Biomedical signal processing for healthcare applications
著者
書誌事項
Biomedical signal processing for healthcare applications
（Emerging trends in biomedical technologies and health informatics series）
CRC Press, 2022
- : hbk
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
1. Automatic Sleep EEG Classification with Ensemble Learning Using Graph Modularity 2. Recognition of Distress Phase Situation in Human Emotion EEG Physiological Signals 3. Analysis and Classification of Heart Abnormalities 4. Diagnosis of Parkinson's Disease Using Deep Learning Approaches: A Review 5. Classifying Phonological Categories and Imagined Words from EEG Signal 6. Blood Pressure Monitoring Using Photoplethysmogram and Electrocardiogram Signals 7. Investigation of the Efficacy of Acupuncture Using Electromyographic Signals 8. Appliance Control System for Physically Challenged and Elderly Persons through Hand Gesture-Based Sign Language 9. Computer-Aided Drug Designing - Modality of Diagnostic System 10. Diagnosing Chest-Related Abnormalities Using Medical Image Processing through Convolutional Neural Network 11. Recent Trends in Healthcare System for Diagnosis of Three Diseases Using Health Informatics 12. Nursing Care System Based on Internet of Medical Things (IoMT) through Integrating Non-Invasive Blood Sugar (BS) and Blood Pressure (BP) Combined Monitoring 13. Eye Disease Detection from Retinal Fundus Image Using CNN
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