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Proceedings of the 1997 ieee international conference on intelligent processing systems, ICIPS'97. Part 1 (of 2)

The proceedings contains 208 papers from the 1997 ieee international conference on intelligent processing systems. Topics discussed include: image information processing and management;expert systems;machine intelligence and applications;knowledge-based signal processing;robotics and applications;scheduling and planning;computer vision;diagnostic systems;decision support systems;computer databases;computer networks and applications;design and development systems;multimedia applications;virtual reality;natural language understanding and speech recognition systems;and software development.

关键词： Artificial intelligence

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An Efficient Method for Subcutaneous Veins Localization Using Near Infrared Imaging

An Efficient Method for Subcutaneous Veins Localization Usin...

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5th international conference on intelligent and Advanced systems (ICIAS)

作者： Shahzad, A. Saad, N. M. Walter, N. Malik, Aamir Saeed Meriaudeau, F. Univ Teknol PETRONAS Ctr Intelligent Signal & Imaging Res Perak Malaysia Univ Burgundy Le2i Le Creusot France

ISBN: (纸本)9781479946532

In the majority of the medical treatments, intravenous catheterization is the most important phase in which skilled medical practitioners locate the best vein and perform catheterization process for medication or blood sampling. Due to the different physiological characteristics, mainly darker skin tone, scars or dehydrated condition of patients, medical staff stumbles in localization of veins. This paper proposes an enhanced method which intends to overcome the difficulty faced by medical staff in veins localization for intravenous catheterization. Using the Near Infrared imaging and image processing algorithms a novel approach for veins visualization is proposed. In order to have complete insight of veins location in the subcutaneous layer of skin a method to estimate the depth of veins using Monte Carlo simulations is presented. The complete system will increase guidance towards medical practitioners to facilitate the insertion of catheter or syringe into the veins.

关键词： Intravenous catheterization multispectral NIR PCA

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Proceedings of 2003 ieee/RSJ international conference on intelligent Robots and systems (IROS 2003) Volume 2

Proceedings of 2003 IEEE/RSJ International Conference on Int...

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2003 ieee/RSJ international conference on intelligent Robots and systems

The proceedings contains 166 papers from the 2003 ieee/RSJ international conference on intelligent Robots and systems (IROS 2003) Volume 2. The topics discussed include: an active artificial whisker array for texture discrimination;a signal separation technique which can be applied to the ears of robots;task driven dynamic QoS based bandwidth allocation for real-time teleoperation via the internet;multi-objective optimal robot path planning in manufacturing;approaches for heuristically biasing RRT growth;active learning of a mobile robot based on percieving-acting cycle;and spiking neural building block robot with Hebbian learning.

关键词： intelligent robots

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Recognition of Grasp Types through Principal Components of DWT based EMG Features

Recognition of Grasp Types through Principal Components of D...

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ieee international conference on Rehabilitation robotics (ICORR)/international Neurorehabilitation Symposium (INRS)/international conference on Virtual Rehabilitation (ICVR)

作者： Kakoty, Nayan M. Hazarika, Shyamanta M. Tezpur Univ Sch Engn Tezpur India

ISBN: (纸本)9781424498628

With the advancement in machine learning and signal processing techniques, electromyogram (EMG) signals have increasingly gained importance in man-machine interaction. Multifingered hand prostheses using surface EMG for control has appeared in the market. However, EMG based control is still rudimentary, being limited to a few hand postures based on higher number of EMG channels. Moreover, control is non-intuitive, in the sense that the user is required to learn to associate muscle remnants actions to unrelated posture of the prosthesis. Herein lies the promise of a low channel EMG based grasp classification architecture for development of an embedded intelligent prosthetic controller. This paper reports classification of six grasp types used during 70% of daily living activities based on two channel forearm EMG. A feature vector through principal component analysis of discrete wavelet transform coefficients based features of the EMG signal is derived. Classification is through radial basis function kernel based support vector machine following preprocessing and maximum voluntary contraction normalization of EMG signals. 10-fold cross validation is done. We have achieved an average recognition rate of 97.5%.

关键词： Electrodes Electromyography Feature extraction Grasping Kernel Muscles Support vector machines discrete wavelet transform discrete wavelet transforms electromyogram electromyography grasp type recognition intelligent control intelligent prosthetic controller learning (artificial intelligence) machine learning man-machine interaction medical control systems multifingered hand prosthesis muscle remnant action principal component analysis principal component analysis prosthetics signal processing surface EMG

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Media processing ecologies

Media processing ecologies

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international conference on Information Technology

作者： Bove, VM MIT Media Lab Cambridge MA 02139 USA

ISBN: (纸本)0780377249

Research in the MIT Media Laboratory's Object-Based Media Group is looking to solve multimedia signal processing problems through the creation of ecosystems of intelligent devices that organize themselves to distribute information and to divide large tasks. I examine the technological trends that make this approach possible and desirable, and briefly introduce three example systems.

关键词： multimedia signal processing parallel multimedia processing self-organizing systems peer-to-peer

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Active Sensing for Range-Only Mapping using Multiple Hypothesis

Active Sensing for Range-Only Mapping using Multiple Hypothe...

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ieee/RSJ international conference on intelligent Robots and systems

作者： Merino, L. Caballero, F. Ollero, A. Pablo de Olavide Univ Carretera Utrera Km1 Seville 41013 Spain

ISBN: (纸本)9781424466757

Radio signal-based localization and mapping is becoming more interesting in robotics as applications involving the collaboration between robots and static wireless devices are more common. This paper describes a method for mapping with a mobile robot the position of a set of nodes using radio signal measurements. The method employs Gaussian Mixtures Models (GMM) for undelayed initialization of the position of the wireless nodes within a Kalman filter. Moreover, the paper extends the method to consider active sensing strategies in order to map the nodes. Entropy variation is used as a measurement of information gain, and allows to prioritize control actions of the robot. However, as there is no analytical expression for the entropy of a GMM, upper bounds of the entropy, for which close form computation is possible, are used instead. The paper describes simulations that show the feasibility of the approach.

关键词： Gaussian mixture model Gaussian processes Kalman filter Kalman filters active sensing active sensing strategy entropy entropy variation information gain mapping mobile robot mobile robots radio signal based localization radio signal measurement range only mapping robotic signal processing static wireless device wireless sensor networks

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Tactile identification of objects using Bayesian exploration

Tactile identification of objects using Bayesian exploration

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ieee international conference on robotics and Automation (ICRA)

作者： Xu, Danfei Loeb, Gerald E. Fishel, Jeremy A. SynTouch LLC Los Angeles CA 90007 USA

ISBN: (纸本)9781467356411;9781467356435

In order to endow robots with human-like tactile sensory abilities, they must be provided with tactile sensors and intelligent algorithms to select and control useful exploratory movements and interpret data from all available sensors. Current robotic systems do not possess such sensors or algorithms. In this study we integrate multimodal tactile sensing (force, vibration and temperature) from the BioTac (R) with a Shadow Dexterous Hand and program the robot to make exploratory movements similar to those humans make when identifying objects by their compliance, texture, and thermal properties. signal processing strategies were developed to provide measures of these perceptual properties. When identifying an object, exploratory movements are intelligently selected using a process we have previously developed called Bayesian exploration [1], whereby exploratory movements that provide the most disambiguation between likely candidates of objects are automatically selected. The exploration algorithm was augmented with reinforcement learning whereby its internal representations of objects evolved according to its cumulative experience with them. This allowed the algorithm to compensate for drift in the performance of the anthropomorphic robot hand and the ambient conditions of testing, improving accuracy while reducing the number of exploratory movements required to identify an object. The robot correctly identified 10 different objects on 99 out of 100 presentations.

关键词： Bayes methods dexterous manipulators force sensors haptic interfaces intelligent robots learning (artificial intelligence) robot programming signal processing tactile sensors temperature sensors thermal conductivity vibrations

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A Novel Approach to Neural Network Based intelligent systems for Emotion Recognition in Audio signals 18

A Novel Approach to Neural Network Based Intelligent Systems...

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ieee 18th international conference on Information Reuse and Integration (IRI)

作者： Mooman, Abdelniser Powers, Stephen Bluecorss Blueshield Excellus Rochester NY 14647 USA Univ Waterloo Fac Math Waterloo ON Canada Rochester Inst Technol 1 Lomb Mem Dr Rochester NY 14623 USA

ISBN: (纸本)9781538615621

In this work, we present research done in the field of affective computing and intelligent systems which could benefit countless other fields including medicine, game development, and robotics. We attempted to develop an intelligent system capable of recognizing seven basic human emotions when given nothing but a raw audio signal. This task was accomplished through creating a two-tier intelligent system comprised of neural networks designed to determine the emotion of a 40 millisecond audio signal and a simple voting algorithm used to combine the output of the neural networks. Overall, we were able to achieve 60% accuracy of classifying 7 different emotions in a semi-open loop test with the system's primary guess, and 80% accuracy with the addition of the secondary guess. The results we obtained prove the potential of using this unique system design in the field of affective computing and hint that greater accuracy could be achieved through the combination of multiple intelligent systems.

关键词： Affective Computing Neural Networks Emotion Recognition Digital signal processing

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Correlation techniques for digital time-of-flight measurement by airborne ultrasonic rangefinders

Correlation techniques for digital time-of-flight measuremen...

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Proceedings of the ieee/RSJ/GI international conference on intelligent Robots and systems. Part 3 (of 3)

作者： Sabatini, Angelo M. Spinielli, Enrico ARTS Lab Pisa Italy

A simple pulse-echo ranging system whose receiver signal processing is completely digital is described in this paper: the use of appropriate sampling techniques and signal processing algorithms allow one to benefit from the advantages of correlation-based detection methods for accurate ranging of multiple objects, without compromising the most prominent features of pulse-echo sonar systems, namely their relatively low cost and simplicity of operation. The experimental results presented concern the use of relatively high-frequency ultrasonic transducers.

关键词： Digital signal processing

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Probabilistic instantaneous model-based signal processing applied to localization and tracking

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robotics AND AUTONOMOUS systems 2009年第3期57卷 249-258页

作者： Beutler, Frederik Huber, Marco F. Hanebeck, Uwe D. Univ Karlsruhe TH Inst Comp Sci & Engn Intelligent Sensor Actuator Syst Lab D-76128 Karlsruhe Germany

In this paper, a probabilistic approach for estimating time and space-variant parameters of a system, based on sequentially received discrete-time signal values, is presented. The system description is the solution of a linear partial differential equation (PDE). The PDE describes for example the wave propagation of an acoustic wave in a localization system. The solution of the PDE is given by a time-variant and space-variant impulse response. This impulse response is characterized by the time and space-variant parameters in order to track an object, which emits for example an acoustic signal. For estimating the position of the object in an instantaneous way a Bayesian approach has to be used, which considers the dynamic behavior of the parameters in a system model and uncertainties in a stochastic manner by means of probability density functions. Hence, the new approach provides a probabilistic instantaneous model-based signal processing, where the sequentially measured signal values are processed directly and known reference signal sequences are interpreted as part of a time-variant nonlinear measurement equation. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Model-based signal processing Bayesian estimator Localization Tracking

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