • 依托单位:
ATLAS实验探测器Phase 2升级
  • 批准号:
    11961141014
  • 项目类别:
    国际(地区)合作与交流项目
  • 资助金额:
    3350万元
  • 批准年份:
    2019
  • 负责人:
    刘衍文
  • 依托单位:
地幔含水相Phase E的温度压力稳定区域与晶体结构研究
  • 批准号:
    41802035
  • 项目类别:
    青年科学基金项目
  • 资助金额:
    12.0万元
  • 批准年份:
    2018
  • 负责人:
    张里
  • 依托单位:
基于数字增强干涉的Phase-OTDR高灵敏度定量测量技术研究