Biomedical Signal Processing for Healthcare Applications
- Available for pre-order. Item will ship after July 21, 2021
This book examines biomedical signal processing in which biomedical signals such as EEG, EMG, ECG are used to analyze and diagnosis various medical conditions. These modalities are used in diagnosis of dangerous illness related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals will subsequently benefit the healthcare sector by improving improving patient outcomes through early and more reliable detection. The discussion of these modalities will help in better understanding, analysis and application of biomedical signal processing for specific diseases. The major highlights of the book include biomedical signals; acquisition of the signals; pre-processing and analysis; post-processing and classification of the signals; application of analysis and classification for diagnosis of brain- and heart-related diseases. Emphasis is given to the brain and heart signals because major complications and poorer interpretations are made by the physicians in quite a number of situations. 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.
Table of Contents
1. Automatic Sleep EEG Classification with Ensemble Learning using Graph Modularity.
Sudarson Jena, Jibendu Kumar Mantri, Chinmaya Misra
2. Recognition of distress phase situation in human emotion EEG physiological signals.
Abdultaofeek Abayomi, Oludayo Olufolorunso Olugbara, Delene Heukelman
3. Analysis and Classification of Heart Abnormailities.
4. Diagnosis of Parkinson’s diseases using deep learning approaches: a review.
Priyanka Khanna, Mridu Sahu, Bikesh Kumar Singh
5. Classifying phonological categories and imagined words from EEG signals (Design, Method, Simulation, idea, writing).
Ashwin Kamble, Pradnya Ghare, Vinay Kumar
6. Blood pressure monitoring using photoplethysmogram and electrocardiogram signals.
Jamal Esmaelpoor, Zahra Momayez Sanat, Mohammad Hassan Moradi
7. Investigation of the Efficacy of Acupuncture Using Electromyographic Signals.
Kim Ho Yeap, Wey Long Ng, Humaira Nisar, Veerendra Dakulagi
8. Appliance Control System for Physically Challenged and Elderly Persons through Hand Gesture based Sign Language.
Boopathi Raja G
9. Computer aided Drug Designing- modality of diagnostic system.
Shalini Ramesh, Sugumari Vallinayagam, Karthikeyan Rajendran, Sasireka Rajendran, Vinoth Rathinam, Sneka Ramesh
10. Diagnosing Chest related Abnormalities using Medical Image Processing through Convolutional Neural Network.
Sneka Ramesh, Vignessh B, Reena Raj, Balakrishnakumar V
11. Recent Trends in Healthcare System for Diagnosis of Three Diseases Using Health Informatics.
Shawni Dutta, Samir Kumar Bandyopadhyay
12. Nursing Care System Based on Internet of Medical Things (IOMT) Through Integrate Non-Invasive Blood Sugar (BS) And Blood Pressure (BP) Combined Monitoring.
Patrali Pradhan, Subham Ghosh, Biswarup Neogi
13. Eye Disease Detection from Retinal Fundus Image using CNN.
Padma Selvaraj, Pugazendi Rajagopal
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.