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International Joint Conference on Neural Networks

作者： Dongxu Gao Jiangtao Cao Zhaojie Ju Department of Information and Control Engineering Liaoning Shihua University Intelligent Systems and Biomedical Robotics group School of Creative Technologies University of Portsmouth

ISBN: (纸本)9781479914821

The current sparse representation tracking algorithm is not suitable for the objects that illumination changes, scale changes, the object color is similar with the surrounding region, and occlusion etc, what's more, it is hard to realize real-time tracking for solving an l1 norm related minimization problems. An optimal algorithm is introduced by exploiting an accelerated proximal gradient approach which contains some improvements of particle filter function, sparse representation alterative weights and coefficient. These improvements not only reduce the influences of appearance change but also make the tracker runs in real time. Both qualitative and quantitative evaluations demonstrate that the proposed tracking algorithm has favorably better performance than several state-of-the-art trackers using challenging benchmark image sequences, and significantly reduces the computing cost.

关键词： Target tracking Principal component analysis Minimization Lighting Mathematical model Real-time systems

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A web-based, hospital-wide health care-associated bloodstream infection surveillance and classification system: Development and evaluation

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JMIR Medical Informatics 2015年第3期3卷 e31页

作者： Tseng, Yi-Ju Wu, Jung-Hsuan Lin, Hui-Chi Chen, Ming-Yuan Ping, Xiao-Ou Sun, Chun-Chuan Shang, Rung-Ji Sheng, Wang-Huei Chen, Yee-Chun Lai, Feipei Chang, Shan-Chwen Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan Computational Health Informatics Program Boston Children's Hospital Boston MA United States Department of Electrical Engineering National Taiwan University Taipei Taiwan Center for Infection Control National Taiwan University Hospital Taipei Taiwan National Taiwan University Hospital Information Systems Office Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Internal Medicine National Taiwan University Hospital and College of Medicine Taipei Taiwan National Health Research Institutes National Institute of Infectious Diseases and Vaccinology Miaoli Taiwan

Background: Surveillance of health care-associated infections is an essential component of infection prevention programs, but conventional systems are labor intensive and performance dependent. Objective: To develop an automatic surveillance and classification system for health care-associated bloodstream infection (HABSI), and to evaluate its performance by comparing it with a conventional infection control personnel (ICP)-based surveillance system. Methods: We developed a Web-based system that was integrated into the medical information system of a 2200-bed teaching hospital in Taiwan. The system automatically detects and classifies HABSIs. Results: In this study, the number of computer-detected HABSIs correlated closely with the number of HABSIs detected by ICP by department (n=20;r=.999 P<.001) and by time (n=14;r=.941;P<.001). Compared with reference standards, this system performed excellently with regard to sensitivity (98.16%), specificity (99.96%), positive predictive value (95.81%), and negative predictive value (99.98%). The system enabled decreasing the delay in confirmation of HABSI cases, on average, by 29 days. Conclusions: This system provides reliable and objective HABSI data for quality indicators, improving the delay caused by a conventional surveillance system. © 2020 JMIR Publications Inc. All rights reserved.

关键词： Health care-associated infection Infection control Information systems Surveillance Web-based services

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Monocular Camera and IMU Integration for Indoor Position Estimation

Monocular Camera and IMU Integration for Indoor Position Est...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Yinlong Zhang Jindong Tan Ziming Zeng Wei Liang Ye Xia Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee Information and Control Engineering Faculty Shenyang Jianzhu University

ISBN: (纸本)9781424479276

This paper presents a monocular camera (MC) and inertial measurement unit (IMU) integrated approach for indoor position estimation. Unlike the traditional estimation methods, we fix the monocular camera downward to the floor and collect successive frames where textures are orderly distributed and feature points robustly detected, rather than using forward oriented camera in sampling unknown and disordered scenes with pre-determined frame rate and autofocus metric scale. Meanwhile, camera adopts the constant metric scale and adaptive frame rate determined by IMU data. Furthermore, the corresponding distinctive image feature point matching approaches are employed for visual localizing, i.e., optical flow for fast motion mode;Canny Edge Detector & Harris Feature Point Detector & Sift Descriptor for slow motion mode. For superfast motion and abrupt rotation where images from camera are blurred and unusable, the Extended Kalman Filter is exploited to estimate IMU outputs and to derive the corresponding trajectory. Experimental results validate that our proposed method is effective and accurate in indoor positioning. Since our system is computationally efficient and in compact size, it's well suited for visually impaired people indoor navigation and wheelchaired people indoor localization.

关键词： Cameras Feature extraction Estimation Acceleration Trajectory Navigation Vectors

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Apical four-chamber echocardiography segmentation using Marker-controlled Watershed segmentation

Apical four-chamber echocardiography segmentation using Mark...

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IEEE EMBS Conference on biomedical engineering and Sciences (IECBES)

作者： Nonthaporn Nakphu Dyah Ekashanti Octorina Dewi Muhammad Qurhanul Rizqie Eko Supriyanto Ahmad 'Athif Mohd Faudzi Dolwin Ching Ching Kho Suhaini Kadiman Panrasee Rittipravat Department of Biomedical Engineering Mahidol University Salaya Nakorn Pathom Thailand Universiti Teknologi Malaysia Skudai Johor MY Faculty of Biosciences and Medical Engineering Universitas Sriwijaya Indonesia Department of Biomedical Engineering Faculty of Engineering Mahidol University Johor Malaysia Control and Mechatronics Engineering Department University Technology Malaysia Skudai Johor Malaysia National Heart Institute Kuala Lumpur Malaysia Department of Biomedical Engineering Mahidol University Salaya Salaya Nakorn Pathom Thailand

Echocardiography provides information about size, shape, and function of heart to create the image. Apical four-chamber echocardiography can be obtained by placing the ultrasound probe at the apex of the left ventricle. Such view enables to analyze heart abnormalities. In this regard, chamber quantification is recommended to evaluate the heart volume by defining the endocardial border of the chambers. Image segmentation that subdivides an image into different regions may be suitable to analyze the chambers. In this study, we propose a Marker-controlled Watershed segmentation method. It involves Watershed Transform, internal and external markers, and morphological processing. The advantage is that it can control over-segmentation due to noise and other local irregularities. We tested the proposed method on an apical four-chamber echocardiography image and a model image. We also compared the segmentation result with an Active Contour-based segmentation method. The results show that the Watershed Transform performs better than Active Contour.

关键词： Image segmentation Echocardiography Heart Noise Mathematical model Shape Educational institutions

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Identification of linear parameter varying systems with missing output data using generalized expectation-maximization algorithm 19

Identification of linear parameter varying systems with miss...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Yang, X. Xiong, W. Huang, B. Gao, H. Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin Heilongjiang150080 China Jiangnan University Wuxi Jiangsu214122 China Department of Chemical and Materials Engineering University of Alberta EdmontonABT6G 2G6 Canada Research Institute of Mechatronics and Automation Bohai University Jinzhou121013 China

ISBN: (纸本)9783902823625

This paper is concerned with the identification problems of linear parameter varying (LPV) systems with randomly missing output data. Since one local linearized model cannot capture the global dynamics of the nonlinear industrial process, the multiple-model LPV model in which the global model is constructed by smoothly weighted combination of multiple local models is considered here. The problem of missing output variables data is commonly encountered in practice. In order to handle the multiple-model identification problems of LPV systems with incomplete data, the local model is taken to have a finite impulse response (FIR) model structure and the generalized expectation-maximization (EM) algorithm is adopted to estimate the unknown parameters of the global LPV model. To avoid the problems of ill-conditioned matrices and high sensitivity of parameters to noise, the prior information on the coefficients of each local FIR model is employed to construct the prior probability of unknown parameters. Then the maximum a posteriori (MAP) estimates of the global model parameters are derived via the generalized EM algorithm. The numerical example is presented to demonstrate the effectiveness of the proposed method. © IFAC.

关键词： Parameter estimation

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Colour image segmentation using unsupervised clustering technique for acute leukemia images

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AIP Conference Proceedings 2015年第1期1660卷

作者： N. H. Abd Halim M. Y. Mashor A. S. Abdul Nasir N. Mustafa R. Hassan 1Electronic & Biomedical Intelligent Systems (EBItS) Research Group School of Mechatronics Engineering University Malaysia Perlis 02600 Kampus Pauh Putra Perlis Malaysia 2Department of Hematology School of Medical Science University Science Malaysia Kubang Kerian Kelantan Malaysia

Colour image segmentation has becoming more popular for computer vision due to its important process in most medical analysis tasks. This paper proposes comparison between different colour components of RGB(red, green, blue) and HSI (hue, saturation, intensity) colour models that will be used in order to segment the acute leukemia images. First, partial contrast stretching is applied on leukemia images to increase the visual aspect of the blast cells. Then, an unsupervised moving k-means clustering algorithm is applied on the various colour components of RGB and HSI colour models for the purpose of segmentation of blast cells from the red blood cells and background regions in leukemia image. Different colour components of RGB and HSI colour models have been analyzed in order to identify the colour component that can give the good segmentation performance. The segmented images are then processed using median filter and region growing technique to reduce noise and smooth the images. The results show that segmentation using saturation component of HSI colour model has proven to be the best in segmenting nucleus of the blast cells in acute leukemia image as compared to the other colour components of RGB and HSI colour models.

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Performance evaluation of the novel grasper for a robotic catheter navigation system

Performance evaluation of the novel grasper for a robotic ca...

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International Conference on Information and Automation (ICIA)

作者： Shuxiang Guo Jian Guo Lin Shao Peng Wang Yunliang Wang Intelligent Mechanical Systems Engineering Department Kagawa University Takamatsu Kagawa Japan Tianjin Key Laboratory for Control Theory & Application in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Tianjin China

This paper proposed a novel grasper for a novel master-slave robotic catheter navigation system in Vascular Interventional Surgery (VIS). The developed novel grasper can imitate the catheter grasping motion of the surgeon during VIS. The grasper is a key factor to drive the catheter into the vessel accurately. It adopts a common structure like the pliers, which can guarantee that the catheter can be clamped on the same axes with other via hole. The clamping force can be adjusted by the screw through changing the entered length of the screw to change the compression length of the spring. The clamping system consists of two graspers both master side and slave side respectively. The graspers clamp the catheter just like the surgeon's hand and the clamping method of the grasper imitates the surgeon's operation. The performance evaluation experiments of the novel grasper were done. The experimental results indicated that the grasper was effective to clamp catheter tightly to increase accuracy of surgery, which can satisfy the design demand.

关键词： Catheters Clamps Force Surgery Rubber Friction Robots

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Event-Triggered Reinforcement Learning Approach for Unknown Nonlinear Continuous-Time System

Event-Triggered Reinforcement Learning Approach for Unknown ...

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International Joint Conference on Neural Networks

作者： Xiangnan Zhong Zhen Ni Haibo He Xin Xu Dongbin Zhao Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston USA College of Mechatronics and Automation National University of Defense Technology Changsha China State Key Lab of Management and Control for Complex Systems Chinese Academy of Sciences Beijing P. R. China

This paper provides an adaptive event-triggered method using adaptive dynamic programming (ADP) for the nonlinear continuous-time system. Comparing to the traditional method with fixed sampling period, the event-triggered method samples the state only when an event is triggered and therefore the computational cost is reduced. We demonstrate the theoretical analysis on the stability of the event-triggered method, and integrate it with the ADP approach. The system dynamics are assumed unknown. The corresponding ADP algorithm is given and the neural network techniques are applied to implement this method. The simulation results verify the theoretical analysis and justify the efficiency of the proposed event-triggered technique using the ADP approach.

关键词： Equations Neural networks Stability analysis Performance analysis Approximation algorithms Approximation methods Heuristic algorithms

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Study of the plasticizer effect of single yeast cell by nanorobotic manipulation system

Study of the plasticizer effect of single yeast cell by nano...

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World Congress on Intelligent control and Automation (WCICA)

作者： Yajing Shen Masahiro Nakajima Jian Huang Toshio Fukuda Mechanical and Biomedical Engineering Department City University of Hong Kong China Dept. of Micro-Nano Systems Engineering Nagoya University Japan School of Automation Huazhong University of Science and Technology China Mechatronics Engineering Beijing Institute of Technology Beijing China

Plasticizer effect plays an important role in biological field, such as in the fruit ripe process. Humidity is a key factor to affect the plasticize. Previously, the stiffness of plant cells have been measured to study the plasticizer of the plant. However, these studies are based on group cell analysis and is not in vivo. In this paper, A nanoneedle was fabricated from AFM (atomic force microscopy) cantilever by FIB (focused ion beam) etching *** nanoneedle was fixed to a nanorobotic manipulator, which has three degrees of freedom, i.e. X, Y and Z translation. Single yeast cell was put on the sample stage inside an environmental scanning electron microscopy (ESEM). The environment relative humidity was set to three values, i.e. 100%, 70% and 40%. The stiffness of the single cell at these conditions were measured using the nanoneedle driven by the nanorobotic manipulation system.

关键词： Nanobioscience Humidity Force Etching Microscopy Educational institutions Temperature measurement

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