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2 edition of Robust subject recognition using the electrocardiogram found in the catalog.

Robust subject recognition using the electrocardiogram

Foteini Agrafioti

Robust subject recognition using the electrocardiogram

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  • 25 Currently reading

Published in 2008 .
Written in English


Edition Notes

Statementby Foteini Agrafioti.
The Physical Object
Paginationx, 125 leaves :
Number of Pages125
ID Numbers
Open LibraryOL20332899M

  Similar to the activity recognition dataset, we trained and tested random forests on the simulated dataset, using both record-wise and subject-wise methods, to predict whether a record came from a patient (β s = 1) or a healthy subject (β s = − 1). For record-wise, we randomly split the dataset into 50% training and 50% test, regardless of Cited by:   Biometrics: Theory, Methods, and Applications - Ebook written by N. V. Boulgouris, Konstantinos N. Plataniotis, Evangelia Micheli-Tzanakou. Read this book using Google Play Books app on your PC, android, iOS devices. Download for offline reading, highlight, bookmark or take notes while you read Biometrics: Theory, Methods, and Applications.


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Robust subject recognition using the electrocardiogram by Foteini Agrafioti Download PDF EPUB FB2

Abstract. In recent years, Biometric identification has taken a giant leap from objective security access system such as retina scan or a finger print scan to a continuous biometric identification based system and for that a single lead Electrocardiogram (ECG) signal is considered to be a good by: 1.

validity of using ECG for biometric recognition is supported by the fact that the physiological and geometrical di˜erences of the heart in di˜erent individuals display certain uniqueness in their ECG signals [].

The advantage of ECGs in biometric systems is their robust nature against the application of falsified credentials. Using the electrocardiogram biometric as a case study, it is shown that these methods offer the flexibility of designing security constraints in a statistical manner.

Experimental results for identification over PTB and MIT healthy ECG databases indicate a robust subject identification rate of % using only 2 heartbeats in average for each individual. View. Although the electrocardiogram (ECG) has been a reliable diagnostic tool for decades, its deployment in the context of biometrics is relatively recent.

Its robustness to falsification, the evidence it carries about aliveness and its rich feature space has rendered the deployment of ECG based biometrics an interesting prospect. The rich feature space contains Cited by: This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.

Show less Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May Generally, subject-independent emotion recognition is a challenging field due to the facts that (a) physiological expressions of emotion depend on age, gender, culture and other social factors, and (b) it also depends on the environment in which a subject lives, (c) the subject-independent nature of human emotion recognition which means that Cited by: 3.

Rattanyu K, Mizukawa M, Jacko J. Emotion Recognition Using Biological Signal in Intelligent Space. Human-Com Int. ; – Maaoui C, Pruski A. Book Emotion Recognition through Physiological Signals for Human-Machine Communication.

In Book Emotion Recognition through Physiological Signals for Human-Machine Communication. Cited by: This book details a wide range of challenges in the processes of acquisition, preprocessing, segmentation, mathematical modelling and pattern recognition in ECG signals, presenting practical and robust solutions based on digital signal processing techniques.

Identifying the emotional state is helpful in applications involving patients with autism and other intellectual disabilities; computer-based training, human computer interaction etc. Electrocardiogram (ECG) signals, being an activity of the autonomous nervous system (ANS), reflect the underlying true emotional state of a person.

However, the performance of various. In this paper, a new wavelet based framework is developed and evaluated for automatic analysis of single lead electrocardiogram (ECG) for application in human recognition.

The proposed system utilizes a robust preprocessing stage that enables it to handle noise and outliers so that it is directly applied on the raw ECG signal.

Moreover, it is capable of handling ECGs regardless. In this paper, we present the results of an analysis of the electrocardiogram (ECG) as a biometric using a novel short-time frequency method with robust feature selection.

Our proposed method incorporates heartbeats from multiple days and fuses information. Single lead ECG signals from a comparatively large sample of subjects that were sampled from the general population. Search Tips. Phrase Searching You can use double quotes to search for a series of words in a particular order.

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Phinyomark et al. [26,30] investigated the effect of sampling rate on EMG pattern recognition and then identified a novel set of features that are more accurate and robust for emerging low-sampling rate EMG systems, using four different EMG data sets containing 40 subject sessions with over separate by:   rd It is a pleasure and an honour both to organize ICBthe 3 IAPR/IEEE Inter- tional Conference on Biometrics.

This will be held 2&#;5 June in Alghero, Italy, hosted by the Computer Vision Laboratory, University of Sassari. The conference series is the premier forum for presenting Price: $ Biometrics is the technical term for body measurements and calculations. It refers to metrics related to human characteristics.

Biometrics authentication (or realistic authentication) is used in computer science as a form of identification and access control. It is also used to identify individuals in groups that are under surveillance.

robust likelihood ratio test using alpha-divergence: robust low rate speech coding based on cloned networks and wavenet: robust marine buoy placement for ship detection using dropout k-means: robust matrix completion via lp-greedy pursuits: robust multi-channel speech recognition using frequency aligned network: An issue of paramount importance in the development of a cost-effective face recognition (FR) system is the determination of low-dimensional, intrinsic face feature representation with enhanced discriminatory power.

It is well-known that the distribution of face images, under a perceivable variation in viewpoint, illumination or facial expression, is highly non convex and. Sohn M, Lee S, Kim D, Kim B and Kim H A comparison of 3D hand gesture recognition using dynamic time warping Proceedings of the 27th Conference on Image and Vision Computing New Zealand, () Kumar D and Ramakrishnan A Recognition of Kannada characters extracted from scene images Proceeding of the workshop on Document Analysis and.

peripheral resistance. In addition, the book demon-strates methods to extract diagnostic parameters for assessing cardiac function.

[.] Contents Electrocardiogram.- Analysis of Electrocardio-grams.- Modelling of Electrocardiogram Signals.- Vi-sualization of Cardiac Health using Electrocardio-grams.- Heart Rate Variability: a Review.- Data Fu. Subtle distortions on electrocardiogram (ECG) can help doctors to diagnose some serious larvaceous heart sickness on their patients.

However, it is difficult to find them manually because of disturbing factors such as baseline wander and high-frequency noise. In this chapter, we propose a method based on variational autoencoder to distinguish these distortions Author: Shaojie Chen, Zhaopeng Meng, Qing Zhao.

This book aims at promoting high-quality research by researchers and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security, and Computational Models ICC3 organized by PSG College of Technology, Coimbatore, India during December.

Time series classification is an important field in time series data-mining which have covered broad applications so far. Although it has attracted great interests during last decades, it remains a challenging task and falls short of efficiency due to the nature of its data: high dimensionality, large in data size and updating continuously.

With the advent of deep learning, new methods Cited by: 4. processes are fast and experimental results show that the approach is quite robust for preliminary normal ECG recognition.

Keywords: electrocardiogram, express-diagnostics, curvature scale-space, dynamic programming, dynamic time wrapping. ACM. Journal Papers. J Ali Akbari, Roozbeh Jafari, Personalizing Activity Recognition Models through Quantifying Different Types of Uncertainty using Wearable Sensors, IEEE Transaction on Biomedical Engineering (TBME), in press.

J Ayca Aygun, Hassan Ghasemzadeh, Roozbeh Jafari, Robust Interbeat Interval and Heart Rate Variability Estimation Method from Various.

Face recognition robust to head pose from one sample image. Shan, Ting, Lovell, Brian C. and Chen, Shaokang (). Face recognition robust to head pose from one sample image. In: Y. Tang, P. Wang, G. Lorette and D.S. Yeung, Proceedings of the 18th International Conference on Pattern Recognition.

Electrocardiogram is a slow signal to acquire, and it is prone to noise. It can be inconvenient to collect large number of ECG heartbeats in order to train a reliable biometric system; hence, this issue might result in a small sample size phenomenon which occurs when the number of samples is much smaller than the number of observations to model.

In this paper, Cited by: 5. In: Extended Kalman observer based Robust Control of one degree of freedom TRMS, 09/06/, International conference Hall. Eğer, Mehmet Taylan and Nayak, Gurudas C and Vaz, Aldrin () Liquid Level Detection using Ultrasonic Transducer.

In: Liquid Level Detection using Ultrasonic Transducer, 16/03/, Chennai. There are eight new chapters on the latest developments in life sciences using pattern recognition as well as two new chapters on pattern recognition in remote sensing. Sample Chapter(s) Chapter 1: A Unification of Component Analysismethods ( KB) Contents: Basic Methods in Pattern Recognition; Basic Methods in Computer Vision and Image.

The present invention is a biometric security system and method operable to authenticate one or more individuals using physiological signals. The method and system may comprise one of the following modes: instantaneous identity recognition (MR); or continuous identity recognition (CIR). The present invention may include a methodology and framework for biometric recognition Cited by: 2.

Full text of "Progress in pattern recognition, speech and image analysis [electronic resource]: 8th Iberoamerican Congress on Pattern Recognition, CIARPHavana, Cuba, Novemberproceedings" See other formats.

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Abstract. The present conference discusses the optical Gabor and wavelet transforms for image analysis, image segmentation via optical wavelets, semidifferential invariants, object labeling via convolution, tactile pattern recognition with complex linear morphology, a hybrid six-degree-of-freedom tracking system, and a hazard detection/avoidance sensor for NASA planetary landers.

cation techniques. Furthermore, these techniques are necessarily implemented using a knowledge of computational programming. This book follows the open-source philosophy that the development of robust signal processing algorithms is best done by making them freely available, together with the labeled data on which they were evaluated.

Electrocardiogram Feature Extraction and Pattern Recognition Using a Novel Windowing Algorithm. Muhammad Umer, Bilal Ahmed Bhatti, Muhammad Hammad Tariq, Muhammad Zia-ul-Hassan, Muhammad Yaqub Khan, Tahir Zaidi.

DOI: /abb 4, Downloads 5, Views Citations. As an important field of research in Human-Machine Interactions, emotion recognition based on physiological signals has become research hotspots.

Motivated by the outstanding performance of deep learning approaches in recognition tasks, we proposed a Multimodal Emotion Recognition Model that consists of a 3D convolutional neural network model, a 1D convolutional neural Author: Yuxuan Zhao, Xinyan Cao, Jinlong Lin, Dunshan Yu, Xixin Cao.

form robust face recognition, in order to improve machine recognition of human faces. This research is relevant to computer vision paradigm. A comprehensive references to the current state-of-the-art approaches to face processing can be found in [12]. Iris and retina Iris recognition systems scan the surface of the iris to com-pare patterns.

Get this from a library. Pattern recognition and machine intelligence: 5th international conference, PReMIKolkata, India, Decemberproceedings. [Pradipta Maji;] -- This book constitutes the refereed proceedings of the 5th International Conference on Pattern Recognition and Machine Intelligence, PReMIheld in Kolkata, India in December Edited by a panel of experts, this book fills a gap in the existing literature by comprehensively covering system, processing, and application aspects of biometrics, based on a wide variety of biometric traits.

The book provides an extensive survey of biometrics theory, methods,and applications, making it an indispensable source of information for researchers, security.

@article{osti_, title = {Wavelet transform analysis of transient signals: the seismogram and the electrocardiogram}, author = {Anant, K S}, abstractNote = {In this dissertation I quantitatively demonstrate how the wavelet transform can be an effective mathematical tool for the analysis of transient signals.

The two key signal processing applications of the wavelet transform, namely. () Robust Multilinear Tensor Rank Estimation Using Higher Order Singular Value Decomposition and Information Criteria.

IEEE Transactions on Signal Processing() Local Canonical Correlation Analysis for Nonlinear Common Variables by: () Color-based feature extraction with application to facial recognition using tensor-matrix and tensor-tensor analysis. Multimedia Tools and Applications() Tensor-Train decomposition for image by:   Writer recognition based on handwriting is important from security as well as judiciary point of view.

In this paper, based on static off-line data, we have proposed a novel writer recognition methodology using word level micro-features and .