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

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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.