Biomedical Signal Processing for Healthcare Applications

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Synopsis

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.

Book details

Series:
Emerging Trends in Biomedical Technologies and Health informatics
Author:
Varun Bajaj, G. R. Sinha, Chinmay Chakraborty
ISBN:
9781000413304
Related ISBNs:
9780367707545, 9781003147817, 9780367705879
Publisher:
CRC Press
Pages:
316
Reading age:
Not specified
Includes images:
No
Date of addition:
2021-07-20
Usage restrictions:
Copyright
Copyright date:
2021
Copyright by:
N/A 
Adult content:
No
Language:
English
Categories:
Medicine, Nonfiction, Science, Technology