Abstract:Image-guided surgery (IGS) has allowed for more minimally invasive procedures, leading to better patient outcomes, reduced risk of infection, less pain, shorter hospital stays and faster recoveries. One drawback that has emerged with IGS is that the surgeon must shift their attention from the patient to the monitor for guidance. Yet both cognitive and motor tasks are negatively affected with attention shifts. Augmented reality (AR), which merges the realworld surgical scene with preoperative virtual patient im… Show more
“… 2016 , Léger et al. 2017 ). The amount of information is controlled in real time by the surgeon, so that the cognitive load is tolerable.…”
Section: Discussionmentioning
confidence: 99%
“…This provides a gain in accuracy and safety in the procedurem which finally might result in time-saving and correct positioning of the implant (Léger et al. 2017 , Vávra et al. 2017 ).…”
Section: Discussionmentioning
confidence: 99%
“…The voice- and image-activated command is easy to use, without latency or excessive repetition (Léger et al. 2017 ). The image quality, contrast and stability are good enough not to cause tiredness or motion sickness.…”
“… 2016 , Léger et al. 2017 ). The amount of information is controlled in real time by the surgeon, so that the cognitive load is tolerable.…”
Section: Discussionmentioning
confidence: 99%
“…This provides a gain in accuracy and safety in the procedurem which finally might result in time-saving and correct positioning of the implant (Léger et al. 2017 , Vávra et al. 2017 ).…”
Section: Discussionmentioning
confidence: 99%
“…The voice- and image-activated command is easy to use, without latency or excessive repetition (Léger et al. 2017 ). The image quality, contrast and stability are good enough not to cause tiredness or motion sickness.…”
“…Similar approaches are known, the ARSys Tricorder [4], or the Probaris system [5], none of which have found widespread use in daily surgical routine, presumably due to the additional constraints introduced to surgical workflow (e.g., eye calibration or wearing AR glasses intraoperatively). When considering attention shift [6,7] and depth-perception [8], Spatial AR systems have an advantage over conventional displays or seethrough AR systems [9][10][11]. More recently, microscope and instrument-mounted projectors have been used to provide spatial augmented reality guidance with image projection [12][13][14], or instrument-mounted displays [15] to ease instrument alignment.…”
Purpose
A robotic intraoperative laser guidance system with hybrid optic-magnetic tracking for skull base surgery is presented. It provides in situ augmented reality guidance for microscopic interventions at the lateral skull base with minimal mental and workload overhead on surgeons working without a monitor and dedicated pointing tools.
Methods
Three components were developed: a registration tool (Rhinospider), a hybrid magneto-optic-tracked robotic feedback control scheme and a modified robotic end-effector. Rhinospider optimizes registration of patient and preoperative CT data by excluding user errors in fiducial localization with magnetic tracking. The hybrid controller uses an integrated microscope HD camera for robotic control with a guidance beam shining on a dual plate setup avoiding magnetic field distortions. A robotic needle insertion platform (iSYS Medizintechnik GmbH, Austria) was modified to position a laser beam with high precision in a surgical scene compatible to microscopic surgery.
Results
System accuracy was evaluated quantitatively at various target positions on a phantom. The accuracy found is 1.2 mm ± 0.5 mm. Errors are primarily due to magnetic tracking. This application accuracy seems suitable for most surgical procedures in the lateral skull base. The system was evaluated quantitatively during a mastoidectomy of an anatomic head specimen and was judged useful by the surgeon.
Conclusion
A hybrid robotic laser guidance system with direct visual feedback is proposed for navigated drilling and intraoperative structure localization. The system provides visual cues directly on/in the patient anatomy, reducing the standard limitations of AR visualizations like depth perception. The custom- built end-effector for the iSYS robot is transparent to using surgical microscopes and compatible with magnetic tracking. The cadaver experiment showed that guidance was accurate and that the end-effector is unobtrusive. This laser guidance has potential to aid the surgeon in finding the optimal mastoidectomy trajectory in more difficult interventions.
“…Types of usability metrics category. 13,15,16,18,19,22,25-27,31-35,37,40,41,43,49-59,61,62,64-77,80,81,83] Combination of Both 20[14,17,20,21,23,24,29,38,39,42,[44][45][46][47][48]60,63,78,79,82] …”
The implementation of usability in mobile augmented reality (MAR) learning applications has been utilized in a myriad of standards, methodologies, and techniques. The usage and combination of techniques within research approaches are important in determining the quality of usability data collection. The purpose of this study is to identify, study, and analyze existing usability metrics, methods, techniques, and areas in MAR learning. This study adapts systematic literature review techniques by utilizing research questions and Boolean search strings to identify prospective studies from six established databases that are related to the research context area. Seventy-two articles, consisting of 45 journals, 25 conference proceedings, and two book chapters, were selected through a systematic process. All articles underwent a rigorous selection protocol to ensure content quality according to formulated research questions. Post-synthesis and analysis, the output of this article discusses significant factors in usability-based MAR learning applications. This paper presents five identified gaps in the domain of study, modes of contributions, issues within usability metrics, technique approaches, and hybrid technique combinations. This paper concludes five recommendations based on identified gaps concealing potential of usability-based MAR learning research domains, varieties of unexplored research types, validation of emerging usability metrics, potential of performance metrics, and untapped correlational areas to be discovered.
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