I-Corps: Artificial Intelligence and Haptic-Enabled Robotic Assistant for Surgeons

I-Corps：外科医生的人工智能和触觉机器人助手

• 批准号: 2330934
• 负责人: Ann Majewicz Fey
• 金额: $ 5万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2330934&HistoricalAwards=false
• 关键词: Corps; Artificial; Intelligence; Haptic; Enabled

The broader impact/commercial potential of this I-Corps project is the development of a wearable system capable of sensing and analyzing motion data of surgeons and surgical trainees to provide online, haptic guidance feedback on how to improve surgical performance. Robotic surgery remains a complex and demanding psychomotor task that requires extensive training to master. In addition, a growing shortage within the surgical workforce adds to the challenge of providing comprehensive training. The proposed technology is designed to help surgeons improve their surgical skills. This technology may be particularly useful in rural areas or those impacted by surgeon workforce shortages as access to well-trained surgeon experts is limited. The goal is to make it easier and safer for surgeons to learn and use surgical robots by lowering the barrier for surgeons to learn and use surgical robots through developing online analytics and haptic feedback strategies, ultimately improving patient outcomes.This I-Corps project is based on the development of artificial intelligence (AI) and haptic enabled wearable technology to assist with analyzing surgical motions and providing surgical skill guidance in near real-time. The proposed technology uses human-centered, data driven models for surgical movement analysis and context awareness. These models are designed to detect a range of behaviors, including stylistic behaviors, expertise levels, bimanual coordination, and stress levels of surgeons during robotic surgery and training. The models leverage machine learning, deep learning, and mathematical methods to analyze kinematic data from surgical robots and their operators in real time, making them unique in their ability to provide immediate feedback and guidance using visual and haptic technologies to surgeons, augmenting their surgical performance. This technology has the potential to greatly reduce the training required to operate surgical robots effectively, making it easier for surgeons to integrate this technique into their practice. In addition, the proposed technology has the potential to improve patient outcomes by minimizing the risk of surgical errors and complications. The real-time feedback and guidance provided by the system enable surgeons to make more accurate and informed decisions during surgeries, reducing the likelihood of errors and complications. This has the potential to improve patient safety and reduce the need for postoperative interventions, ultimately leading to better clinical outcomes.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.

该I-Corps项目的更广泛的影响/商业潜力是开发可穿戴系统，能够感知和分析外科医生和外科学员的运动数据，以提供有关如何改善手术性能的在线，触觉指导的反馈。 机器人手术仍然是一项复杂且苛刻的心理运动任务，需要进行广泛的培训才能掌握。 此外，手术劳动力中日益增长的短缺增加了提供全面培训的挑战。 拟议的技术旨在帮助外科医生提高其手术技能。由于训练有素的外科医生专家的访问是有限的，因此该技术在农村地区或受外科医生劳动力短缺的影响方面可能特别有用。 The goal is to make it easier and safer for surgeons to learn and use surgical robots by lowering the barrier for surgeons to learn and use surgical robots through developing online analytics and haptic feedback strategies, ultimately improving patient outcomes.This I-Corps project is based on the development of artificial intelligence (AI) and haptic enabled wearable technology to assist with analyzing surgical motions and providing surgical skill guidance in near 即时的。提出的技术使用以人为中心的数据驱动模型来进行手术运动分析和环境意识。这些模型旨在检测一系列行为，包括在机器人手术和训练期间外科医生的外科医生的风格行为，专业水平，双人协调水平以及压力水平。这些模型利用机器学习，深度学习和数学方法来实时从外科机器人及其操作员分析运动学数据，从而使它们在使用视觉和触觉技术向外科医生提供直接反馈和指导的能力方面具有独特性，从而增强了外科手术性能。该技术有可能大大减少有效操作手术机器人所需的训练，从而使外科医生更容易将此技术整合到他们的实践中。此外，提出的技术有可能通过最大程度地减少手术错误和并发症的风险来改善患者的预后。系统提供的实时反馈和指导使外科医生能够在手术过程中做出更准确和明智的决定，从而减少了错误和并发症的可能性。这有可能提高患者的安全性并减少术后干预的需求，最终导致更好的临床结果。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估来支持的。