CAREER: Scientific Foundations for Augmented Human Performance in Robotic Surgery

有些外科手术是具有挑战性的，因为它们要求仪器控制的速度和精度，即使是最熟练的外科医生也无法做到。这个学院早期职业发展计划（Career）项目的前提是，智能手术机器人可以通过将人类外科医生的高水平规划和适应性与手持机器人工具的超人速度和精度相结合，提高精确手工任务的熟练表现。要研究和建模的具体应用是使用手持、机器人、生物喷射技术将生物相容材料直接3D打印到移动的人体解剖结构上。这是一个新的融合学科的例子，PI称之为“计算合作手术”。在这里，手持机器人与外科医生共同控制生物喷射机。实现人/机器人二极体的全部潜力将需要无缝合作以及速度和精度之间的动态权衡，以处理不可预测的目标运动。这反过来又要求人类外科医生在机器人高速展开时监测和评估其运动的质量和意图。该项目将使用一种新颖的众包方法，量化人类在高速下感知和表征工具运动视觉反馈的能力。无缝合作还需要外科医生对手持设备进行高带宽控制。该提案将探讨肢体反射反应的自主调节在多大程度上可以促进低延迟监测和控制操作。该项目还包括一些年度外展活动，参与者使用手持机器人来发现和学习计算合作手术和人机共享控制。因此，这个职业项目促进了科学的进步，促进了国民健康，并为STEM劳动力的发展做出了贡献，努力吸引来自代表性不足的少数民族的学生。PI将通过一个项目推进一个新的跨学科研究领域，称为“计算合作手术”，该项目最终将使用手持机器人技术将生物材料直接3D打印到移动的人体解剖结构上。该项目结合了心理学（视觉感知）、工程学（机器人设计和控制）和生理学（感觉运动控制）的元素，以提高人类外科医生利用手持机器人工具的速度和精度的能力。在本研究中，智能机器人与人类外科医生共同控制手术器械，以触觉和本体感觉为反馈通道，肢体僵硬调节为驱动方法。研究目标是测量人类如何感知（目标1）和与（目标2）高速（1kHz带宽）和精度（~50 um）移动的物体（目标2）进行交互。目标1将使用Amazon Mechanical Turk来测试工作假设，即当观察工具操作时，对技能的评估反映了运动速度和运动质量（精度）之间的权衡，这取决于心理因素，包括肢体和物体动力学的内部模型，以及多感觉整合中的刺激一致性。此外，该项目将探索触觉和本体感觉（反馈）以及肢体僵硬调节（驱动）的应用，以实现低延迟、无创的双向人机监测和控制。Aim 2将使用具有高惯性模式和低惯性模式的定制手持机器人和Fitts指向任务来测试工作假设：1)肢体刚度调制是在需要高速和精度的操作过程中快速放弃机器人和人类意图之间的控制的快速有效手段；2)人类通过长时间反射动作（即无需长时间训练）自然地调节手-机器人界面的有效刚度。实现这些目标将推动手持协作机器人的基础科学，以应对不可预测的人类运动或人类意图。教育目标包括一个拓展计划，参与者被邀请使用一个小型手持机器人，看看他们是否能在模拟手术任务中“比最好的外科医生表现得更好”。网站涵盖教室设置、公共活动和临床医生和工程师参加的国际会议。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。

Some surgical procedures are challenging to perform because they demand speed and precision of instrument control that tax the limits of even the most skilled surgeons. This Faculty Early Career Development Program (CAREER) project is based on the premise that intelligent surgical robotics can elevate skilled performance of precision manual tasks by melding the high-level planning and adaptability of the human surgeon with the superhuman speed and precision of a hand-held robotic tool. The specific application to be studied and modeled is 3D printing of biologically-compatible materials directly onto moving human anatomy using hand-held, robotic, bio-jet technology. This is an example of a new convergent discipline, which the PI calls "computational co-surgery." Here, the handheld robot shares control of the bio-jet with the surgeon. Realizing the full potential of the human / robot dyad will require seamless cooperation and a dynamic tradeoff between speed and accuracy to deal with unpredictable target motions. This in turn requires the human surgeon to monitor and evaluate the quality and intent of the robot's motions as they unfold at high speed. The project will quantify the ability of humans to perceive and characterize visual feedback of tool motion at high speeds using a novel crowd-sourcing approach. Seamless cooperation also requires that the surgeon exert high-bandwidth control over the hand-held device. The proposal will explore the extent to which voluntary modulation of limb reflex responses can facilitate low-latency monitoring and control operations. The project also includes several annual outreach events where participants use handheld robots to discover and learn about computational co-surgery and human-robot shared control. As such, this CAREER project promotes the progress of science, advances the national health, and contributes to the development of the STEM workforce, with efforts to attract students from underrepresented minority populations. The PI will advance a new interdisciplinary field of study termed "computational co-surgery" through a project that will ultimately enable 3D printing of bio-materials directly onto moving human anatomy using hand-held, robotic technology. The project combines elements of psychology (visual perception), engineering (robotic design and control), and physiology (sensorimotor control) to promote the ability of the human surgeon to leverage the speed and precision of a hand-held robotic tool. In the case to be studied, an intelligent robot and a human surgeon share control of a surgical instrument, with touch and proprioception as the feedback channels and limb stiffness modulation as the actuation method. The research objective is to measure how humans perceive (Aim 1) and interact with (Aim 2) objects that move with high speed (1kHz bandwidth) and precision (~50 um). Aim 1 will use Amazon Mechanical Turk to test the working hypothesis that when viewing tool manipulations, assessments of skill reflect a trade-off between movement speed and movement quality (precision) subject to psychological factors including internal models of limb and object dynamics, and stimulus coherence in multisensory integration. Further, the project will explore the utility of touch and proprioception (feedback) and limb stiffness modulation (actuation) to realize low-latency, non-invasive bidirectional human-robot monitoring and control. Aim 2 will use a customized hand-held robot with high- and low-inertia modes and a Fitts pointing task to test the working hypotheses that: 1) limb stiffness modulation is a fast and effective means of quickly ceding control between robot and human intent during manipulations requiring high speed and precision; and 2) humans naturally modulate effective stiffness at the hand-robot interface via long-latency reflex action (i.e., without lengthy training). Accomplishing these Aims will advance the fundamental science of handheld collaborative robots that cope with unpredictable human motion or human intent. The educational goal includes an outreach plan where participants are invited to use a small hand-held robot to see if they can "perform better than the best surgeon" in mock surgical tasks. Sites span classroom settings, public events, and international acconferences attended by clinicians and engineers.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.