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During neurosurgery, brain deformation occurs because of gravity and leakage of the cerebrospinal fluid (CSF), which is referred to as brain shift. Brain shift is a serious problem in neuronavigation because neuronavigation relies on preoperatively taken medical images. This paper presents a brain shift estimation method based on hydrostatics and dynamic FEM, assuming that gravity and leakage of CSF are the main reasons for brain shift. The accuracy of the proposed method was verified via basic experiments conducted using elastic gelatin cubes. In addition, a 3D brain model was created using preoperative medical images of a patient and brain shift estimation simulations were performed. Their accuracy was verified by comparing the simulation results with the actual brain shift during neurosurgery. Assuming that the node in the most anterior position of the frontal lobe and the node in the highest position of the parietal lobe before the brain shift respectively remain in the most anterior position and the highest position even after the brain shift, the corresponding regions before and after the brain shift were searched and the deformations were evaluated. In this error analysis, the maximum estimation error was 4.4 mm. Furthermore, a region of 40 mm x 30 mm in the frontal lobe was chosen as the region of interest (ROI), and the surface errors in the ROI between the intraoperative MRI images and the simulated shifted brain were analyzed. The mean absolute error (MAE) between the surfaces along the z-axis (the direction of gravity) in the ROI was 3.7 mm (maximum absolute error was 8.8 mm). The proposed method was sufficiently simple for computing the brain shift in real-time. The expected contribution of this study toward improving the neuronavigational error and enhancing the safety of neurosurgery will be beneficial for hospitals, especially when the intraoperative MRI cannot be performed.

The purpose of this study was to characterize the motion features of surgical devices associated with laparoscopic surgical competency and build an automatic skill-credential system in porcine cadaver organ simulation training. Participants performed tissue dissection around the aorta, dividing vascular pedicles after applying Hem-o-lok (tissue dissection task) and parenchymal closure of the kidney (suturing task). Movements of surgical devices were tracked by a motion capture (Mocap) system, and Mocap-metrics were compared according to the level of surgical experience (experts: >= 50 laparoscopic surgeries, intermediates: 10-49, novices: 0-9), using the Kruskal-Wallis test and principal component analysis (PCA). Three machine-learning algorithms: support vector machine (SVM), PCA-SVM, and gradient boosting decision tree (GBDT), were utilized for discrimination of the surgical experience level. The accuracy of each model was evaluated by nested and repeated k-fold cross-validation. A total of 32 experts, 18 intermediates, and 20 novices participated in the present study. PCA revealed that efficiency-related metrics (e.g., path length) significantly contributed to PC 1 in both tasks. Regarding PC 2, speed-related metrics (e.g., velocity, acceleration, jerk) of right-hand devices largely contributed to the tissue dissection task, while those of left-hand devices did in the suturing task. Regarding the three-group discrimination, in the tissue dissection task, the GBDT method was superior to the other methods (median accuracy: 68.6%). In the suturing task, SVM and PCA-SVM methods were superior to the GBDT method (57.4 and 58.4%, respectively). Regarding the two-group discrimination (experts vs. intermediates/novices), the GBDT method resulted in a median accuracy of 72.9% in the tissue dissection task, and, in the suturing task, the PCA-SVM method resulted in a median accuracy of 69.2%. Overall, the mocap-based credential system using machine-learning classifiers pr

Background The purpose of this study was to find a utility of a newly developed 3D-printed sinus model and to evaluate the educational benefit of simulation training with the models for functional endoscopic sinus surgery (FESS). Material and methods Forty-seven otolaryngologists were categorized as experts (board-certified physicians with >= 200 experiences of FESS, n = 9), intermediates (board-certified physicians with <200 experiences of FESS, n = 19), and novices (registrars, n = 19). They performed FESS simulation training on 3D-printed models manufactured from DICOM images of computed tomography (CT) scan of real patients. Their surgical performance was assessed with the objective structured assessment of technical skills (OSATS) score and dissection quality evaluated radiologically with a postdissection CT scan. First we evaluated the face, content, and constructive values. Second we evaluated the educational benefit of the training. Ten novices underwent training (training group) and their outcomes were compared to the remaining novices without training (control group). The training group performed cadaveric FESS surgeries before and after the repetitive training. Results The feedback from experts revealed high face and content value of the 3D-printed models. Experts, intermediates, and novices demonstrated statistical differences in their OSATS scores (74.7 +/- 3.6, 58.3 +/- 10.1, and 43.1 +/- 11.1, respectively, p < .001), and dissection quality (81.1 +/- 13.1, 93.7 +/- 15.1, and 126.4 +/- 25.2, respectively, p < .001). The training group improved their OSATS score (41.1 +/- 8.0 to 61.1 +/- 6.9, p < .001) and dissection quality (122.1 +/- 22.2 to 90.9 +/- 10.3, p = .013), while the control group not. After training, 80% of novices with no prior FESS experiences completed surgeries on cadaver sinuses. Conclusion Repeated training using the models revealed an initial learning curve in novices, which was confirmed in cadaveric mock FESS surgeri

Background The purpose of this study was to find a utility of a newly developed 3D-printed sinus model and to evaluate the educational benefit of simulation training with the models for functional endoscopic sinus surgery (FESS). Material and methods Forty-seven otolaryngologists were categorized as experts (board-certified physicians with >= 200 experiences of FESS, n = 9), intermediates (board-certified physicians with <200 experiences of FESS, n = 19), and novices (registrars, n = 19). They performed FESS simulation training on 3D-printed models manufactured from DICOM images of computed tomography (CT) scan of real patients. Their surgical performance was assessed with the objective structured assessment of technical skills (OSATS) score and dissection quality evaluated radiologically with a postdissection CT scan. First we evaluated the face, content, and constructive values. Second we evaluated the educational benefit of the training. Ten novices underwent training (training group) and their outcomes were compared to the remaining novices without training (control group). The training group performed cadaveric FESS surgeries before and after the repetitive training. Results The feedback from experts revealed high face and content value of the 3D-printed models. Experts, intermediates, and novices demonstrated statistical differences in their OSATS scores (74.7 +/- 3.6, 58.3 +/- 10.1, and 43.1 +/- 11.1, respectively, p < .001), and dissection quality (81.1 +/- 13.1, 93.7 +/- 15.1, and 126.4 +/- 25.2, respectively, p < .001). The training group improved their OSATS score (41.1 +/- 8.0 to 61.1 +/- 6.9, p < .001) and dissection quality (122.1 +/- 22.2 to 90.9 +/- 10.3, p = .013), while the control group not. After training, 80% of novices with no prior FESS experiences completed surgeries on cadaver sinuses. Conclusion Repeated training using the models revealed an initial learning curve in novices, which was confirmed in cadaveric mock FESS surgeries. Level of ev

Tracheal suctioning is an important procedure to maintain airway patency by removing secretions. Today, suctioning operators include not only medical staff, but also family caregivers. The use of a simulation system has been noted to be the most effective way to learn the tracheal suctioning technique for operators. While the size of the trachea varies across different age groups, the artificial trachea model in the simulation system has only one fixed model. Thus, this study aimed to construct multiple removable trachea models according to different age groups. We enrolled 20 patients who had previously received proton beam therapy in our institution and acquired the treatment planning computed tomography (CT) image data. To construct the artificial trachea model for three age groups (children, adolescents and young adults, and adults), we analyzed the three-dimensional coordinates of the entire trachea, tracheal carina, and the end of the main bronchus. We also analyzed the diameter of the trachea and main bronchus. Finally, we evaluated the accuracy of the model by analyzing the difference between the constructed model and actual measurements. The trachea model was 8 cm long for children and 12 cm for adolescents and young adults, and for adults. The angle between the trachea and bed was about 20 degrees, regardless of age. The mean model accuracy was less than 0.4 cm. We constructed detachable artificial trachea models for three age groups for implementation in the endotracheal suctioning training environment simulator (ESTE-SIM) based on the treatment planning CT image. Our constructed artificial trachea models will be able to provide a simulation environment for various age groups in the ESTE-SIM.

Background Our aim was to characterize the motions of multiple laparoscopic surgical instruments among participants with different levels of surgical experience in a series of wet-lab training drills, in which participants need to perform a range of surgical procedures including grasping tissue, tissue traction and dissection, applying a Hem-o-lok clip, and suturing/knotting, and digitize the level of surgical competency. Methods Participants performed tissue dissection around the aorta, dividing encountered vessels after applying a Hem-o-lok (Task 1), and renal parenchymal closure (Task 2: suturing, Task 3: suturing and knot-tying), using swine cadaveric organs placed in a box trainer under a motion capture (Mocap) system. Motion-related metrics were compared according to participants' level of surgical experience (experts: 50 <= laparoscopic surgeries, intermediates: 10-49, novices: 0-9), using the Kruskal-Wallis test, and significant metrics were subjected to principal component analysis (PCA). Results A total of 15 experts, 12 intermediates, and 18 novices participated in the training. In Task 1, a shorter path length and faster velocity/acceleration/jerk were observed using both scissors and a Hem-o-lok applier in the experts, and Hem-o-lok-related metrics markedly contributed to the 1st principal component on PCA analysis, followed by scissors-related metrics. Higher-level skills including a shorter path length and faster velocity were observed in both hands of the experts also in tasks 2 and 3. Sub-analysis showed that, in experts with 100 <= cases, scissors moved more frequently in the "close zone (0 <= to < 2.0 cm from aorta)" than those with 50-99 cases. Conclusion Our novel Mocap system recognized significant differences in several metrics in multiple instruments according to the level of surgical experience. "Applying a Hem-o-lok clip on a pedicle" strongly reflected the level of surgical experience, and zone-metrics may be a promising tool t

Tracheal suctioning is an important procedure to maintain airway patency by removing secretions. Today, suctioning operators include not only medical staff, but also family caregivers. The use of a simulation system has been noted to be the most effective way to learn the tracheal suctioning technique for operators. While the size of the trachea varies across different age groups, the artificial trachea model in the simulation system has only one fixed model. Thus, this study aimed to construct multiple removable trachea models according to different age groups. We enrolled 20 patients who had previously received proton beam therapy in our institution and acquired the treatment planning computed tomography (CT) image data. To construct the artificial trachea model for three age groups (children, adolescents and young adults, and adults), we analyzed the three-dimensional coordinates of the entire trachea, tracheal carina, and the end of the main bronchus. We also analyzed the diameter of the trachea and main bronchus. Finally, we evaluated the accuracy of the model by analyzing the difference between the constructed model and actual measurements. The trachea model was 8 cm long for children and 12 cm for adolescents and young adults, and for adults. The angle between the trachea and bed was about 20 degrees, regardless of age. The mean model accuracy was less than 0.4 cm. We constructed detachable artificial trachea models for three age groups for implementation in the endotracheal suctioning training environment simulator (ESTE-SIM) based on the treatment planning CT image. Our constructed artificial trachea models will be able to provide a simulation environment for various age groups in the ESTE-SIM.

Background: To provide safe tracheal suctioning, the American Association of Respiratory Care guideline discusses the length of suctioning catheter, but the most effective tracheal suctioning catheter technique is still unknown. Objective: The aim of this study is to compare the amount of simulated secretion produced by five different handlings of a catheter at two different viscosities and in two different models to discover the most effective suctioning maneuver in the various mucus conditions. Design: In vitro experimental design. Methods: The amount of secretion aspirated by our researcher's manipulation of a suctioning catheter was measured. The tip of the catheter was recorded using a high-speed video camera to visualize the secretion motion. Results: The most effective suctioning technique differed depending on the viscosity of the secretion. There were no significant differences between five suctioning methods applied to high-viscosity phlegm in a tracheal membrane model, but the flexion technique was the most efficient for low-viscosity secretion. Conclusions: Our results imply that the flexion technique was reasonably safe and the most effective of these five methods for low-viscosity secretion.

Background: To provide safe tracheal suctioning, the American Association of Respiratory Care guideline discusses the length of suctioning catheter, but the most effective tracheal suctioning catheter technique is still unknown. Objective: The aim of this study is to compare the amount of simulated secretion produced by five different handlings of a catheter at two different viscosities and in two different models to discover the most effective suctioning maneuver in the various mucus conditions. Design: In vitro experimental design. Methods: The amount of secretion aspirated by our researcher's manipulation of a suctioning catheter was measured. The tip of the catheter was recorded using a high-speed video camera to visualize the secretion motion. Results: The most effective suctioning technique differed depending on the viscosity of the secretion. There were no significant differences between five suctioning methods applied to high-viscosity phlegm in a tracheal membrane model, but the flexion technique was the most efficient for low-viscosity secretion. Conclusions: Our results imply that the flexion technique was reasonably safe and the most effective of these five methods for low-viscosity secretion.

Humanoid Robots: Modeling and Control provides systematic presentation of the models used in the analysis, design and control of humanoid robots. The book starts with a historical overview of the field, a summary of the current state of the art achievements and an outline of the related fields of research. It moves on to explain the theoretical foundations in terms of kinematic, kineto-static and dynamic relations. Further on, a detailed overview of biped balance control approaches is presented. Models and control algorithms for cooperative object manipulation with a multi-finger hand, a dual-arm and a multi-robot system are also discussed. One of the chapters is devoted to selected topics from the area of motion generation and control and their applications. The final chapter focuses on simulation environments, specifically on the step-by-step design of a simulator using the Matlab® environment and tools. This book will benefit readers with an advanced level of understanding of robotics, mechanics and control such as graduate students, academic and industrial researchers and professional engineers. Researchers in the related fields of multi-legged robots, biomechanics, physical therapy and physics-based computer animation of articulated figures can also benefit from the models and computational algorithms presented in the book.Provides a firm theoretical basis for modelling and control algorithm designGives a systematic presentation of models and control algorithmsContains numerous implementation examples demonstrated with 43 video clips

A symmetry position/force hybrid control framework for cooperative object transportation tasks with multiple humanoid robots is proposed in this paper. In a leader-follower type cooperation, follower robots plan their biped gaits based on the forces generated at their hands after a leader robot moves. Therefore, if the leader robot moves fast (rapidly pulls or pushes the carried object), some of the follower humanoid robots may lose their balance and fall down. The symmetry type cooperation discussed in this paper solves this problem because it enables all humanoid robots to move synchronously. The proposed framework is verified by dynamic simulations.

研究代表者らは、これまで、ソフトロボットと呼ぶ従来のロボットの設計思想とは根本から異なる新しいロボットを提案してきた。このロボットは、機構の柔軟性を積極的に活用することで環境に対し高い安全性を確保できると同時に、高度な技能を実現できる可能性を持うている。このソフトロボットの概念を宇宙遠隔操作システムに適用した工学を宇宙用ソフトテレロボティクスと呼ぶ。本研究プロジェクトにおいては、宇宙用ソフトテレロボッティクスを実現するために必要な基礎技術の確立を目指した。具体的には、宇宙用ソフトロボットのハードウェアおよびその特徴を生かした制御手法の開発、直感的な情報提示が可能なオペレータ支援システムの、パラレルマニピュレータを用いたハイブリヅド型微小重力シミュレータの開発を行った。, NASDA Special Publication, 宇宙開発事業団特別報告

Original contains color illustrations, Meeting Information: The 3rd Workshop on Integration of EFD and CFD (January 25, 2010. AKIHABARA Convention Hall) Chiyoda-ku, Tokyo, Japan, 形態: カラー図版あり, 会議情報: 第3回EFD/CFD融合ワークショップ (2010年1月25日 秋葉原コンベンションホール) 千代田区, 東京