FW-HTF-P: Adapting to the Future of Robotic Surgery: Understanding Training and Design Environments for Human-Robot Teams

机器人辅助手术设备（RASD）使外科医生能够使用计算机和软件技术对各种手术器械进行先进的可视化和控制，与传统手术相比，减少了手术的侵入性。然而，在外科手术环境中成功采用这种创新技术需要考虑工人培训、工作流程和其他潜在的接受障碍。这项工作为未来外科机器人技术与人-机器人团队的整合奠定了基础。该项目开发提案涉及一个多学科团队，其目标是：1)了解当前人机工作系统的态度、障碍和促进因素；2)整合专家对加强rasd采用的挑战和机遇的观点；3)验证基于统计学习的训练模型；4)为RASD集成工作系统的未来发展创建一个框架。了解手术环境中所有工作人员的态度和需求对于实施和评估人机协作团队以提高手术安全性和效率至关重要。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Robotic-assisted surgical devices (RASD) enable surgeons to use computer and software technology for advanced visualization and control of surgical instruments for a variety of procedures, decreasing the invasiveness of the procedure compared to traditional surgery. However, the successful adoption of this innovative technology into surgical environments requires consideration of worker training, workflow, and other potential barriers to acceptance. This work establishes a foundation for the future integration of surgical robotic technology into human-robot teams.This project development proposal involves a multidisciplinary team who aims to 1) understand attitudes, barriers, and facilitators of current human-robot work systems; 2) integrate expert perspectives on challenges and opportunities for enhancing the adoption of RASDs; and 3) validate a training model based on statistical learning; and 4) create a framework for future development of RASD integrated work systems. Understanding attitude and needs of all workers in a surgical setting is critical for implementing and evaluating human-robot collaborative teams to improve surgical safety and efficiency.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.