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Multiple reflections and nonlinearity of phase modulating need to be compensated to accurately profile the surface of the glass plate using wavelength-modulated interferometry. In this study, to assess the glass plate surface using wavelength-modulated interferometry, a new phase-iterative method insensitive to the harmonic signals and nonlinear errors was developed. We developed the harmonic phase-iterative method by combining the phase-iterative method with irradiance signal considering the harmonic components. Moreover, for suppression of the harmonic-related errors in the iterative calculation, the noble pixel-selection technique and convergence formula were combined with the phase-iterative method. For estimation of the developed iterative method, we conducted the numerical simulation and assessed the glass plate surface with the Fizeau interferometer. The simulation and assessment results demonstrated that the proposed method could perform phase extraction with improved iterative calculation and suppression of the effects of the harmonics and nonlinearity.

Intraocular surgery, one of the most challenging discipline of microsurgery, requires sensory and motor skills at the limits of human physiological capabilities combined with tremendously difficult requirements for accuracy and steadiness. Nowadays, robotics combined with advanced imaging has opened conspicuous and significant directions in advancing the field of intraocular microsurgery. Having patient treatment with greater safety and efficiency as the final goal, similar to other medical applications, robotics has a real potential to fundamentally change microsurgery by combining human strengths with computer and sensor-based technology in an information-driven environment. Still in its early stages, robotic assistance for intraocular microsurgery has been accepted with precaution in the operating room and successfully tested in a limited number of clinical trials. However, owing to its demonstrated capabilities including hand tremor reduction, haptic feedback, steadiness, enhanced dexterity, micrometer-scale accuracy, and others, microsurgery robotics has evolved as a very promising trend in advancing retinal surgery. This paper will analyze the advances in retinal robotic microsurgery, its current drawbacks and limitations, as well as the possible new directions to expand retinal microsurgery to techniques currently beyond human boundaries or infeasible without robotics.

Neonate patients have a reduced thoracic cavity, making thoracoscopic procedures even more challenging than their adult counterparts.We evaluated five control strategies for robot-assisted thoracoscopic surgical looping in simulations and experiments with a physical robotic system in a neonate surgical phantom. The strategies are composed of state-of-the-art constrained optimization and a novel looping force feedback term.All control strategies allowed users to successfully perform looping. A user study in simulation showed that the proposed strategy was superior in terms of Physical demandAssistive strategies in looping show promise and further work is needed to extend these benefits to other subtasks in robot-aided surgical suturing.

The Johns Hopkins–Intuitive Gesture and Skill Assessment Working Set (JIGSAWS) dataset is used to develop robotic surgery skill assessment tools, but there has been no detailed analysis of this dataset. The aim of this study is to perform a learning curve analysis of the existing JIGSAWS dataset. Five trials were performed in JIGSAWS by eight participants (four novices, two intermediates and two experts) for three exercises (suturing, knot-tying and needle passing). Global Rating Scores and time, path length and movements were analyzed quantitatively and qualitatively by graphical analysis. There are no significant differences in Global Rating Scale scores over time. Time in the suturing exercise and path length in needle passing had significant differences. Other kinematic parameters were not significantly different. Qualitative analysis shows a learning curve only for suturing. Cumulative sum analysis suggests completion of the learning curve for suturing by trial 4. The existing JIGSAWS dataset does not show a quantitative learning curve for Global Rating Scale scores, or most kinematic parameters which may be due in part to the limited size of the dataset. Qualitative analysis shows a learning curve for suturing. Cumulative sum analysis suggests completion of the suturing learning curve by trial 4. An expanded dataset is needed to facilitate subset analyses.

PurposeThe JIGSAWS dataset is a fixed dataset of robot-assisted surgery kinematic data used to develop predictive models of skill. The purpose of this study is to analyze the relationships of self-defined skill level with global rating scale scores and kinematic data (time, path length and movements) from three exercises (suturing, knot-tying and needle passing) (right and left hands) in the JIGSAWS dataset.MethodsGlobal rating scale scores are reported in the JIGSAWS dataset and kinematic data were calculated using ROVIMAS software. Self-defined skill levels are in the dataset (novice, intermediate, expert). Correlation coefficients (global rating scale-skill level and global rating scale-kinematic parameters) were calculated. Kinematic parameters were compared among skill levels.ResultsGlobal rating scale scores correlated with skill in the knot-tying exercise (r = 0.55,p = 0.0005). In the suturing exercise, time, path length (left) and movements (left) were significantly different (p ConclusionGlobal rating scale scores weakly correlate with skill level and kinematic parameters. The ability of kinematic parameters to differentiate among self-defined skill levels is inconsistent. Additional data are needed to enhance the dataset and facilitate subset analyses and future model development.

We developed a sensor-integrated eye surgical simulator for inner limiting membrane (ILM) peeling, a complicated intraocular surgery. For the quantitative characterization of the retinal surgical skills, we first introduced a quartz crystal resonator (QCR) force sensor that exhibits the high sensitivity, the dynamic range, and the rigidity. The dynamic range of the simulator with this sensor was from 0.087 mN to 7.7 N. We subsequently achieved the uniformity of the force sensitivity on the retinal area of ILM peeling by the parallel mechanical suspension and double ends flexure of the QCR sensor. The error proportion of the sensitivity in that retinal area was suppressed within ±14 %. Finally, we demonstrated the practical evaluation of ILM peeling on the training platform.

Among increasing eye diseases, glaucoma may hurt the optic nerves and lead to vision loss, the treatment of which is to reduce intraocular pressure (IOP). In this research, we introduce a new concept of the surgery simulator for Minimally Invasive Glaucoma Surgery (MIGS). The concept is comprised of an anterior eye model and a fluidic circulatory system. The model made of flexible material includes a channel like the Schlemm’s canal (SC) and a membrane like the trabecular meshwork (TM) covering the SC. The system can monitor IOP in the model by a pressure sensor. In one of the MIGS procedures, the TM is cleaved to reduce the IOP. Using the simulator, ophthalmologists can practice the procedure and measure the IOP. First, considering the characteristics of human eyes, we defined requirements and target performances for the simulator. Next, we designed and manufactured the prototype. Using the prototype, we measured the IOP change before and after cleaving the TM. Finally, we demonstrated the availability by comparing experimental results and target performances. This simulator is also expected to be used for evaluations and developments of new MIGS instruments and ophthalmic surgery robots in addition to the surgical training of ophthalmologists.

Vitreoretinal surgery is challenging even for expert surgeons owing to the delicate target tissues and the diminutive workspace in the retina. In addition to improved dexterity and accuracy, robot assistance allows for (partial) task automation. In this work, we propose a strategy to automate the motion of the light guide with respect to the surgical instrument. This automation allows the instrument's shadow to always be inside the microscopic view, which is an important cue for the accurate positioning of the instrument in the retina. We show simulations and experiments demonstrating that the proposed strategy is effective in a 700-point grid in the retina of a surgical phantom. Furthermore, we integrated the proposed strategy with image processing and succeeded in positioning the surgical instrument's tip in the retina, relying on only the robot's geometric information and microscopic images., Comment: Accepted on T-MRB 2022, 16 pages

The Johns Hopkins-Intuitive Gesture and Skill Assessment Working Set (JIGSAWS) dataset is used to develop robotic surgery skill assessment tools, but there has been no detailed analysis of this dataset. The aim of this study is to perform a learning curve analysis of the existing JIGSAWS dataset.Five trials were performed in JIGSAWS by eight participants (four novices, two intermediates and two experts) for three exercises (suturing, knot-tying and needle passing). Global Rating Scores and time, path length and movements were analyzed quantitatively and qualitatively by graphical analysis.There are no significant differences in Global Rating Scale scores over time. Time in the suturing exercise and path length in needle passing had significant differences. Other kinematic parameters were not significantly different. Qualitative analysis shows a learning curve only for suturing. Cumulative sum analysis suggests completion of the learning curve for suturing by trial 4.The existing JIGSAWS dataset does not show a quantitative learning curve for Global Rating Scale scores, or most kinematic parameters which may be due in part to the limited size of the dataset. Qualitative analysis shows a learning curve for suturing. Cumulative sum analysis suggests completion of the suturing learning curve by trial 4. An expanded dataset is needed to facilitate subset analyses.

Our aims were to develop a training system for camera assistants (CA), and evaluate participants' performance as CA.A questionnaire on essential requirements to be a good CA was administered to experts in pediatric endoscopic surgery. An infant-sized box trainer with several markers and lines inside was developed. Participants performed marker capturing and line-tracing tasks using a 5-mm 30° scope. A postexperimental questionnaire on the developed system was administered. The task completion time was measured.The 5-point evaluation scale was used for each item in the questionnaire survey of experts. The abilities to maintain a horizontal line (mean score: 4.5) and to center the target in a specified rectangle on the monitor (4.5) as well as having a full understanding of the operative procedure (4.3) were ranked as highly important. Fifty-two participants, including 5 surgical residents, were enrolled in the evaluation experiment. The completion time of capturing the markers was significantly longer in the resident group than in the nonresident group (244 versus 124 seconds, P = .04), but that of tracing the lines was not significantly different between the groups. The postexperimental questionnaire showed that the participants felt that the line-tracing tasks (3.7) were more difficult than marker-capturing tasks (2.9).Being proficient in manipulating a camera and having adequate knowledge of operative procedures are essential requirements to be a good CA. The ability was different between the resident and nonresident groups even in a simple task such as marker capturing.

Wavelength-tuning interferometry has been widely used to measure and estimate the surface profile of optical components. However, in multilayer interferometry, the coupling error between the higher harmonics and the phase-shift error causes a considerable systematic error in the calculated phase. In this research, the new 7N − 6 phase-shifting algorithm was developed using the characteristic polynomial theory. The coupling errors calculated by various types of phase-shifting algorithms were analyzed. The surface profile and optical thickness deviation of the lithium niobate crystal wafer were measured simultaneously using wavelength-tuning Fizeau interferometry and the 7N − 6 algorithm. The experimental results were compared in terms of observed ripples and measurement repeatability.

Automation of surgical tasks is expected to improve the quality of surgery. In this paper, we address two issues that must be resolved for automation of robotic surgery: online trajectory planning and force control under dynamic conditions. By leveraging demonstrations under various conditions, we model the conditional distribution of the trajectories given the task condition. This scheme enables generalization of the trajectories of spatial motion and contact force to new conditions in real time. In addition, we propose a force tracking controller that robustly and stably tracks the planned profile of the contact force by learning the spatial motion and contact force simultaneously. The proposed scheme was tested with bimanual tasks emulating surgical tasks that require online trajectory planning and force tracking control, such as tying knots and cutting soft tissues. Experimental results show that the proposed scheme enables planning of the task trajectory under dynamic conditions in real time. In addition, the performance of the force control schemes was verified in the experiments. Note to Practitioners —This paper addresses the problem of motion planning and control for automation of surgical tasks. In surgical tasks, it is necessary to manipulate objects under conditions where positions or shapes of objects often change during the task. Thus, trajectories for surgical tasks need to be planned and updated according to the change in the conditions in real time. In this paper, we propose a framework for learning both spatial motion and force profile from human experts. The proposed system can plan and update task trajectories in real time and robustly control the contact force under dynamic conditions. On the other hand, generalization of trajectories is limited to the conditions, which are close to the conditions where the demonstrations were performed. In the future work, we will investigate reinforcement learning approaches in order to enable autonomous improvement of the performance.

In measurements of the variations in the thickness and surface profile of optical flats using wavelength-tuning fringe analysis, an interference signal can be detected based on the modulation frequency of the signal. However, the modulation frequency can deviate from the predetermined value through the refractive-index dispersion of the optical flat. In this study, two types of noble 25-frame phase-detection algorithms that can compensate for the effect of refractive-index dispersion were developed using Fourier analysis. The behaviors of the 25-frame algorithms were visualized on both the frequency domain and complex plane. The dispersion-resistance ability and signal-to-noise ration of the 25-frame algorithm were estimated by calculating the PV errors and using the frequency-transfer-function paradigm, respectively. Finally, the variations in the thickness and surface profile of the optical flat were measured using a wavelength-tuning Fizeau interferometer and the proposed 25-frame algorithms. The standard deviations of the thickness and surface measurements were 1.654 nm and 8.368 nm, respectively, which were much smaller than those of the conventional phase-detection algorithms.

Precision machining of sintered zirconia ceramics is expected for various applications such as dental prostheses or artificial femoral heads. However, machining of zirconia is a major challenge because of its high hardness. We have found that the bending strength and fracture toughness of this material decrease with an increase in temperature. To use this characteristic, we propose a high-speed milling process with a cutting speed of more than 500 m/min because high-cutting speed can generate a large amount of heat during cutting. According to the results of trials, precision machining of the surface was possible with a cutting speed of 670 m/min. Moreover, the amount of flank wear was decreased by the high-speed milling. These results confirmed the possibility of precision cutting of sintered zirconia ceramics.

[abstFig src='/00290002/15.jpg' width='300' text='Proposed method for tracking and following respiratory organ motion' ] High intensity focused ultrasound (HIFU) is potentially useful for treating stones and/or tumors. With respect to HIFU therapy, it is difficult to focus HIFU on the focal lesion due to respiratory organ motion, and this increases the risk of damaging the surrounding healthy tissues around the target focal lesion. Thus, this study proposes a method to cope with the fore-mentioned problem involving tracking and following the respiratory organ motion via a visual feedback and a prediction model for respiratory organ motion to realize highly accurate servoing performance for focal lesions. The prediction model is continuously updated based on the latest organ motion data. The results indicate that respiratory kidney motion of two healthy subjects is successfully tracked and followed with an accuracy of 0.88 mm by the proposed method and the constructed system.

The absolute optical thickness and surface shape of optical devices are considered as the fundamental characteristics when designing optical equipment. The thickness and surface shape should be measured simultaneously to reduce cost. In this research, the absolute optical thickness and surface shape of a 6–mm-thick fused silica transparent plate of diameter 100 mm was measured simultaneously by a three-surface Fizeau interferometer. A measurement method combining the wavelength tuning Fourier and phase shifting technique was proposed. The absolute optical thickness that corresponds to the group refractive index was determined by wavelength tuning Fourier analysis. At the beginning and end of the wavelength tuning, the fractional phases of the interference fringes were measured by the phase shifting technique and optical thickness deviations with respect to the ordinary refractive index and surface shape were determined. These two kinds of optical thicknesses were synthesized using the Sellmeier equation for the refractive index of fused silica glass, and the least square fitting method was used to determine the final absolute optical thickness distribution. The experimental results indicate that the all the measurement uncertainties for the absolute optical thickness and surface shape were approximately 3 nm and 35 nm, respectively.

Optical thickness variation is a fundamental characteristic of transparent optical devices. When measuring this variation by using a wavelength-tuning Fizeau interferometer, the measurement accuracy depends on the phase-shifting algorithm being used. Therefore, the phase-shifting algorithm should compensate for any errors incurred during the measurement, including the phase-shift error, coupling errors, and bias modulation of intensity. Among these errors, however, the coupling errors between the higher harmonics resulting from the inner reflections of the transparent plate and phase-shift error have not previously been considered. This paper presents a derivation of a 19-sample phase-shifting algorithm that can compensate for the miscalibration and 1st-order nonlinearity of the phase shift, coupling errors, and bias modulation of intensity during wavelength tuning. The characteristics of the 19-sample algorithm were estimated with respect to the Fourier representation in the frequency domain. The phase error of measurements performed using the 19-sample algorithm was discussed and compared with that of measurements obtained using other conventional phase-shifting algorithms. Finally, the optical thickness variation of a fused silica parallel plate was obtained using a wavelength-tuning Fizeau interferometer and the 19-sample algorithm. The measurement accuracy was discussed by comparing the ripples in the crosstalk noise with those calculated using other phase-shifting algorithms. The experimental results indicated that the optical thickness variation measurement accuracy for the fused silica plate was approximately 2 nm.

Yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) is a promising material for dental restoratives. Although grinding or polishing with diamond tools is widely used to machine Y-TZP, the processing efficiency and cost of the process are problematic. In this study, we applied laser-assisted machining (LAM) to Y-TZP, in which non-diamond tools were used. Unlike LAM applied to other materials, decrease of the fracture toughness at elevated temperatures which is a unique feature of the Y-TZP was adopted as a key mechanism for machinability enhancement. In addition, a systematic method to determine the LAM conditions was proposed. In this study, we explain the LAM condition-determining method, which is based on numerical simulations of the temperature distribution. Secondly, the determining method was evaluated through a series of LAM experiments to obtain the appropriate LAM conditions. Using the determined conditions, LAM of Y-TZP was demonstrated to be effective; the thrust force was reduced by 51.3% and the tool wear was significantly reduced, while no cracks formed on the Y-TZP.

Master—slave robotic systems have enabled operators to perform complex tasks with high precision. Some tasks can be further enhanced by adding virtual fixtures, which can guide user motion or constrain it within a safety envelope. In this study, the focus is on the generation of virtual fixtures for robotic-assisted bi-manual cutting, with possible applications in medicine and industry. Two control methods are proposed: forbidden-plane constraints (for increased safety) and an angle-ellipsoid constraint (for increased performance) which guide the user to safe and efficient bi-manual cutting. The proposed methods were evaluated in a user experiment using a pathology grossing master-slave robotic system. The results show that the forbidden-plane constraints enhanced the safety of the task, while the angle-ellipsoid constraint reduced cutting error by more than 58% (p

To evaluate surgeons’ skills and medical devices, interaction between surgical instruments and a physical surgery simulator can be measured by various sensors. This study proposes sensors for a physical surgery model which accurately replicates mechanical properties of human tissues using synthetic materials, and we named such sensors as ”Bionic Sensors”. As an example, we attempted to integrate a sensor measures the force applying to the fundus retina, into an eye surgery simulator, Bionic-EyE™. We designed a cantilever-type load sensor using a quartz crystal resonator (QCR) with a highly load resolution and wide dynamic range and integrated it in the fundus part of Bionic-EyE™ as a Bionic Sensor. The interaction of a microforceps and the fundus part was measured in a simulated task of the inner limiting membrane (ILM) peeling, and the maximum indentation load was approximately 20 mN when the task was performed by a skilled surgeon. The high sensitivity of the bionic sensor designed to measure the millinewton-order indentation force for the ILM peeling task was successfully demonstrated.

Surgical robots are used to perform minimally invasive surgery and alleviate much of the burden imposed on surgeons. Our group has developed a surgical robot to aid in the removal of tumors at the base of the skull via access through the nostrils. To avoid injuring the patients, a collision-avoidance algorithm that depends on having an accurate model for the poses of the instruments' shafts is used. Given that the model's parameters can change over time owing to interactions between instruments and other disturbances, the online estimation of the poses of the instrument's shaft is essential. In this work, we propose a new method to estimate the pose of the surgical instruments' shafts using a monocular endoscope. Our method is based on the use of an automatically annotated training dataset and an improved pose-estimation deep-learning architecture. In preliminary experiments, we show that our method can surpass state of the art vision-based marker-less pose estimation techniques (providing an error decrease of 55% in position estimation, 64% in pitch, and 69% in yaw) by using artificial images., Comment: Accepted on ICRA 2020, 7 pages

The manual generation of training data for the semantic segmentation of medical images using deep neural networks is a time-consuming and error-prone task. In this paper, we investigate the effect of different levels of realism on the training of deep neural networks for semantic segmentation of robotic instruments. An interactive virtual-reality environment was developed to generate synthetic images for robot-aided endoscopic surgery. In contrast with earlier works, we use physically based rendering for increased realism.Using a virtual reality simulator that replicates our robotic setup, three synthetic image databases with an increasing level of realism were generated: flat, basic, and realistic (using the physically-based rendering). Each of those databases was used to train 20 instances of a UNet-based semantic-segmentation deep-learning model. The networks trained with only synthetic images were evaluated on the segmentation of 160 endoscopic images of a phantom. The networks were compared using the Dwass-Steel-Critchlow-Fligner nonparametric test.Our results show that the levels of realism increased the mean intersection-over-union (mIoU) of the networks on endoscopic images of a phantom ([Formula: see text]). The median mIoU values were 0.235 for the flat dataset, 0.458 for the basic, and 0.729 for the realistic. All the networks trained with synthetic images outperformed naive classifiers. Moreover, in an ablation study, we show that the mIoU of physically based rendering is superior to texture mapping ([Formula: see text]) of the instrument (0.606), the background (0.685), and the background and instruments combined (0.672).Using physical-based rendering to generate synthetic images is an effective approach to improve the training of neural networks for the semantic segmentation of surgical instruments in endoscopic images. Our results show that this strategy can be an essential step in the broad applicability of deep neural networks in semantic segmentation tasks and help bridge the domain gap in machine learning.

Background With the increasing presence of surgical robots minimally invasive surgery, there is a growing necessity of a versatile surgical system for deep and narrow workspaces. Methods We developed a versatile system for constrained workspaces called SmartArm. It has two industrial-type robotic arms with flexible tools attached to its distal tip, with a total of nine active degrees-of-freedom. The system has a control algorithm based on constrained optimization that allows the safe generation of task constraints and intuitive teleoperation. Results The SmartArm system is evaluated in a master-slave experiment in which a medically untrained user operates the robot to suture the dura mater membrane at the skull base of a realistic head phantom. Our results show that the user could accomplish the task proficiently, with speed and accuracy comparable to manual suturing by surgeons. Conclusions We demonstrated the integration and validation of the SmartArm.

In production lines, human workers assemble and/or inspect products in a predetermined process flow. Training new workers is a complex process with varying results. To track the workers motion in a way to better understand human skill, an overhead semantic part segmentation of workers is desired. For this purpose, in this work, we propose a fully-convolutional neural-network model paired with four proposed augmentation strategies. Artificial depth images were used as training data and the augmentation strategies were essential in aiding the network to generalize to the real images. The proposed method was evaluated in two tasks with different backgrounds: a part assembly task and a quality check task. We improved the F-measure by 12% in the part assembly task and 4% in the quality check task when compared to our previous work.

Minimally Invasive Surgery (MIS) is one of the most successful applications of surgical robots. Although the introduction of robotic technology has brought a number of benefits, further advancements in MIS are limited by the size and bending radius of instruments. In this paper, we present a compliant four degree-of-freedom manipulator that consists of elastic elements with partly thinner structures. The proposed mechanism allows the elastic element to deform locally, thus minimizing its bending radius while the low number of mechanical parts greatly contributes to its compactness. This paper describes the design strategy, optimization method using FEA, prototype implementation, and evaluations. The evaluations reveal high accuracy and repeat accuracy, which are key elements for robotic instruments in MIS. Further, the prototype is able to exert sufficient force and it is possible to perform a simulated needle insertion task using the manipulator, demonstrating the feasibility of the proposed mechanism.

Indium tin oxide (ITO) thin films have been widely used in displays such as liquid crystal displays and touch panels because of their favorable electrical conductivity and optical transparency. The surface shape and thickness of ITO thin films must be precisely measured to improve their reliability and performance. Conventional measurement techniques take single point measurements and require expensive systems. In this paper, we measure the surface shape of an ITO thin film on top of a transparent plate using wavelength-tuning Fizeau interferometry. The surface shape was determined by compensating for the phase error introduced by optical interference from the thin film, which was calculated using the phase and amplitude distributions measured by wavelength-tuning. The proposed measurement method achieved noncontact, large-aperture, and precise measurements of transparent thin films. The surface shape of the sample was experimentally measured to an accuracy of 40 nm, mainly limited by the accuracy of the reference surface of 30 nm.

Three-dimensional (3D) microfluidic channels, which simulate human tissues such as blood vessels, are useful in surgical simulator models for evaluating surgical devices and training novice surgeons. However, animal models and current artificial models do not sufficiently mimic the anatomical and mechanical properties of human tissues. Therefore, we established a novel fabrication method to fabricate an eye model for use as a surgical simulator. For the glaucoma surgery task, the eye model consists of a sclera with a clear cornea, a 3D microchannel with a width of 200&ndash, 500 &micro, m, representing the Schlemm&rsquo, s canal (SC), and a thin membrane with a thickness of 40&ndash, 132 &micro, m, representing the trabecular meshwork (TM). The sclera model with a clear cornea and SC was fabricated by 3D molding. Blow molding was used to fabricate the TM to cover the inner surface of the sclera part. Soft materials with controllable mechanical behaviors were used to fabricate the sclera and TM parts to mimic the mechanical properties of human tissues. Additionally, to simulate the surgery with constraints similar to those in a real operation, the eye model was installed on a skull platform. Therefore, in this paper, we propose an integration method for fabricating an eye model that has a 3D microchannel representing the SC and a membrane representing the TM, to develop a glaucoma model for training novice surgeons.

Vitreoretinal surgery tasks are difficult even for expert surgeons. Therefore, an eye-surgery robot has been developed to assist surgeons in performing such difficult tasks accurately and safely. In this paper, the autonomous positioning of a micropipette mounted on an eye-surgery robot is proposed; specifically, the shadow of the micropipette is used for positioning in the depth direction. First, several microscopic images of the micropipette and its shadow are obtained, and the images are manually segmented into three regions, namely, the micropipette, its shadow, and the eye ground regions. Next, each pixel of the segmented regions is labeled, and labeled images are used as ground-truth data. Subsequently, the Gaussian Mixture Model (GMM) is used by the eye surgery robot system to learn the sets of the microscope images and their corresponding ground-truth data using the HSV color information as feature values. The GMM model is then used to estimate the regions of the micropipette and its shadow in a real-time microscope image as well as their tip positions, which are utilized for the autonomous robotic position control. After the planar positioning is performed using the visual servoing method, the micropipette is moved to approach the eye ground until the distance between the tip of the micropipette and its shadow is either equal to or less than a predefined threshold. Thus, the robot could accurately approach the eye ground and safely stop before contact. An autonomous positioning task is performed ten times in a simulated eye-surgery setup, and the robot stops at an average height of 1.37 mm from a predefined target when the threshold is 1.4 mm. Further enhancement in the estimation accuracy in the image processing would improve the positioning accuracy and safety.

As a hard and brittle material, glass is difficult to precisely cut with high efficiency. Although various attempts at ductile cutting of glass with high cutting depth have been reported, the low efficiency of the cutting process remains problematic. In order to achieve high-efficiency and precision cutting of glass, this paper proposes selective laser-assisted milling (SLAM). In this method, a fiber laser that has a wavelength out of the absorption band of glass is absorbed only into the small area where the black-body coating is put, and the selectively heated area is removed with a cutting tool. The experimental results of this study have demonstrated that SLAM reduces the arithmetic average of the roughness profile by 74% compared with conventional cutting. An observational analysis of the generated chips revealed that the application of SLAM changed the morphology of the chips from the crack type to the quasi-continuous type. These results demonstrate the feasibility of the high-efficiency and precision cutting of glass.

Precision machining of glass has been receiving attention in various applications because of the use of glass interposers in layered semiconductors or glass substrates for microfluidic chips. These applications require complicated and three-dimensional machining for further product functionality. Etching is conventionally used for precision machining of glass. However, applying etching for three-dimensional machining is difficult, and thus, a method which is applicable to three-dimensional machining of glass is needed. Cutting is a method applicable to three-dimensional machining. However, precision cutting of glass is difficult because glass is a hard and brittle material. In this research, we applied laser-assisted machining for cutting of glass. We first conducted laser-assisted milling for plane surface cutting. We then proposed laser-assisted drilling for glass drilling to perform the three-dimensional cutting of glass by laser-assisted machining. Through the experimental analyses, we demonstrated the feasibility of the precision and three-dimensional cutting of glass.

Cutting (including sawing and drilling) is a common procedure in orthopedics. Although it is widely used, cutting is associated with surgical problems, such as bone breakthrough and necrosis. In this study, the phenomenon of large fractures was analyzed with a discontinuum model of a bone by initially predicting crack propagation. A cutting method utilizing impacts by vibration was then proposed, and experiments were performed. The results indicated that the principal cutting force decreased by more than 80% in each cutting direction. The findings suggest that the method can realize low load, high efficiency, and high accuracy of bone machining.

Thoracoscopic esophageal atresia/tracheoesophageal fistula (EA/TEF) repair in neonates is technically difficult because of the small working space and fragility of tissues. This study aimed to show the construct validity of the neonatal EA/TEF simulator by video-based assessment of endoscopic suturing skill.A rapid-prototyped neonatal chest model with an artificial esophagus model similar to the actual neonatal esophagus was developed. Forty pediatric surgeons performed an endoscopic intracorporeal suturing task and a knot-tying task using the model, and a questionnaire survey was administered. Each task was video recorded and assessed using two skill assessment methods (the 29-point checklist method and the error assessment sheet method). The task completion time and the number of manipulations were measured.With regard to experience in performing thoracoscopic TEF repair, the experienced surgeons (ESs, ≥3 EA/TEF repair experiences, n = 6) were significantly superior to the inexperienced surgeons (ISs,3 experiences, n = 34) in all metrics. Upon comparison by the pediatric Endoscopic Surgical Skill Qualification (ESSQ) status, there were no significant differences in all metrics between the ESSQ-qualified (n = 15) and nonqualified (n = 25) surgeons. The qualified ESs (n = 6) were significantly superior to the qualified ISs (n = 9) in all metrics.Video-based endoscopic surgical skill assessment using the neonatal EA/TEF simulator could differentiate ESs from ISs. The construct validity of the simulator was demonstrated, and the simulator would be useful especially for practicing thoracoscopic EA/TEF procedures.

The present authors have been developing a master-slave neurosurgical robot and its intelligent control for tasks in the deep and narrow spaces of the brain. This paper proposes a robotic autonomous control method for avoiding possible collisions between the shaft of a surgical robotic instrument and the surrounding tissues. To this end, a new robotic simulator was developed and used to evaluate the proposed method. The results showed the proof of concept of the proposed autonomous collision avoidance, which has the potential to enhance the safety of robotic neurosurgery in deep and narrow spaces.

Ultrashort pulse laser processing that facilitates high-speed and fine processing of glass materials has received considerable attention in recent years, despite mechanical processing or etching having been the mainstream methods. However, the physical mechanisms of this technique and the influence of various parameters, such as the processing conditions and physical properties of the processed material, on generated shapes are not yet fully understood. In this work, we comprehensively investigated the influence of various parameters of ultrashort pulse lasers on the processing mechanisms through experiments conducted by changing the wavelength, pulse width, repetition rate, and pulse energy over a wide range. The physical effects of the laser parameters on the reflection of light and heat generation were discussed by analyzing the experimental results, and the influence of the parameters on the generated shapes, processing speed, and saturated depth was clarified. In addition, cracks around the ablated area, which are one of the problems concerning glass processing with ultrashort pulse lasers, were observed, and the influence of the pulse energy on the cracks was evaluated. It is expected that this research will allow for a thorough understanding of the laser parameters that are suitable for glass processing and widen the range of laser processing applications.

When measuring the surface shape of a transparent sample using wavelength-tuning Fizeau interferometry, the calculated phase is critically determined by not only phase-shift errors, but also by coupling errors between higher harmonics and phase-shift errors. This paper presents the derivation of a 13 -sample phase-shifting algorithm that can compensate for miscalibration and first-order nonlinearity of phase shift, coupling errors, and bias modulation of the intensity, and has strong suppression of the second reflective harmonic effect. The characteristics of the 13 -sample algorithm are estimated with respect to Fourier representation in the frequency domain. The phase error of measurement performed using the 13 -sample algorithm is discussed and compared with those of measurements obtained using other conventional phase-shifting algorithms. Finally, the surface shape of a fused silica wedge plate obtained using a wavelength tuning Fizeau interferometer and the 13 -sample algorithm are presented. The experimental results indicate that the surface shape measurement accuracy for a transparent fused silica plate is 3 nm. The accuracy of the measurement is discussed by comparing the amplitudes of the crosstalk noise calculated using other conventional algorithms.

Yttria-stabilized tetragonal zirconia polycrystal (Y-TZP) is a promising material for dental restoratives. The fabrication method of such dental restoratives is usually as follows: (1) hot pressing of zirconia powder (2) machining of pre-sintered zirconia (3) sintering. However, the current method has disadvantages such as low geometrical accuracy and long process time. It was adopted since the fully sintered Y-TZP is extremely difficult to machine. If a suitable milling process for fully sintered Y-TZP can be established, it will enable an accurate, efficient, and cost-effective process. The milling process is important for three-dimensional free-form fabrication, which is required for manufacturing dental restoratives. In this study, we propose a thermally assisted milling process in which a fully sintered Y-TZP workpiece is directly heated to several hundred degrees by a heater to soften it and enhance its machinability. In a practical situation, the machinability must be predicted in advance to determine the proper machining conditions, including the workpiece temperature. In order to make such predictions, the machining phenomena occurring during thermally assisted machining must be understood. In addition, the quantitative relationships between the workpiece temperature, cutting conditions, and the resulting machinability must be characterized. In the present study, we conducted a series of straight-milling experiments to observe the machining phenomena and obtain the quantitative relationships between the machining conditions and the machinability of Y-TZP using the proposed thermally assisted milling process. A series of experiments were performed using the central composite design method. The results of the experiments revealed that raising the workpiece temperature significantly reduces cutting resistance and the tool wear. Although a greater amount of fracturing occurred when the workpiece was heated, the resulting roughness of the bottom surface of the grooves did not increase. Quantitative relationships between the machining conditions, including the workpiece temperature, and the machinability were established using a curve-fitting method.