Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications

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  • Author : Sridhar Krishnan
  • Publisher : Elsevier
  • Pages : 334 pages
  • ISBN : 0128130865
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBiomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare
  • Author : Sridhar Krishnan
  • Publisher : Elsevier
  • Release : 09 July 2021
GET THIS BOOKBiomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare.

Biomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare
  • Author : Sridhar Krishnan
  • Publisher : Academic Press
  • Release : 23 June 2021
GET THIS BOOKBiomedical Signal Analysis for Connected Healthcare

Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare.

Biomedical Signal Processing for Healthcare Applications

Biomedical Signal Processing for Healthcare Applications
  • Author : Varun Bajaj,G. R. Sinha,Chinmay Chakraborty
  • Publisher : CRC Press
  • Release : 21 July 2021
GET THIS BOOKBiomedical Signal Processing for Healthcare Applications

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal

Biomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare
  • Author : Walid A. Zgallai
  • Publisher : Academic Press
  • Release : 29 July 2020
GET THIS BOOKBiomedical Signal Processing and Artificial Intelligence in Healthcare

Biomedical Signal Processing and Artificial Intelligence in Healthcare is a new volume in the Developments in Biomedical Engineering and Bioelectronics series. This volume covers the basics of biomedical signal processing and artificial intelligence. It explains the role of machine learning in relation to processing biomedical signals and the applications in medicine and healthcare. The book provides background to statistical analysis in biomedical systems. Several types of biomedical signals are introduced and analyzed, including ECG and EEG signals. The role of

Biomedical Signal Analysis

Biomedical Signal Analysis
  • Author : Rangaraj M. Rangayyan
  • Publisher : John Wiley & Sons
  • Release : 24 April 2015
GET THIS BOOKBiomedical Signal Analysis

The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications 800 mathematical expressions and equations Practical questions, problems and laboratory exercises Includes fractals and chaos theory with biomedical applications

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
  • Author : Abdulhamit Subasi
  • Publisher : Academic Press
  • Release : 16 March 2019
GET THIS BOOKPractical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques,

Biomedical Signal Analysis

Biomedical Signal Analysis
  • Author : Fabian J. Theis,Anke Meyer-Bäse
  • Publisher : MIT Press
  • Release : 15 August 2022
GET THIS BOOKBiomedical Signal Analysis

A comprehensive introduction to innovative methods in the field of biomedical signal analysis, covering both theory and practice. Biomedical signal analysis has become one of the most important visualization and interpretation methods in biology and medicine. Many new and powerful instruments for detecting, storing, transmitting, analyzing, and displaying images have been developed in recent years, allowing scientists and physicians to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. This book offers an overview of a range of proven

Practical Biomedical Signal Analysis Using MATLAB®

Practical Biomedical Signal Analysis Using MATLAB®
  • Author : Katarzyn J. Blinowska,Jaroslaw Zygierewicz
  • Publisher : CRC Press
  • Release : 12 September 2011
GET THIS BOOKPractical Biomedical Signal Analysis Using MATLAB®

Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely

Advanced Methods in Biomedical Signal Processing and Analysis

Advanced Methods in Biomedical Signal Processing and Analysis
  • Author : Kunal Pal,Samit Ari,Arindam Bit,Saugat Bhattacharyya
  • Publisher : Academic Press
  • Release : 15 June 2022
GET THIS BOOKAdvanced Methods in Biomedical Signal Processing and Analysis

Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques. Gives advanced methods in

Personalized Health Systems for Cardiovascular Disease

Personalized Health Systems for Cardiovascular Disease
  • Author : Anna Maria Bianchi,Jorge Henriques,Vicente Traver Salcedo
  • Publisher : Academic Press
  • Release : 25 January 2022
GET THIS BOOKPersonalized Health Systems for Cardiovascular Disease

Personalized Health Systems for Cardiovascular Disease is intended for researchers, developers, and designers in the field of p-health, with a specific focus on management of cardiovascular diseases. Biomedical engineers will benefit from coverage of sensors, data transmission, signal processing, data analysis, home and mobile applications, standards, and all other subject matters developed in this book in order to provide an integrated view of the different and multidisciplinary problems related to p-health systems. However, many chapters will also be interesting to

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
  • Author : Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
  • Publisher : Academic Press
  • Release : 14 January 2020
GET THIS BOOKDeep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they

Ultra Low-Power Biomedical Signal Processing

Ultra Low-Power Biomedical Signal Processing
  • Author : Sandro Augusto Pavlik Haddad,Wouter A. Serdijn
  • Publisher : Springer Science & Business Media
  • Release : 26 May 2009
GET THIS BOOKUltra Low-Power Biomedical Signal Processing

Often WT systems employ the discrete wavelet transform, implemented on a digital signal processor. However, in ultra low-power applications such as biomedical implantable devices, it is not suitable to implement the WT by means of digital circuitry due to the relatively high power consumption associated with the required A/D converter. Low-power analog realization of the wavelet transform enables its application in vivo, e.g. in pacemakers, where the wavelet transform provides a means to extremely reliable cardiac signal detection.

Photoplethysmography

Photoplethysmography
  • Author : Panicos A. Kyriacou,John Allen
  • Publisher : Academic Press
  • Release : 03 November 2021
GET THIS BOOKPhotoplethysmography

Photoplethysmography: Technology, Signal Analysis, and Applications is the first comprehensive volume on the theory, principles, and technology (sensors and electronics) of photoplethysmography (PPG). It provides a detailed description of the current state-of-the-art technologies/optical components enabling the extreme miniaturization of such sensors, as well as comprehensive coverage of PPG signal analysis techniques including machine learning and artificial intelligence. The book also outlines the huge range of PPG applications in healthcare, with a strong focus on the contribution of PPG in

Classification and Clustering in Biomedical Signal Processing

Classification and Clustering in Biomedical Signal Processing
  • Author : Dey, Nilanjan
  • Publisher : IGI Global
  • Release : 07 April 2016
GET THIS BOOKClassification and Clustering in Biomedical Signal Processing

Advanced techniques in image processing have led to many innovations supporting the medical field, especially in the area of disease diagnosis. Biomedical imaging is an essential part of early disease detection and often considered a first step in the proper management of medical pathological conditions. Classification and Clustering in Biomedical Signal Processing focuses on existing and proposed methods for medical imaging, signal processing, and analysis for the purposes of diagnosing and monitoring patient conditions. Featuring the most recent empirical research

Machine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare
  • Author : Krishna Kant Singh,Mohamed Elhoseny,Akansha Singh,Ahmed A. Elngar
  • Publisher : Academic Press
  • Release : 26 April 2021
GET THIS BOOKMachine Learning and the Internet of Medical Things in Healthcare

Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide. The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and