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- 저자 : Shingo Kamiya (검색결과 5 건)
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Tomonori Shirasaka,Shingo Kunioka,Masahiko Narita,Ryohei Ushioda,Keisuke Shibagaki,Yuta Kikuchi,Naohiro Wakabayashi,Natsuya Ishikawa,Hiroyuki Kamiya 대한흉부외과학회 2021 Journal of Chest Surgery (J Chest Surg) Vol.54 No.5
Background: Achieving external access to and manual occlusion of the left atrial ap- pendage (LAA) during minimally invasive mitral valve surgery (MIMVS) through a small right thoracotomy is difficult. Occlusion of the LAA using an epicardial closure device seems quite useful compared to other surgical techniques. Methods: Fourteen patients with atrial fibrillation underwent MIMVS with concomitant surgical occlusion of the LAA using double-layered endocardial closure stitches (n=6, endocardial suture group) or the AtriClip Pro closure device (n=8, AtriClip group) at our institution. The primary safety endpoint was any device-related adverse event, and the primary efficacy endpoint was successful complete occlusion of blood flow into the LAA as assessed by transthoracic echocardiography at hospital discharge. The primary efficacy endpoint for stroke reduction was the occurrence of ischemic or hemorrhagic neurologic events. Results: All patients underwent LAA occlusion as scheduled. The cardiopulmonary by- pass and aortic cross-clamp times in the endocardial suture group and the AtriClip group were 202±39 and 128±41 minutes, and 213±53 and 136±44 minutes, respectively (p=0.68, p=0.73). No patients in either group experienced any device-related serious adverse events, incomplete LAA occlusion, early postoperative stroke, or neurologic complication. Conclusion: Epicardial LAA occlusion using the AtriClip Pro during MIMVS in patients with mitral valve disease and atrial fibrillation is a simple, safe, and effective adjunctive procedure.
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Naoki Asatani,Tohru Kamiya,Shingo Mabu,Shoji Kido 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
According to the 2016 World Health Organization (WHO) survey, respiratory diseases are serious diseases that account for four of the top ten causes of death in the world, accounting for more than 8 million deaths worldwide. Currently, the diagnosis of respiratory disease is made by auscultation, but in order to make an accurate diagnosis, a number of abnormal patterns of respiratory sounds need to be memorized, and the results of the diagnosis are dependent on the proficiency of the physician. Therefore, a computer aided diagnosis (CAD) system is needed to quantitatively classify the respiratory sounds and output the results as a "second opinion". In this paper, a short-time Fourier transformed spectrogram, a Constant-Q transformed logarithmic frequency spectrogram, and a continuous wavelet transformed scalogram are simultaneously input to VGG16 which is one of the network models of CNN(Convolutional Neural Network) and classified by LSTM (Long short-term memory). The proposed method is applied to 26 respiratory sounds, and the 0.90 of accuracy, sensitivity of 0.97, and specificity of 0.90 is obtained.
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Classification of Respiratory Sounds by Generated Image and Improved CRNN
Naoki Asatani,Tohru Kamiya,Shingo Mabu,Shoji Kido 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
The death toll from respiratory illness reached nearly 8 million in 2019. Auscultation is used to diagnose for respiratory illness. Highly accurate diagnosis is required to reduce the number of deaths. However, unlike diagnostic imaging, auscultation of respiratory sounds could not visualize the diagnostic results. In addition, since there is a problem that the experience of a doctor affects the diagnosis results, it is required to develop a diagnostic system for quantitative analysis. In recent years, the development of a diagnostic system using the ICBHI 2017 Challenge Respiratory Sound Database has been carried out in the field of respiratory sound analysis. However, the proposed system still has accuracy problems. Therefore, in this study, we improve the proposed method by classifying the improved CRNN (Convolutional Recurrent Neural Network) by inputting multiple respiratory sound images. As a result, Sensitivity: 0.64, Specificity: 0.83, Average Score: 0.74, Harmonic Score: 0.72 were obtained, and excellent results were achieved compared with other methods.
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Automatic Classification of Respiratory Sound Considering Hierarchical Structure
Manami Tabata,Huimin Lu,Tohru Kamiya,Shingo Mabu,Shoji Kido 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Respiratory diseases are one of the leading causes of death worldwide. Approximately 8 million people die annually from respiratory diseases. Diagnosis is made primarily by auscultation using a stethoscope. The lack of quantitative criteria makes diagnosis difficult in the field where physicians are in short supply. To solve this problem, a computer aided diagnosis (CAD) system that quantitatively analyzes and classifies respiratory sounds and outputs them as a second opinion is needed. In this paper, HPSS (Harmonious / Percussive Sound Separation) is used to separate abnormal respiratory sound features. Images are generated from the spectral envelopes obtained by linear prediction coefficients (LPC) for each of the three types of respiratory sound data before separation. The CNN (convolutional neural networks) framework based on hierarchical structure of the correct labels is introduced. The proposed method was applied to the dataset used in the International Conference on Biomedical and Health Informatics (ICBHI) 2017 Challenge. As a result, we obtained a sensitivity of 63.5%, specificity of 85.1%, average score of 74.3%, harmonic score of 72.7%, area under the curve of 87.8%, and false negative rate of 24.5%, respectively.
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Integration of UML with Simulink into Embedded Software Engineering
Tibor Farkas,Emi Meiseki,Carsten Neumann,Kunihisa Okano,Andreas Hinnerichs,Shingo Kamiya 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
Today, control algorithms of electronic in-vehicle functions are implemented on various networked control units with different software architectures and designs. Special effort is needed when integrating those artifacts and software components from different sources to overcome the limits of efficient integration of model-based design into the embedded development. This paper focuses on the advantages of model-based development by mixing object-oriented and signal-oriented modeling concepts together and referencing (generated) legacy software components to get an overall software design. Therefore, we present an integration methodology of UML and Simulink modeling concepts to a traditional automotive software engineering process. Furthermore we describe the model-based engineering of a car-door control system as an example.
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