| 小林 誠人 | M, 2回目発表 | サイバネティクス・リアリティ工学 | 清川 清, | 小笠原 司, | 酒田 信親, | 磯山 直也 | ||
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title: A Flying Sensation Display by Using a Jet Pool and Underwater VR
abstract: In the past, the feeling of flight was presented by hanging the body or raising it by wind pressure. However, there was a problem that the load on the user was heavy when hanging the body, and it was extremely costly when it was lifted by wind pressure. In addition, the method of riding on a pedestal with a mechanical device that presents a feeling of floating. However, there was a lack of floating feeling because the body could not be floated on land. Therefore, in this research, we propose a method of presenting a flight sensation using the environment of underwater. Using underwater buoyancy By giving a feeling of floating and reproducing the feeling of speed using a stream of water, we aim to present a natural feeling of flight with a low physical load on the experiencer. language of the presentation: Japanese | ||||||||
| 萩岡 宣旭 | M, 2回目発表 | 生体医用画像 | 佐藤 嘉伸, | 小笠原 司, | 大竹 義人, | Soufi Mazen, | 上村 圭亮 | |
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title: Evaluation of OpenSim Biomechanical Analysis with Muscle Model Derived from Fiber Tractography in High-Resolution Cryo-section Images
abstract: In biomechanical simulation models, muscles are approximated as linear fibers based on the overall geometry of muscle volume. However, the fibers are derived without considering the subject-specific internal structure characteristics in usually, such as fiber orientation and attachment point. In this study, we propose to model the muscle fibers derived from high-resolution images based on a fiber tractography approach, thus reflecting the internal structure in biomechanical simulation models. We modeled the manually adapting fibers by adapting a generic simulation model to fit with the tractography-based fiber orientations. The approach was applied to the fibers in the gluteus maximus muscle, and the muscle activation were assessed. Compared with the generic model, we obtained a difference in the muscle activation. It is now possible to express features of the lower part of the gluteus maximus muscles that are not represented in the general model. This possibly indicates an impact of the derived fiber orientation on the simulation results; further validation of personalization techniques is needed. language of the presentation: Japanese | ||||||||
| 槇野 大樹 | M, 2回目発表 | 生体医用画像 | 佐藤 嘉伸, | 小笠原 司, | 別所 康全, | 大竹 義人, | Soufi Mazen, | 上村 圭亮 |
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title: Construction of statistical model of cup and stem placement for surgical planning in total hip arthroplasty
abstract: In total hip arthroplasty (THA), surgeons need to plan an appropriate implant types, sizes, positions and orientations, considering changes in the range of motion, leg length, bone and implant stability, and load balance. In one of our previous work, we built a statistical shape model using preoperative CT images and surgical plans as the training data, and implemented an automatic surgical planning system. In a previous study, we constructed a statistical shape model using preoperative CT images and preoperative planning as training data, and planned the surgery automatically. However, the bone geometry for the training data was manually extracted in small cases. In recent years, deep learning methods have been proposed and their applicability has been increased by improving the accuracy. In this study, we train a statistical model using the bone shape of a large number of cases extracted automatically by segmentation using deep learning. In addition, we have developed a system that automatically measures hip joint functions such as range of motion of the hip joint and analyzes the bone shape extracted automatically for the automatic surgical planning system. language of the presentation: Japanese | ||||||||