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A cadaver study of mastoidectomy using an image-guided human-robot collaborative control system.

ABSTRACT: Objective:Surgical precision would be better achieved with the development of an anatomical monitoring and controlling robot system than by traditional surgery techniques alone. We evaluated the feasibility of robot-assisted mastoidectomy in terms of duration, precision, and safety. Study Design:Human cadaveric study. Materials and Methods:We developed a multi-degree-of-freedom robot system for a surgical drill with a balancing arm. The drill system is manipulated by the surgeon, the motion of the drill burr is monitored by the image-guided system, and the brake is controlled by the robotic system. The system also includes an alarm as well as the brake to help avoid unexpected damage to vital structures. Experimental mastoidectomy was performed in 11 temporal bones of six cadavers. Parameters including duration and safety were assessed, as well as intraoperative damage, which was judged via pre- and post-operative computed tomography. Results:The duration of mastoidectomy in our study was comparable with that required for chronic otitis media patients. Although minor damage, such as dura exposure without tearing, was noted, no critical damage to the facial nerve or other important structures was observed. When the brake system was set to 1 mm from the facial nerve, the postoperative average bone thicknesses of the facial nerve was 1.39, 1.41, 1.22, 1.41, and 1.55 mm in the lateral, posterior pyramidal and anterior, lateral, and posterior mastoid portions, respectively. Conclusion:Mastoidectomy can be successfully performed using our robot-assisted system while maintaining a pre-set limit of 1 mm in most cases. This system may thus be useful for more inexperienced surgeons. Level of Evidence:NA.

SUBMITTER: Yoo MH

PROVIDER: S-EPMC5655553 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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A cadaver study of mastoidectomy using an image-guided human-robot collaborative control system.

Yoo Myung Hoon MH Lee Hwan Seo HS Yang Chan Joo CJ Lee Seung Hwan SH Lim Hoon H Lee Seongpung S Yi Byung-Ju BJ Chung Jong Woo JW

Laryngoscope investigative otolaryngology 20170925 5

<h4>Objective</h4>Surgical precision would be better achieved with the development of an anatomical monitoring and controlling robot system than by traditional surgery techniques alone. We evaluated the feasibility of robot-assisted mastoidectomy in terms of duration, precision, and safety.<h4>Study design</h4>Human cadaveric study.<h4>Materials and methods</h4>We developed a multi-degree-of-freedom robot system for a surgical drill with a balancing arm. The drill system is manipulated by the su ...[more]

PMID: 29094065

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Project description:This article provides a perspective on estimation and control problems in cyberphysical human systems (CPHSs) that work at the intersection of cyberphysical systems and human systems. The article also discusses solutions to some of the problems in CPHSs. One example of a CPHS is a close-proximity human-robot collaboration (HRC) in a manufacturing setting. The issue of the joint operation's efficiency and human factors, such as safety, attention, mental states, and comfort, naturally arise in the HRC context. By considering human factors, robots' actions can be controlled to achieve objectives, including safe operations and human comfort. Alternately, questions arise when robot factors are considered. For example, can we provide direct inputs and information to humans about an environment and the robots in the area such that the objectives of safety, efficiency, and comfort can be satisfied by considering the robots' current capabilities? The article discusses specific problems involved in HRC related to controlling a robot's motion by taking the current actions of the human in the loop with the robot's control system. To this end, two main challenges are discussed: 1) inferring the intention behind human actions by analyzing a person's motion as observed through skeletal tracking and gaze data and 2) a controller design that keeps robot motion constrained to a boundary in a 3D space by using control barrier functions. The intention inference method fuses skeleton-joint tracking data obtained using the Microsoft Kinect sensor and human gaze data gathered from red-green-blue Kinect images. The direction of a human's hand-reaching motion and a goal-reaching point is estimated while performing a joint pick-and-place task. The trajectory of the hand is estimated forward in time based on the gaze and hand motion data at the current time instance. A barrier function method is applied to generate safe robot trajectories along with forecast hand movements to complete the collaborative displacement of an object by a person and a robot. An adaptive controller is then used to track the reference trajectories using the Baxter robot, which is tested in a Gazebo simulation environment.

Dataset Information

A cadaver study of mastoidectomy using an image-guided human-robot collaborative control system.

Publications

A cadaver study of mastoidectomy using an image-guided human-robot collaborative control system.

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