35-11 : Traitement des biosignaux

35-01 Génie biomédical général
35-02 Instrumentation biomédicale
35-03 Traitement d'images médicales
35-04 Modélisation des systèmes physiologiques
35-05 Biophysique
35-06 Biomatériaux
35-07 Biomécanique
35-08 Génie de la réhabilitation
35-09 Informatique biomédicale
35-10 Capteurs et mesures biomédicaux

Ouvrages de la bibliothèque en indexation 35-11

Biomedical signals based computer-aided diagnosis for neurological disorders / M. Murugappan

Public ISBD Titre : Biomedical signals based computer-aided diagnosis for neurological disorders Type de document : texte imprimé Auteurs : M. Murugappan, Auteur ; Rajamanickam Yuvaraj, Auteur Editeur : Netherlands : Springer Année de publication : 2022 Importance : 289 p. Présentation : couv. ill. en en coul Format : 24 cm. ISBN/ISSN/EAN : 978-3-03-097844-0 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders. Note de contenu : Contents Abnormal EEG Detection Using Time-Frequency Images and Convolutional Neural Network Physical Action Categorization Pertaining to Certain Neurological Disorders Using Machine Learning-Based Signal Analysis A Comparative Study on EEG Features for Neonatal Seizure Detection Hilbert Huang Transform (HHT) Analysis of Heart Rate Variability (HRV) in Recognition of Emotion in Children with Autism Spectrum Disorder (ASD) Detection of Tonic-Clonic Seizures Using Scalp EEG of Spectral Moments Investigation of the Brain Activation Pattern of Stroke Patients and Healthy Individuals During Happiness and Sadness A Novel Parametric Nonstationary Signal Model for EEG Signals and Its Application in Epileptic Seizure Detection Biomedical Signal Analysis Using Entropy Measures: A Case Study of Motor Imaginary BCI in End Users with Disability Automatic Detection of Epilepsy Using CNN-GRU Hybrid Model Catalogic Systematic Literature Review of Hardware-Accelerated Neurodiagnostic Systems Wearable Real-Time Epileptic Seizure Detection and Warning System Analysis of Intramuscular Coherence of Lower Limb Muscle Activities Usin Magnitude Squared Coherence -Index Biomedical signals based computer-aided diagnosis for neurological disorders [texte imprimé] / M. Murugappan, Auteur ; Rajamanickam Yuvaraj, Auteur . - Netherlands : Springer, 2022 . - 289 p. : couv. ill. en en coul ; 24 cm. ISBN : 978-3-03-097844-0 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Biomedical signals provide unprecedented insight into abnormal or anomalous neurological conditions. The computer-aided diagnosis (CAD) system plays a key role in detecting neurological abnormalities and improving diagnosis and treatment consistency in medicine. This book covers different aspects of biomedical signals-based systems used in the automatic detection/identification of neurological disorders. Several biomedical signals are introduced and analyzed, including electroencephalogram (EEG), electrocardiogram (ECG), heart rate (HR), magnetoencephalogram (MEG), and electromyogram (EMG). It explains the role of the CAD system in processing biomedical signals and the application to neurological disorder diagnosis. The book provides the basics of biomedical signal processing, optimization methods, and machine learning/deep learning techniques used in designing CAD systems for neurological disorders. Note de contenu : Contents Abnormal EEG Detection Using Time-Frequency Images and Convolutional Neural Network Physical Action Categorization Pertaining to Certain Neurological Disorders Using Machine Learning-Based Signal Analysis A Comparative Study on EEG Features for Neonatal Seizure Detection Hilbert Huang Transform (HHT) Analysis of Heart Rate Variability (HRV) in Recognition of Emotion in Children with Autism Spectrum Disorder (ASD) Detection of Tonic-Clonic Seizures Using Scalp EEG of Spectral Moments Investigation of the Brain Activation Pattern of Stroke Patients and Healthy Individuals During Happiness and Sadness A Novel Parametric Nonstationary Signal Model for EEG Signals and Its Application in Epileptic Seizure Detection Biomedical Signal Analysis Using Entropy Measures: A Case Study of Motor Imaginary BCI in End Users with Disability Automatic Detection of Epilepsy Using CNN-GRU Hybrid Model Catalogic Systematic Literature Review of Hardware-Accelerated Neurodiagnostic Systems Wearable Real-Time Epileptic Seizure Detection and Warning System Analysis of Intramuscular Coherence of Lower Limb Muscle Activities Usin Magnitude Squared Coherence -Index

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
4083	35-11-07	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	4083

Biosignal and Medical Image Processing / John L. Semmlow

Public ISBD Titre : Biosignal and Medical Image Processing Type de document : texte imprimé Auteurs : John L. Semmlow, Auteur Mention d'édition : 1st.+2nd. ed. Editeur : Boca Raton; London; New York : CRC Press/Taylor & Françis Group Année de publication : 2004+2009 Importance : 450 p. Présentation : couv. ill. en coul., ill. Format : 25,9 cm. Accompagnement : 1 st. ed. CDROM ISBN/ISSN/EAN : 978-1-420-06230-4 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Just as a cardiologist can benefit from an oscilloscope-type display of the ECG without a deep understanding of electronics, an engineer can benefit from advanced signal processing tools without always understanding the details of the underlying mathematics. Through the use of extensive MATLAB® examples and problems, Biosignal and Medical Image Processing, Second Edition provides readers with the necessary knowledge to successfully evaluate and apply a wide range of signal and image processing tools. The book begins with an extensive introductory section and a review of basic concepts before delving into more complex areas. Topics discussed include classical spectral analysis, basic digital filtering, advanced spectral methods, spectral analysis for time-variant spectrums, continuous and discrete wavelets, optimal and adaptive filters, and principal and independent component analysis. In addition, image processing is discussed in several chapters with examples taken from medical imaging. Finally, new to this second edition are two chapters on classification that review linear discriminators, support vector machines, cluster techniques, and adaptive neural nets. Comprehensive yet easy to understand, this revised edition of a popular volume seamlessly blends theory with practical application. Most of the concepts are presented first by providing a general understanding, and second by describing how the tools can be implemented using the MATLAB software package. Through the concise explanations presented in this volume, readers gain an understanding of signal and image processing that enables them to apply advanced techniques to applications without the need for a complex understanding of the underlying mathematics. Note de contenu : TABLE OF CONTENTS chapter 1 Introduction chapter 2 Basic Concepts chapter 3 Spectral Analysis: Classical Methods chapter 4 Digital Filters chapter 5 Spectral Analysis: Modern Techniques chapter 6 Time-Frequency Methods chapter 7 The Wavelet Transform chapter 8 Advanced Signal Processing Techniques: Optimal and Adaptive Filters chapter 9 Multivariate Analyses: Principal Component Analysis and Independent Component Analysis chapter 10 Fundamentals of Image Processing: MATLAB Image Processing Toolbox chapter 11 Image Processing: Filters, Transformations, and Registration chapter 12 Image Segmentation chapter 13 Image Reconstruction chapter 14 Classification I: linear discriminant analysis and support vector machines chapter 15 Adaptive neural nets -Index Biosignal and Medical Image Processing [texte imprimé] / John L. Semmlow, Auteur  . -  1st.+2nd. ed. . - Boca Raton; London; New York : CRC Press/Taylor & Françis Group, 2004+2009 . - 450 p. : couv. ill. en coul., ill. ; 25,9 cm. + 1 st. ed. CDROM. ISBN : 978-1-420-06230-4 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Just as a cardiologist can benefit from an oscilloscope-type display of the ECG without a deep understanding of electronics, an engineer can benefit from advanced signal processing tools without always understanding the details of the underlying mathematics. Through the use of extensive MATLAB® examples and problems, Biosignal and Medical Image Processing, Second Edition provides readers with the necessary knowledge to successfully evaluate and apply a wide range of signal and image processing tools. The book begins with an extensive introductory section and a review of basic concepts before delving into more complex areas. Topics discussed include classical spectral analysis, basic digital filtering, advanced spectral methods, spectral analysis for time-variant spectrums, continuous and discrete wavelets, optimal and adaptive filters, and principal and independent component analysis. In addition, image processing is discussed in several chapters with examples taken from medical imaging. Finally, new to this second edition are two chapters on classification that review linear discriminators, support vector machines, cluster techniques, and adaptive neural nets. Comprehensive yet easy to understand, this revised edition of a popular volume seamlessly blends theory with practical application. Most of the concepts are presented first by providing a general understanding, and second by describing how the tools can be implemented using the MATLAB software package. Through the concise explanations presented in this volume, readers gain an understanding of signal and image processing that enables them to apply advanced techniques to applications without the need for a complex understanding of the underlying mathematics. Note de contenu : TABLE OF CONTENTS chapter 1 Introduction chapter 2 Basic Concepts chapter 3 Spectral Analysis: Classical Methods chapter 4 Digital Filters chapter 5 Spectral Analysis: Modern Techniques chapter 6 Time-Frequency Methods chapter 7 The Wavelet Transform chapter 8 Advanced Signal Processing Techniques: Optimal and Adaptive Filters chapter 9 Multivariate Analyses: Principal Component Analysis and Independent Component Analysis chapter 10 Fundamentals of Image Processing: MATLAB Image Processing Toolbox chapter 11 Image Processing: Filters, Transformations, and Registration chapter 12 Image Segmentation chapter 13 Image Reconstruction chapter 14 Classification I: linear discriminant analysis and support vector machines chapter 15 Adaptive neural nets -Index

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
1998	35-11-05	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	1998
1999	35-11-05	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	1999
941	35-11-05	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	941

EEG Signal Processing / Saeid Sanei

Public ISBD Titre : EEG Signal Processing Type de document : texte imprimé Auteurs : Saeid Sanei, Auteur ; J.A. Chambers, Auteur Editeur : The Atrium, Southern Gate, Chichester : John Wiley & Sons Année de publication : 2007 Importance : 289 p. Présentation : couv. ill. en coul., ill. Format : 25,2 cm. ISBN/ISSN/EAN : 978-0-470-02581-9 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference. Note de contenu : Contents 1 Introduction to EEG 1.1 History 1.2 Neural Activities 1.3 Action Potentials 1.4 EEG Generation 1.5 Brain Rhythms 1.6 EEG Recording and Measurement 1.7 Abnormal EEG Patterns 1.8 Ageing 1.9 Mental Disorders 1.10 Summary and Conclusions References 2 Fundamentals of EEG Signal Processing 2.1 EEG Signal Modelling 2.2 Nonlinearity of the Medium 2.3 Nonstationarity 2.4 Signal Segmentation 2.5 Signal Transforms and Joint Time–Frequency Analysis 2.6 Coherency, Multivariate Autoregressive (MVAR) Modelling, and Directed Transfer Function (DTF) 2.7 Chaos and Dynamical Analysis 2.8 Filtering and Denoising 2.9 Principal Component Analysis 2.10 Independent Component Analysis 2.11 Application of Constrained BSS: Example 2.12 Signal Parameter Estimation 2.13 Classification Algorithms 2.14 Matching Pursuits 2.15 Summary and Conclusions References 3 Event-Related Potentials 3.1 Detection, Separation, Localization, and Classification of P300 Signals 3.2 Brain Activity Assessment Using ERP 3.3 Application of P300 to BCI 3.4 Summary and Conclusions References 4 Seizure Signal Analysis 4.1 Seizure Detection 4.2 Chaotic Behaviour of EEG Sources 4.3 Predictability of Seizure from the EEGs\ 4.4 Fusion of EEG–fMRI Data for Seizure Prediction 4.5 Summary and Conclusions References 5 EEG Source Localization 5.1 Introduction 5.2 Overview of the Traditional Approaches 5.3 Determination of the Number of Sources 5.4 Summary and Conclusions References 6 Sleep EEG 6.1 Stages of Sleep 6.2 The Influence of Circadian Rhythms 6.3 Sleep Deprivation 6.4 Psychological Effects 6.5 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis 6.6 Concluding Remarks References 7 Brain–Computer Interfacing 7.1 State of the Art in BCI 7.2 Major Problems in BCI 7.3 Multidimensional EEG Decomposition 7.4 Detection and Separation of ERP Signals 7.5 Source Localization and Tracking of the Moving Sources within the Brain 7.6 Multivariant Autoregressive (MVAR) Modelling and Coherency Maps 7.7 Estimation of Cortical Connectivity 7.8 Summary and Conclusions References Index EEG Signal Processing [texte imprimé] / Saeid Sanei, Auteur ; J.A. Chambers, Auteur . - The Atrium, Southern Gate, Chichester : John Wiley & Sons, 2007 . - 289 p. : couv. ill. en coul., ill. ; 25,2 cm. ISBN : 978-0-470-02581-9 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Electroencephalograms (EEGs) are becoming increasingly important measurements of brain activity and they have great potential for the diagnosis and treatment of mental and brain diseases and abnormalities. With appropriate interpretation methods they are emerging as a key methodology to satisfy the increasing global demand for more affordable and effective clinical and healthcare services. Developing and understanding advanced signal processing techniques for the analysis of EEG signals is crucial in the area of biomedical research. This book focuses on these techniques, providing expansive coverage of algorithms and tools from the field of digital signal processing. It discusses their applications to medical data, using graphs and topographic images to show simulation results that assess the efficacy of the methods. Additionally, expect to find: explanations of the significance of EEG signal analysis and processing (with examples) and a useful theoretical and mathematical background for the analysis and processing of EEG signals; an exploration of normal and abnormal EEGs, neurological symptoms and diagnostic information, and representations of the EEGs; reviews of theoretical approaches in EEG modelling, such as restoration, enhancement, segmentation, and the removal of different internal and external artefacts from the EEG and ERP (event-related potential) signals; coverage of major abnormalities such as seizure, and mental illnesses such as dementia, schizophrenia, and Alzheimer’s disease, together with their mathematical interpretations from the EEG and ERP signals and sleep phenomenon; descriptions of nonlinear and adaptive digital signal processing techniques for abnormality detection, source localization and brain-computer interfacing using multi-channel EEG data with emphasis on non-invasive techniques, together with future topics for research in the area of EEG signal processing. The information within EEG Signal Processing has the potential to enhance the clinically-related information within EEG signals, thereby aiding physicians and ultimately providing more cost effective, efficient diagnostic tools. It will be beneficial to psychiatrists, neurophysiologists, engineers, and students or researchers in neurosciences. Undergraduate and postgraduate biomedical engineering students and postgraduate epileptology students will also find it a helpful reference. Note de contenu : Contents 1 Introduction to EEG 1.1 History 1.2 Neural Activities 1.3 Action Potentials 1.4 EEG Generation 1.5 Brain Rhythms 1.6 EEG Recording and Measurement 1.7 Abnormal EEG Patterns 1.8 Ageing 1.9 Mental Disorders 1.10 Summary and Conclusions References 2 Fundamentals of EEG Signal Processing 2.1 EEG Signal Modelling 2.2 Nonlinearity of the Medium 2.3 Nonstationarity 2.4 Signal Segmentation 2.5 Signal Transforms and Joint Time–Frequency Analysis 2.6 Coherency, Multivariate Autoregressive (MVAR) Modelling, and Directed Transfer Function (DTF) 2.7 Chaos and Dynamical Analysis 2.8 Filtering and Denoising 2.9 Principal Component Analysis 2.10 Independent Component Analysis 2.11 Application of Constrained BSS: Example 2.12 Signal Parameter Estimation 2.13 Classification Algorithms 2.14 Matching Pursuits 2.15 Summary and Conclusions References 3 Event-Related Potentials 3.1 Detection, Separation, Localization, and Classification of P300 Signals 3.2 Brain Activity Assessment Using ERP 3.3 Application of P300 to BCI 3.4 Summary and Conclusions References 4 Seizure Signal Analysis 4.1 Seizure Detection 4.2 Chaotic Behaviour of EEG Sources 4.3 Predictability of Seizure from the EEGs\ 4.4 Fusion of EEG–fMRI Data for Seizure Prediction 4.5 Summary and Conclusions References 5 EEG Source Localization 5.1 Introduction 5.2 Overview of the Traditional Approaches 5.3 Determination of the Number of Sources 5.4 Summary and Conclusions References 6 Sleep EEG 6.1 Stages of Sleep 6.2 The Influence of Circadian Rhythms 6.3 Sleep Deprivation 6.4 Psychological Effects 6.5 Detection and Monitoring of Brain Abnormalities During Sleep by EEG Analysis 6.6 Concluding Remarks References 7 Brain–Computer Interfacing 7.1 State of the Art in BCI 7.2 Major Problems in BCI 7.3 Multidimensional EEG Decomposition 7.4 Detection and Separation of ERP Signals 7.5 Source Localization and Tracking of the Moving Sources within the Brain 7.6 Multivariant Autoregressive (MVAR) Modelling and Coherency Maps 7.7 Estimation of Cortical Connectivity 7.8 Summary and Conclusions References Index

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
2802	35-11-02	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2802
2803	35-11-02	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	2803

Handbook of biometrics / Anil K. Jain

Public ISBD Titre : Handbook of biometrics Type de document : texte imprimé Auteurs : Anil K. Jain, Auteur ; Patrick Flynn, Auteur ; Arun A. Ross, Auteur Editeur : Springer Année de publication : 2008 Importance : 556 p. Présentation : couv. ill. en coul., ill. Format : 23,9 cm. ISBN/ISSN/EAN : 978-0-387-71040-2 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Biometric recognition, or simply Biometrics, is a rapidly evolving field with applications ranging from accessing one's computer to gaining entry into a country. Biometric systems rely on the use of physical or behavioral traits, such as fingerprints, face, voice and hand geometry, to establish the identity of an individual. The deployment of large-scale biometric systems in both commercial (e.g., grocery stores, amusement parks, airports) and government (e.g., US-VISIT) applications has served to increase the public's awareness of this technology. This rapid growth has also highlighted the challenges associated with designing and deploying biometric systems. Indeed, the problem of biometric recognition is a "Grand Challenge" in its own right. The past five years has seen a significant growth in biometric research resulting in the development of innovative sensors, robust and efficient algorithms for feature extraction and matching, enhanced test methodologies and novel applications. These advances have resulted in robust, accurate, secure and cost effective biometric systems. The Handbook of Biometrics -- an edited volume contributed by prominent invited researchers in Biometrics -- describes the fundamentals as well as the latest advancements in the burgeoning field of biometrics. It is designed for professionals composed of practitioners and researchers in Biometrics, Pattern Recognition and Computer Security. The Handbook of Biometrics can be used as a primary textbook for an undergraduate biometrics class. This book is also suitable as a secondary textbook or reference for advanced-level students in computer science. Note de contenu : Contents 1 Introduction to Biometrics 2 Fingerprint Recognition 3 Face Recognition 4 Iris Recognition 5 Hand Geometry Recognition 6 Gait Recognition 7 The Ear as a Biometric 8 Voice Biometrics 9 A Palmprint Authentication System 10 On-Line Signature Verification 11 3D Face Recognition 12 Automatic Forensic Dental Identification 13 Hand Vascular Pattern Technology 14 Introduction to Multibiometrics 15 Multispectral Face Recognition 16 Multibiometrics Using Face and Ear 17 Incorporating Ancillary Information in Multibiometric Systems 18 The Law and the Use of Biometrics 19 Biometric System Security 20 Spoof Detection Schemes 21 Linkages between Biometrics and Forensic Science 22 Biometrics in the Government Sector 23 Biometrics in the Commercial Sector 24 Biometrics Standards 25 Biometrics databases Index Handbook of biometrics [texte imprimé] / Anil K. Jain, Auteur ; Patrick Flynn, Auteur ; Arun A. Ross, Auteur . - [S.l.] : Springer, 2008 . - 556 p. : couv. ill. en coul., ill. ; 23,9 cm. ISBN : 978-0-387-71040-2 Langues : Anglais (eng) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Biometric recognition, or simply Biometrics, is a rapidly evolving field with applications ranging from accessing one's computer to gaining entry into a country. Biometric systems rely on the use of physical or behavioral traits, such as fingerprints, face, voice and hand geometry, to establish the identity of an individual. The deployment of large-scale biometric systems in both commercial (e.g., grocery stores, amusement parks, airports) and government (e.g., US-VISIT) applications has served to increase the public's awareness of this technology. This rapid growth has also highlighted the challenges associated with designing and deploying biometric systems. Indeed, the problem of biometric recognition is a "Grand Challenge" in its own right. The past five years has seen a significant growth in biometric research resulting in the development of innovative sensors, robust and efficient algorithms for feature extraction and matching, enhanced test methodologies and novel applications. These advances have resulted in robust, accurate, secure and cost effective biometric systems. The Handbook of Biometrics -- an edited volume contributed by prominent invited researchers in Biometrics -- describes the fundamentals as well as the latest advancements in the burgeoning field of biometrics. It is designed for professionals composed of practitioners and researchers in Biometrics, Pattern Recognition and Computer Security. The Handbook of Biometrics can be used as a primary textbook for an undergraduate biometrics class. This book is also suitable as a secondary textbook or reference for advanced-level students in computer science. Note de contenu : Contents 1 Introduction to Biometrics 2 Fingerprint Recognition 3 Face Recognition 4 Iris Recognition 5 Hand Geometry Recognition 6 Gait Recognition 7 The Ear as a Biometric 8 Voice Biometrics 9 A Palmprint Authentication System 10 On-Line Signature Verification 11 3D Face Recognition 12 Automatic Forensic Dental Identification 13 Hand Vascular Pattern Technology 14 Introduction to Multibiometrics 15 Multispectral Face Recognition 16 Multibiometrics Using Face and Ear 17 Incorporating Ancillary Information in Multibiometric Systems 18 The Law and the Use of Biometrics 19 Biometric System Security 20 Spoof Detection Schemes 21 Linkages between Biometrics and Forensic Science 22 Biometrics in the Government Sector 23 Biometrics in the Commercial Sector 24 Biometrics Standards 25 Biometrics databases Index

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
1609	35-11-06	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	1609

Modélisation et débruitage du signal electrocardiogramme ECG / Mouna Ghanai

Public ISBD Titre : Modélisation et débruitage du signal electrocardiogramme ECG : identification et filtrage Type de document : texte imprimé Auteurs : Mouna Ghanai, Auteur ; Kheireddine Chafaa, Auteur Editeur : Allemagne : Presses Academiques Francophones Année de publication : 2014 Importance : 102 p. Présentation : couv. ill.,ill. Format : 22 cm. ISBN/ISSN/EAN : 978-3-8381-4265-4 Langues : Français (fre) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Les travaux de recherches présentés dans ce livre touchent essentiellement le débruitage des signaux physiologiques et spécialement les signaux électrocardiogrammes ECGs. L'ensemble des travaux peut être divisé en deux parties principales : - Modélisation intelligente du signal ECG, où la logique floue a été utilisée dans le but d'obtenir des modèles efficaces pour de tels signaux - Débruitage des signaux ECGs où deux types de bruits ont été considérés, les bruits blancs Gaussiens et les bruits à basses fréquences. Le filtre de Kalman a été optimisé par la méthode des PSO puis utilisé pour l'élimination des bruits blancs Gaussiens (lissage). La méthode des ondelettes a été utilisée pour l'élimination de la déformation de la ligne de base considérée ici comme un bruit à basse fréquence. Note de contenu : Table des matières Chapitre I L'anatomie du cœur et l'électrocardiographie Chapitre II Modélisation dynamique du signal ECG Chapitre III Identification floue pour systèmes et signaux Chapitre IV Débruitage du signal électrocardiogramme ECG par le filtre de Kalman étendu Conclusion générale Modélisation et débruitage du signal electrocardiogramme ECG : identification et filtrage [texte imprimé] / Mouna Ghanai, Auteur ; Kheireddine Chafaa, Auteur . - Allemagne : Presses Academiques Francophones, 2014 . - 102 p. : couv. ill.,ill. ; 22 cm. ISBN : 978-3-8381-4265-4 Langues : Français (fre) Catégories : GÉNIE BIOMÉDICAL Index. décimale : 35-11 Traitement des biosignaux Résumé : Les travaux de recherches présentés dans ce livre touchent essentiellement le débruitage des signaux physiologiques et spécialement les signaux électrocardiogrammes ECGs. L'ensemble des travaux peut être divisé en deux parties principales : - Modélisation intelligente du signal ECG, où la logique floue a été utilisée dans le but d'obtenir des modèles efficaces pour de tels signaux - Débruitage des signaux ECGs où deux types de bruits ont été considérés, les bruits blancs Gaussiens et les bruits à basses fréquences. Le filtre de Kalman a été optimisé par la méthode des PSO puis utilisé pour l'élimination des bruits blancs Gaussiens (lissage). La méthode des ondelettes a été utilisée pour l'élimination de la déformation de la ligne de base considérée ici comme un bruit à basse fréquence. Note de contenu : Table des matières Chapitre I L'anatomie du cœur et l'électrocardiographie Chapitre II Modélisation dynamique du signal ECG Chapitre III Identification floue pour systèmes et signaux Chapitre IV Débruitage du signal électrocardiogramme ECG par le filtre de Kalman étendu Conclusion générale

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité	N.Inventaire
3967	35-11-04	Livre	Bibliothèque de Génie Electrique- USTO	Documentaires	Exclu du prêt	3967

Speech, Audio, Image and Biomedical Signal Processing using Neural Networks / Bhanu Prasad

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Traitement de signaux phonocardiogrammes / Mohammed Sofiane Bendelhoum

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