Biomedical Signal Processing for Healthcare Applications Biomedical Signal Processing for Healthcare Applications
Emerging Trends in Biomedical Technologies and Health informatics

Biomedical Signal Processing for Healthcare Applications

Varun Bajaj and Others
    • $59.99
    • $59.99

Publisher Description

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 Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications.

FEATURES
Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems
This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

GENRE
Professional & Technical
RELEASED
2021
July 20
LANGUAGE
EN
English
LENGTH
336
Pages
PUBLISHER
CRC Press
SELLER
Taylor & Francis Group
SIZE
24.5
MB
Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare Analysis of Medical Modalities for Improved Diagnosis in Modern Healthcare
2021
Artificial Intelligence-Based Brain-Computer Interface Artificial Intelligence-Based Brain-Computer Interface
2022
Computer-aided Design and Diagnosis Methods for Biomedical Applications Computer-aided Design and Diagnosis Methods for Biomedical Applications
2021
Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering Evolution of Machine Learning and Internet of Things Applications in Biomedical Engineering
2024
Computational Approaches in Biotechnology and Bioinformatics Computational Approaches in Biotechnology and Bioinformatics
2024
Computational Approaches in Biomaterials and Biomedical Engineering Applications Computational Approaches in Biomaterials and Biomedical Engineering Applications
2024
Healthcare Services in the Metaverse Healthcare Services in the Metaverse
2024
Deep Learning in Biomedical and Health Informatics Deep Learning in Biomedical and Health Informatics
2021
Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems Machine Learning and Deep Learning in Efficacy Improvement of Healthcare Systems
2022