Enabling Technology for Safe Robot-assisted Surgical Micromanipulation

安全机器人辅助手术显微操作的实现技术

• 批准号: 9291018
• 负责人: IULIAN IOAN IORDACHITA
• 金额: $ 30.5万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-15 至 2020-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9291018
• 关键词: Address; Algorithms; Area; Behavior; Cannulations; Clinic; Clinical; Cognitive; Computers; Development; Disadvantaged; Discipline; Environment; Eye; Eye Movements; Feedback; Future; Goals; Grant; Hand; Healthcare; Hemorrhage; Histology; Human; Hybrids; Iatrogenesis; Injury; Intervention; Learning; Machine Learning; Manuals; Mechanics; Medical; Micromanipulation; Microsurgery; Miniaturization; Monitor; Motion; Movement; Operative Surgical Procedures; Ophthalmologic Surgical Procedures; Ophthalmology; Optics; Oryctolagus cuniculus; Otorhinolaryngologic Surgical Procedures; Patients; Perception; Performance; Phase; Physiological; Positioning Attribute; Postoperative Period; Procedures; Property; Reporting; Research; Research Proposals; Retina; Retinal; Retinal Hemorrhage; Retinal Perforations; Retinal Vein Occlusion; Robot; Robotics; Safety; Sclera; Site; Sterilization; Structure; Structure of central vein of the retina; Surgeon; Surveys; System; Tactile; Techniques; Technology; Time; Tissues; Touch sensation; Training; Tremor; User-Computer Interface; Veins; Vision; Work; adaptive learning; base; design; dexterity; high risk; improved; in vivo; in vivo Model; innovation; instrument; interest; learning strategy; man; medical specialties; multisensory; neurosensory; neurosurgery; operation; prevent; research clinical testing; robot assistance; robot control; sensor; technological innovation; tool; trend; virtual

Project Summary The goal of this grant is to develop enabling technology and systems that address fundamental limitations in microsurgery with a specific focus on vitreoretinal surgery. Due to the inherent micro-scale and the fragility of the neurosensory retina, vitreoretinal surgeons can be challenged by physiological hand tremor where the tremor amplitude is larger than retinal structures, delicate movements that are below tactile sensation, and multiple cognitive decisions that are required when executing high-risk movements, such as during retinal vein cannulation (RVC). Nevertheless currently vitreoretinal surgery is at the limits of human physiological performance and lacks the adequate technology that could further improve the technical performance. This situation is less than optimal and can significantly benefit from the recent advances in medical robotics, sensor feedback and human machine interface design. Robotic assistance may be ideally suited to address common problems encountered in the performance of the demanding micromanipulations in retinal microsurgery. We propose a robotic system with enhanced real-time multisensory feedback that assesses multiple points of instrument contact located both inside and outside of the eye. Our comprehensive system will enable the surgeon to manipulate tools based on quantitative feedback that will prevent mechanical injury by implementing safeguards against the application of excessive and previously unmeasurable forces at the eyewall and the tool tip. Our aims are: (1) Develop and demonstrate in vivo position/force hybrid control algorithms for enabling real- time high-fidelity sensorimotor capabilities at the sclerotomy for safe robot-assisted vitreoretinal microsurgery: real-time sensorimotor capabilities at the sclerotomy will be uniquely used to control the robot through a machine learning method that adaptively learns a nonlinear mapping from user behavior to sclera-force/position and predicts unsafe motions; (2) Develop and demonstrate in vivo force-input control algorithms for enabling real- time high-fidelity sensorimotor capabilities at the tool-tip for safe robot-assisted vein cannulation: real-time tool- tip-to-tissue interaction force sensing and non-linear robot control algorithms based on observing the user behavior will be used to control the tool-tip position and force and to prevent entry into subretinal areas during RVC; (3) Demonstrate safe robot-assisted RVC in rabbit model in vivo: real-time, position/force hybrid control algorithms based on dual-point (tool-shaft and tip) information fusion will provide sensorimotor guidance of surgical maneuvers during RVC. Statistically significant results in vivo, in clinically realistic conditions will demonstrate the feasibility of our approach. This highly innovative system will enable surgeons to perform maneuvers in a tremor free environment with a higher level of precision than previously possible and with the ability to sense forces on a scale that have been previously imperceptible. We envision this development as a logical next step in the integration of man, machine and computer for the performance of unprecedented microsurgical maneuvers.

项目摘要 这项赠款的目标是开发使能技术和系统，解决基本的限制， 显微手术，特别关注玻璃体视网膜手术。由于固有的微观规模和脆弱性， 对于神经感觉视网膜，玻璃体视网膜外科医生可能受到生理性手震颤的挑战，其中震颤 振幅大于视网膜结构，低于触觉的精细运动，以及多个 执行高风险运动时所需的认知决策，例如在视网膜静脉注射期间， 插管（RVC）。然而，目前玻璃体视网膜手术处于人类生理的极限， 这些国家的技术能力有限，缺乏可进一步提高技术性能的适当技术。这 这种情况不是最佳的，可以从医疗机器人、传感器 反馈和人机界面设计。机器人辅助可能非常适合解决常见的 在视网膜显微外科手术中进行要求严格的显微操作时遇到的问题。 我们提出了一个机器人系统与增强的实时多感官反馈，评估多个点 眼内和眼外的仪器接触。我们的全面系统将使 外科医生基于定量反馈来操纵工具， 防止在眼壁和工具处施加过度的和以前不可测量的力的保护措施 tip.我们的目标是：（1）开发和演示体内位置/力混合控制算法，使真实的- 安全的机器人辅助玻璃体视网膜显微手术在巩膜切开术时的时间高保真感觉运动能力： 巩膜切开术的实时感觉运动能力将被独特地用于通过机器控制机器人 自适应地学习从用户行为到巩膜力/位置的非线性映射的学习方法， 预测不安全的运动;（2）开发和演示体内力输入控制算法，以实现真实的- 安全机器人辅助静脉插管工具尖端的时间高保真感觉运动功能：实时工具- 基于观察用户的尖端-组织相互作用力感测和非线性机器人控制算法 行为将用于控制工具尖端的位置和力，并防止进入视网膜下区域 （3）在兔体内模型中验证机器人辅助的安全RVC：实时、位置/力混合控制 基于双点（工具轴和尖端）信息融合的算法将提供 RVC期间的手术操作。在临床现实条件下，体内统计学显著结果将 证明了我们方法的可行性。 这种高度创新的系统将使外科医生能够在无震颤的环境中进行操作， 比以前可能的精度更高，并且能够感知已经被 以前无法察觉的。我们将这一发展设想为人类、机器 和计算机来进行前所未有的显微手术操作。