Enabling Technology for Safe Robot-assisted Surgical Micromanipulation
Enabling Technology for Safe Robot-assisted Surgical Micromanipulation
批准号:
9291018
负责人:
IULIAN IOAN IORDACHITA
金额:
$30.5万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-03-15 至 2020-01-31
关键词:
AddressAlgorithmsAreaBehaviorCannulationsClinicClinicalCognitiveComputersDevelopmentDisadvantagedDisciplineEnvironmentEyeEye MovementsFeedbackFutureGoalsGrantHandHealthcareHemorrhageHistologyHumanHybridsIatrogenesisInjuryInterventionLearningMachine LearningManualsMechanicsMedicalMicromanipulationMicrosurgeryMiniaturizationMonitorMotionMovementOperative Surgical ProceduresOphthalmologic Surgical ProceduresOphthalmologyOpticsOryctolagus cuniculusOtorhinolaryngologic Surgical ProceduresPatientsPerceptionPerformancePhasePhysiologicalPositioning AttributePostoperative PeriodProceduresPropertyReportingResearchResearch ProposalsRetinaRetinalRetinal HemorrhageRetinal PerforationsRetinal Vein OcclusionRobotRoboticsSafetyScleraSiteSterilizationStructureStructure of central vein of the retinaSurgeonSurveysSystemTactileTechniquesTechnologyTimeTissuesTouch sensationTrainingTremorUser-Computer InterfaceVeinsVisionWorkadaptive learningbasedesigndexterityhigh riskimprovedin vivoin vivo Modelinnovationinstrumentinterestlearning strategymanmedical specialtiesmultisensoryneurosensoryneurosurgeryoperationpreventresearch clinical testingrobot assistancerobot controlsensortechnological innovationtooltrendvirtual
中文摘要
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英文摘要
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.
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Enabling technology for image-guided robot-assisted sub-retinal injections
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批准号:10248434
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项目类别:
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资助金额:$46.84万
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财政年份:2019
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负责人:IULIAN IOAN IORDACHITA
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依托单位:
Enabling technology for image-guided robot-assisted sub-retinal injections
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批准号:10019539
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项目类别:
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资助金额:$50.4万
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财政年份:2019
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负责人:IULIAN IOAN IORDACHITA
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依托单位:
海外基金