CAREER: Scientific Foundations for Augmented Human Performance in Robotic Surgery

一些外科手术具有挑战性，因为它们要求器械控制的速度和精度，即使是最熟练的外科医生也会受到限制。 这个教师早期职业发展计划（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超人的速度和精度相结合来提高精确手动任务的熟练性能手持机器人工具。要研究和建模的具体应用是使用手持式，机器人，生物喷射技术将生物相容性材料直接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享生物射流的控制权。实现人/机器人二元体的全部潜力将需要无缝合作以及在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机器人运动的质量和意图。该项目将量化人类感知和描述高速工具运动视觉反馈的能力，使用一种新的众包方法。无缝协作还要求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愿调节在多大程度上可以促进低延迟监测和控制操作。该项目还包括几个年度外展活动，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CAREER项目促进了科学的进步，促进了国民健康，并有助于STEM劳动力的发展，努力吸引来自代表性不足的少数民族人口的学生。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。在要研究的情况下，智能机器人和人类外科医生共享手术器械的控制，触摸和本体感觉作为反馈通道，肢体刚度调制作为致动方法。研究目标是测量人类如何感知（目标1）和与（目标2）高速（1 kHz带宽）和精确（~50 μ m）移动的物体进行交互。 Aim 1将使用Amazon Mechanical Turk来测试工作假设，即在查看工具操作时，技能评估反映了运动速度和运动质量（精度）之间的权衡，受心理因素的影响，包括肢体和物体动力学的内部模型以及多感官整合中的刺激连贯性。 此外，该项目将探索触摸和本体感觉（反馈）和肢体刚度调制（驱动）的实用性，以实现低延迟，非侵入性的双向人机监测和控制。目标2将使用具有高惯性和低惯性模式的定制手持机器人以及Fitts指向任务来测试以下工作假设：1）肢体刚度调制是在需要高速度和精度的操纵期间在机器人和人类意图之间快速放弃控制的快速有效手段;以及2）人类通过长延迟反射动作自然地调制手-机器人界面处的有效刚度（即，没有长期的训练）。 实现这些目标将推进手持协作机器人的基础科学，以科普不可预测的人类运动或人类意图。教育目标包括一个推广计划，邀请参与者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”。 该奖项反映了NSF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.