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

Produk Detail:

  • 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 : 02 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 : 25 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

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

Biomedical Signal Processing

Biomedical Signal Processing
  • Author : Metin Akay
  • Publisher : Academic Press
  • Release : 02 December 2012
GET THIS BOOKBiomedical Signal Processing

Sophisticated techniques for signal processing are now available to the biomedical specialist! Written in an easy-to-read, straightforward style, Biomedical Signal Processing presents techniques to eliminate background noise, enhance signal detection, and analyze computer data, making results easy to comprehend and apply. In addition to examining techniques for electrical signal analysis, filtering, and transforms, the author supplies an extensive appendix with several computer programs that demonstrate techniques presented in the text.

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

Signal Processing and Machine Learning for Biomedical Big Data

Signal Processing and Machine Learning for Biomedical Big Data
  • Author : Ervin Sejdic,Tiago H. Falk
  • Publisher : CRC Press
  • Release : 04 July 2018
GET THIS BOOKSignal Processing and Machine Learning for Biomedical Big Data

This will be a comprehensive, multi-contributed reference work that will detail the latest research and developments in biomedical signal processing related to big data medical analysis. It will describe signal processing, machine learning, and parallel computing strategies to revolutionize the world of medical analytics and diagnosis as presented by world class researchers and experts in this important field. The chapters will desribe tools that can be used by biomedical and clinical practitioners as well as industry professionals. It will give

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,

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

Digital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine
  • Author : Lotfi Chaari
  • Publisher : Springer
  • Release : 10 July 2019
GET THIS BOOKDigital Health Approach for Predictive, Preventive, Personalised and Participatory Medicine

This collection, entitled Digital Health for Predictive, Preventive, Personalized and Participatory Medicine contains the proceedings of the first International conference on digital healthtechnologies (ICDHT 2018). Ten recent contributions in the fields of Artificial Intelligence (AI) and machine learning, Internet of Things (IoT) and data analysis, all applied to digital health. This collection enables researchers to learn about recent advances in the above mentioned fields. It brings a technological viewpoint of P4 medicine. Readers will discover how advanced Information Technology (IT) tools

Biomedical Signal and Image Processing

Biomedical Signal and Image Processing
  • Author : Kayvan Najarian,Robert Splinter
  • Publisher : CRC Press
  • Release : 19 April 2016
GET THIS BOOKBiomedical Signal and Image Processing

Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of

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

Health Monitoring Systems

Health Monitoring Systems
  • Author : Rajarshi Gupta,Dwaipayan Biswas
  • Publisher : CRC Press
  • Release : 21 November 2019
GET THIS BOOKHealth Monitoring Systems

Remote health monitoring using wearable sensors is an important research area involving several key steps: physiological parameter sensing and data acquisition, data analysis, data security, data transmission to caregivers, and clinical intervention, all of which play a significant role to form a closed loop system. Subject-specific behavioral and clinical traits, coupled with individual physiological differences, necessitate a personalized healthcare delivery model for around-the-clock monitoring within the home environment. Cardiovascular disease monitoring is an illustrative application domain where research has been

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging
  • Author : Nilanjan Dey,Surekha Borra,Amira S. Ashour,Fuqian Shi
  • Publisher : Academic Press
  • Release : 30 November 2018
GET THIS BOOKMachine Learning in Bio-Signal Analysis and Diagnostic Imaging

Machine Learning in Bio-Signal Analysis and Diagnostic Imaging presents original research on the advanced analysis and classification techniques of biomedical signals and images that cover both supervised and unsupervised machine learning models, standards, algorithms, and their applications, along with the difficulties and challenges faced by healthcare professionals in analyzing biomedical signals and diagnostic images. These intelligent recommender systems are designed based on machine learning, soft computing, computer vision, artificial intelligence and data mining techniques. Classification and clustering techniques, such as

IoT and ICT for Healthcare Applications

IoT and ICT for Healthcare Applications
  • Author : Nishu Gupta,Sara Paiva
  • Publisher : Springer Nature
  • Release : 12 August 2020
GET THIS BOOKIoT and ICT for Healthcare Applications

This book provides an insight on the importance that Internet of Things (IoT) and Information and Communication Technology (ICT) solutions can have in taking care of people's health. Key features of this book present the recent and emerging developments in various specializations in curing health problems and finding their solutions by incorporating IoT and ICT. This book presents useful IoT and ICT applications and architectures that cater to their improved healthcare requirements. Topics include in-home healthcare services based on the