Vinayak Bairagi's Books

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

By: Archana Bajirao Kanwade,Vinayak Bairagi

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Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

By: Archana Bajirao Kanwade,Vinayak Bairagi

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG) presents a new and innovative method of COPD diagnosis using EMG to analyze sternomastoid muscle activity using features extraction and classification. The book describes the methodology of EMG analysis, the slope-based onset detection algorithm and SEMG analysis in time, frequency and time frequency domain analyses. It also explores the identification of frequencies for single frequency Continuous Wavelet Transform (CWT) analysis and feature extraction and selection for successful classification COPD into its severity grades. The book provides a compilation of all techniques used in the literatures and emphasizes newly proposed techniques for the early detection of COPD. Fully comprehensive, the book includes discussion of limitations of existing methods for COPD diagnosis and introduces new efficient methods for COPD identification, classification and early diagnosis. - Provides an easy, simple and comprehensive guide to using EMG analysis for COPD diagnosis - Presents detailed explanations of the recently developed slope-based onset detection algorithm for muscle activity detection, along with numerous original figures, tables and graphs to aid interpretation - Includes a complete review of various features, such as extraction using single frequency CWT analysis and the feature selection algorithm for COPD diagnosis

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Page Count

194

Publisher

Academic Press

Published Date

ISBN 10

0323886086

ISBN 13

9780323886086

Multimodal Biometric Identification System

Case Study of Real-Time Implementation

By: Sampada Dhole,Vinayak Bairagi

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Multimodal Biometric Identification System

Case Study of Real-Time Implementation

By: Sampada Dhole,Vinayak Bairagi

This book presents a novel method of multimodal biometric fusion using a random selection of biometrics, which covers a new method of feature extraction, a new framework of sensor-level and feature-level fusion. Most of the biometric systems presently use unimodal systems, which have several limitations. Multimodal systems can increase the matching accuracy of a recognition system. This monograph shows how the problems of unimodal systems can be dealt with efficiently, and focuses on multimodal biometric identification and sensor-level, feature-level fusion. It discusses fusion in biometric systems to improve performance. • Presents a random selection of biometrics to ensure that the system is interacting with a live user. • Offers a compilation of all techniques used for unimodal as well as multimodal biometric identification systems, elaborated with required justification and interpretation with case studies, suitable figures, tables, graphs, and so on. • Shows that for feature-level fusion using contourlet transform features with LDA for dimension reduction attains more accuracy compared to that of block variance features. • Includes contribution in feature extraction and pattern recognition for an increase in the accuracy of the system. • Explains contourlet transform as the best modality-specific feature extraction algorithms for fingerprint, face, and palmprint. This book is for researchers, scholars, and students of Computer Science, Information Technology, Electronics and Electrical Engineering, Mechanical Engineering, and people working on biometric applications.

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Page Count

142

Publisher

CRC Press

Published Date

ISBN 10

1040148131

ISBN 13

9781040148136

EEG-Based Diagnosis of Alzheimer Disease

A Review and Novel Approaches for Feature Extraction and Classification Techniques

By: Nilesh Kulkarni,Vinayak Bairagi

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EEG-Based Diagnosis of Alzheimer Disease

A Review and Novel Approaches for Feature Extraction and Classification Techniques

By: Nilesh Kulkarni,Vinayak Bairagi

EEG-Based Diagnosis of Alzheimer Disease: A Review and Novel Approaches for Feature Extraction and Classification Techniques provides a practical and easy-to-use guide for researchers in EEG signal processing techniques, Alzheimer's disease, and dementia diagnostics. The book examines different features of EEG signals used to properly diagnose Alzheimer's Disease early, presenting new and innovative results in the extraction and classification of Alzheimer's Disease using EEG signals. This book brings together the use of different EEG features, such as linear and nonlinear features, which play a significant role in diagnosing Alzheimer's Disease. - Includes the mathematical models and rigorous analysis of various classifiers and machine learning algorithms from a perspective of clinical deployment - Covers the history of EEG signals and their measurement and recording, along with their uses in clinical diagnostics - Analyzes spectral, wavelet, complexity and other features of early and efficient Alzheimer's Disease diagnostics - Explores support vector machine-based classification to increase accuracy

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Page Count

112

Publisher

Academic Press

Published Date

ISBN 10

0128153938

ISBN 13

9780128153932

Brain Seizure Detection and Classification Using EEG Signals

By: Varsha K. Harpale,Vinayak Bairagi

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Brain Seizure Detection and Classification Using EEG Signals

By: Varsha K. Harpale,Vinayak Bairagi

Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT). The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance. - Presents EEG signal processing and analysis concepts with high performance feature extraction - Discusses recent trends in seizure detection, prediction and classification methodologies - Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication - Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet

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Page Count

178

Publisher

Academic Press

Published Date

ISBN 10

0323911218

ISBN 13

9780323911214

EEG-Based Diagnosis of Alzheimer Disease

A Review and Novel Approaches for Feature Extraction and Classification Techniques

By: Nilesh Kulkarni,Vinayak Bairagi

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EEG-Based Diagnosis of Alzheimer Disease

A Review and Novel Approaches for Feature Extraction and Classification Techniques

By: Nilesh Kulkarni,Vinayak Bairagi

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Solve jigsaw puzzle

Age

Page Count

112

Publisher

Academic Press

Published Date

ISBN 10

0128153938

ISBN 13

9780128153932

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

By: Archana Bajirao Kanwade,Vinayak Bairagi

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Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

By: Archana Bajirao Kanwade,Vinayak Bairagi

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Solve jigsaw puzzle

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Page Count

194

Publisher

Academic Press

Published Date

ISBN 10

0323886086

ISBN 13

9780323886086

Multimodal Biometric Identification System

Case Study of Real-Time Implementation

By: Sampada Dhole,Vinayak Bairagi

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Multimodal Biometric Identification System

Case Study of Real-Time Implementation

By: Sampada Dhole,Vinayak Bairagi

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N/A

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Solve jigsaw puzzle

Age

Page Count

142

Publisher

CRC Press

Published Date

ISBN 10

1040148131

ISBN 13

9781040148136

Brain Seizure Detection and Classification Using EEG Signals

By: Varsha K. Harpale,Vinayak Bairagi

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Brain Seizure Detection and Classification Using EEG Signals

By: Varsha K. Harpale,Vinayak Bairagi

Brain Seizure Detection and Classification Using Electroencephalographic Signals presents EEG signal processing and analysis with high performance feature extraction. The book covers the feature selection method based on One-way ANOVA, along with high performance machine learning classifiers for the classification of EEG signals in normal and epileptic EEG signals. In addition, the authors also present new methods of feature extraction, including Singular Spectrum-Empirical Wavelet Transform (SSEWT) for improved classification of seizures in significant seizure-types, specifically epileptic and Non-Epileptic Seizures (NES). The performance of the system is compared with existing methods of feature extraction using Wavelet Transform (WT) and Empirical Wavelet Transform (EWT). The book's objective is to analyze the EEG signals to observe abnormalities of brain activities called epileptic seizure. Seizure is a neurological disorder in which too many neurons are excited at the same time and are triggered by brain injury or by chemical imbalance. Presents EEG signal processing and analysis concepts with high performance feature extraction Discusses recent trends in seizure detection, prediction and classification methodologies Helps classify epileptic and non-epileptic seizures where misdiagnosis may lead to the unnecessary use of antiepileptic medication Provides new guidance and technical discussions on feature-extraction methods and feature selection methods based on One-way ANOVA, along with high performance machine learning classifiers for classification of EEG signals in normal and epileptic EEG signals, and new methods of feature extraction developed by the authors, including Singular Spectrum-Empirical Wavelet

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Page Count

176

Publisher

Elsevier

Published Date

ISBN 10

032391120X

ISBN 13

9780323911207

Book's by Vinayak Bairagi

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

Multimodal Biometric Identification System

Multimodal Biometric Identification System

EEG-Based Diagnosis of Alzheimer Disease

EEG-Based Diagnosis of Alzheimer Disease

Brain Seizure Detection and Classification Using EEG Signals

Brain Seizure Detection and Classification Using EEG Signals

EEG-Based Diagnosis of Alzheimer Disease

EEG-Based Diagnosis of Alzheimer Disease

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

Chronic Obstructive Pulmonary Disease (COPD) Diagnosis using Electromyography (EMG)

Multimodal Biometric Identification System

Multimodal Biometric Identification System

Brain Seizure Detection and Classification Using EEG Signals

Brain Seizure Detection and Classification Using EEG Signals

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