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Computers in Cardiology (CinC)

作者： M.G. Tsipouras Y. Goletsis D.I. Fotiadis Unit of Medical Technology and Intelligent Information Systems Department of Computer Science University of Ioannina (UoI) Ioannina Greece Biomedical Research Institute-FORTH Ioannina Greece

A method for arrhythmic episode classification using only the RR-interval signal is presented. The method is based on fuzzy logic and Markov models, while classification is performed for nine categories of cardiac rhythms. A two-stage classifier is applied. In the first stage, a fuzzy system classifies the episode using the mean value and standard deviation of the RR-intervals. In the second, the RR-interval signal is transformed to character sequences, which are classified by Markov models. Two representation techniques are used for the extraction of the character sequences: symbolic dynamics and one based on the RR-interval length. The classification of an episode is achieved combining the outcomes of the two stages. The MIT-BIH arrhythmia database is used for the evaluation of the proposed method. The obtained results indicate high performance (accuracy 73%) in arrhythmic episode classification.

关键词： Electrocardiography Fuzzy logic Rhythm Databases Cardiology Testing intelligent systems information systems Computer science Signal processing

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A framework for remote execution of whole body motions for humanoid robots

A framework for remote execution of whole body motions for h...

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IEEE-RAS International Conference on Humanoid Robots

作者： Neo Ee Sian K. Yokoi S. Kajita K. Tanie Cooperative Graduate School of Systems and Information Engineering University of Tsukuba Tsukuba Japan JRL Intelligent Systems Institute Tsukuba Japan HRG ISI Tsukuba Japan Evaluation Department National Institute for Advanced Industrial Science and Technology Tsukuba Japan

This paper introduces a framework for the remote execution of whole body motions for humanoid robots. Humanoid robots are biped machines which usually possess more than 20 degrees of freedom(D0F). The complexity of their multi-DOF structure and the difficulty in maintaining postural stability make the whole body operation of humanoid robots fundamentally different from traditional fixed-base manipulators or stable-base mobile manipulators. Getting hints from human conscious and subconscious motion generations, we propose a method of generating whole body motions which integrates operator’s command input and the robot’s autonomous functions. Instead of giving commands to all joints all the time, the operator selects only the necessary points of the humanoid robot’s body for manipulation. This paper first explains the concept of the system and the framework for integrating operator’s command and autonomous functions in whole body motion generation. Using the framework, we constructed autonomous functions for maintaining stability constraint while satisfying the desired trajectory of operation points and a workspace extension autonomy which changes utilization of body parts. Finally the paper reports on the implementation of the proposed method to teleoperate a 30 DOF humanoid robot HRP-2 using only two 3 DOF joysticks. Experiments teleoperating HRP-2 confirmed the effectiveness of the proposed method.

关键词： Humanoid robots Humans Stability Manipulators Mobile robots systems engineering and theory intelligent systems intelligent robots Intersymbol interference Telephony

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Autonomous navigation using neural networks

Autonomous navigation using neural networks

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International Conference on Machine Learning and Applications (ICMLA)

作者： J.R. Deming M.A.A. de Oliveira New Mexico Institute of Mining and Technology Intelligent Systems and Robotics Center Socorro NM USA Escole de Engenharia Elétrica Universidade Federal de Goiás Goiania Goias Brazil

Semi-autonomous to fully autonomous robots rely on some form of data collection to operate in their environment. This has traditionally been accomplished using sonar or infra-red sensors to measure the robot's proximity to nearby objects. These sensors provide information to the robot so that the software controlling the robot can exhibit some degree of autonomy. These systems commonly use deterministic algorithms that employ rules that attempt to cover any eventuality. This paper discusses an alternative method to this rule based approach. A feed forward neural network was trained to exhibit the same behaviors as a simple rule based algorithm as a first step to a more sophisticated approach that will be able to draw up more complex rule sets, human teaching , and run-time learning that allows the robot to build on past experiences.

关键词： Navigation Neural networks Robot sensing systems intelligent robots intelligent sensors Humans Education Testing intelligent systems intelligent networks

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Application of rough set based dynamic parameter optimization to MRI segmentation

Application of rough set based dynamic parameter optimizatio...

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Conference of the North American Fuzzy information Processing Society - NAFIPS

作者： S. Widz D. Slezak K. Revett Department of Robotics and Multi-Agent Systems Polish-Japanese Institute of Information Technology Warsaw Poland Department of Computer Science University of Regina Regina Canada Department of Computer Science University of Luton Luton UK

We introduce a multi-spectral MRI segmentation technique based on approximate reducts derived from the data mining paradigm of the theory of rough sets. We use genetic algorithms to tune the parameterized attributes a... 详细信息

关键词： Magnetic resonance imaging Image segmentation Genetic algorithms Brain Histograms Computer science Rough sets Alzheimer's disease Parkinson's disease Testing

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Classification of atrial tachyarrhythmias in electrocardiograms using time frequency analysis

Classification of atrial tachyarrhythmias in electrocardiogr...

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Computers in Cardiology (CinC)

作者： M.G. Tsipouras V.P. Oikonomou Di Fotiadis L.K. Michalis D. Sideris Unit of Medical Technology and Intelligent Information Systems Department of Computer Science University of Ioannina (UoI) Ioannina Greece Biomedical Research Institute-FORTH Ioannina Greece Division of Cardiology Medical School Ioannina Greece

In this work a novel automated method, combining time-frequency analysis and expert's knowledge, for the classification of atrial tachyarrhythmias is presented. It is based on the analysis of small ECG segments and their classification into three categories of cardiac rhythm: (a) atrial fibrillation, (b) atrial flutter and (c) normal sinus rhythms. Time-frequency analysis is used to calculate the power spectrum density for each segment. Several spectral characteristics are extracted from the power spectrum density, representing the energy distribution on the time-frequency plane. These characteristics are used as input in an artificial neural network, which classifies each ECG segment into one of the three categories. The method is validated using the MIT-BIH arrhythmia database and the obtained average sensitivity and specificity are 93.4% and 96.5%, respectively.

关键词： Time frequency analysis Electrocardiography Rhythm Databases Atrial fibrillation Cardiology Artificial neural networks Medical diagnostic imaging Feature extraction Heart

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Command and control of autonomous mobile vehicle robots using mobile phone and computer via internet

Command and control of autonomous mobile vehicle robots usin...

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AUVSI's Unmanned systems North America 2004 - Proceedings

作者： Sugisaka, Masanori Akizuki, Kageo Albus, James S. Finkelstein, Robert Department of Electrical and Electronic Engineering Oita Univesity 700 Oaza Dannoharu Oita 870-1192 Japan at Nagoya Moriyamak-ku Nagoya 463-0003 Japan Graduate School of Information Production and Systems Waseda University 2-7 Hibikino Kitakyushu Fukuoka 808-0135 Japan Intelligent Systems Division National Institute of Standard and Technology Stop 8230 100 Bureau Drive Gaithersburg MD 20899-8230 United States Robotic Technology Inc. 11424 Palatine Drive Potomac MD 20854-1451 United States

This paper describes the techniques for command and control of autonomous mobile vehicle robots using a mobile phone and a mobile computer via Internet. The autonomous unmanned ground vehicle robot(UGV) developed at Artificial Life and robotics Laboratory of The University of Oita is called "Tarou". We show the techniques for Tarou to perform the tasks as follows;(1) an efficient sensor fusion from many sensors(vision, audio, geographic, etc.), (2) synthesizing and understanding the data including on-line image obtained from sensors installed with Tarou, (3) formulate the next course of action. The techniques developed enable Tarou to obtain the powerful ability for autonomous sensing and dynamic mobility for locomotion and navigation. The experiments for sending command and control to Tarou's tasks were performed successfully by the public Internet. The techniques developed could dramatically increase the performance of the autonomous unmanned ground vehicle robots for a future robotic defense system need.

关键词： Remotely operated vehicles

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Estimating fuzzy membership functions parameters by the Levenberg-Marquardt algorithm

Estimating fuzzy membership functions parameters by the Leve...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： J. Botzheim C. Cabrita L.T. Koczy A.E. Ruano Department of Telecommunication and Media informatics Budapest University슠of슠Technology슠and슠Economics Hungary Centre for Intelligent Systems University of Algarve Portugal Institute of Information Technology and Electrical Engineering Széchenyi István University Gyor Hungary

In previous papers from the authors fuzzy model identification methods were discussed. The bacterial algorithm for extracting fuzzy rule base from a training set was presented. The Levenberg-Marquardt algorithm was also proposed for determining membership functions in fuzzy systems. In this paper the Levenberg-Marquardt technique is improved to optimise the membership functions in the fuzzy rules without Ruspini-partition. The class of membership functions investigated is the trapezoidal one as it is general enough and widely used. The method can be easily extended to arbitrary piecewise linear functions as well.

关键词： Fuzzy systems Fuzzy sets Neural networks intelligent systems Informatics Data mining Input variables information technology Microorganisms Piecewise linear techniques

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Motion-Based Template Matching for Obstacle Detection

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Journal of Advanced Computational Intelligence and intelligent Informatics 2004年第5期8卷 469-476页

作者： Kawamoto, Kazuhiko Ohnishi, Naoya Imiya, Atsushi Klette, Reinhard Hirota, Kaoru Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Mail-Box G3-49 4259 Nagatsuta Midori-ku Yokohama226-8502 Japan Institute of Media and Information Technology Chiba University 1-33 Yayoi-cho Inage-ku Chiba263-8522 Japan Software Research Division National Institute of Informatics 2-1-2 Hitotsubashi Chiyoda-ku Tokyo101-8430 Japan Centre for Image Technology and Robotics University of Auckland Tamaki Campus Building 731 Auckland New Zealand

A matching algorithm that evaluates the difference between model and calculated flows for obstacle detection in video sequences is presented. A stabilization method for obstacle detection by median filtering to overcome instability in the computation of optical flow is also presented. Since optical flow is a scene-independent measurement, the proposed algorithm can be applied to various situations, whereas most of existing color- and texture-based algorithms depend on specific scenes, such as roadway and indoor scenes. An experiment is conducted with three real image sequences, in which a static box or a moving toy car appears, to evaluate the performance in terms of accuracy under varying thresholds using a receiver operating characteristic (ROC) curve. For the three image sequences, the ROC curves show, in the best case, that the false positive fraction and the true positive fraction is 19.0% and 79.6%, 11.4% and 84.5%, 19.0% and 85.4%, respectively. The processing time per frame is 19.38msec. on 2.0GHz Pentium 4, which is less than the video-frame rate. © Fuji technology Press Ltd.

关键词： Optical flows

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Design of B-spline neural networks using a bacterial programming approach

Design of B-spline neural networks using a bacterial program...

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International Joint Conference on Neural Networks (IJCNN)

作者： C. Cabrita J. Botzheim A.E. Ruano L.T. Koczy Centre for Intelligent Systems University of Algarve Algarve Portugal Department of Telecommunication and Media Informatics Budapest University슠of슠Technology슠and슠Economics Hungary Institute of Information Technology and Electrical Engineering Széchenyi István University Gyor Hungary Department of Telecommunication and Media informatics Budapest University슠of슠Technology슠and슠Economics Hungary

The design phase of B-spline neural networks represents a very high computational task. For this purpose, heuristics have been developed, but have been shown to be dependent on the initial conditions employed. In This work a new technique, bacterial programming, is proposed, whose principles are based on the replication of the microbial evolution phenomenon. The performance of this approach is illustrated and compared with existing alternatives.

关键词： Spline Neural networks Microorganisms Genetic programming Telecommunication network topology Evolution (biology) Evolutionary computation intelligent systems intelligent networks Informatics

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Project Scheduling Using Hybrid Genetic Algorithm with Fuzzy Logic Controller in SCM Environment

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Tsinghua Science and technology 2003年第1期8卷 19-29页

作者： Mitsuo Gen KwanWoo Kim Genji Yamazaki Graduate School of Information Production & Systems Waseda UniversityDepartment of Intelligent Systems Tokyo Metropolitan Institute of TechnologyDepartment of Intelligent Systems Tokyo Metropolitan Institute of Technology Kitakyushu 808-0135 Japan Hino-city Tokyo 190-0065 Japan Hino-city Tokyo 190-0065 Japan

In supply chain management (SCM) environment, we consider a resource-constrained project scheduling problem (rcPSP) model as one of advanced scheduling problems considered by a constraint programming technique. We develop a hybrid genetic algorithm (hGA) with a fuzzy logic controller (FLC) to solve the rcPSP which is the well known NP-hard problem. This new approach is based on the design of genetic operators with FLC through initializing the serial method which is superior for a large rcPSP scale. For solving these rcPSP problems, we first demonstrate that our hGA with FLC (flc-hGA) yields better results than several heuristic procedures presented in the literature. We have revealed a fact that flc-hGA has the evolutionary behaviors of average fitness better than hGA without FLC.

关键词： resource-constrained project scheduling problem (rcPSP) priority rule method (PRM) hybrid genetic algorithm (hGA) fuzzy logic controller (FLC)

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