Del i serien Emerging Trends in Biomedical Technologies and Health informatics

Biomedical Signal Processing for Healthcare Applications

Häftad, Engelska, 2023

AvVarun Bajaj,G. R. Sinha,Chinmay Chakraborty

1 079 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

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 systemsThis 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.

Produktinformation

Utgivningsdatum2023-09-25
Mått156 x 234 x 18 mm
Vikt740 g
FormatHäftad
SpråkEngelska
SerieEmerging Trends in Biomedical Technologies and Health informatics
Antal sidor316
FörlagTaylor & Francis Ltd
ISBN9780367707545

Tillhör följande kategorier

Biokemisk teknik inom Naturvetenskap och teknik
Energiteknik inom Naturvetenskap och teknik
Biomedicinsk teknik inom Medicin
Medicin: icke kliniska discipliner inom Medicin

Dr. Varun Bajaj has been working as a faculty in the discipline of Electronics and Communication Engineering, at Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Jabalpur, India since 2014. G R Sinha is Adjunct Professor at International Institute of Information Technology Bangalore (IIITB) and currently deputed as Professor at Myanmar Institute of Information Technology (MIIT) Mandalay Myanmar. Dr. Chinmay Chakraborty is working as an Assistant Professor (Sr.) in the Dept. of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India.

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

Du kanske också är intresserad av