This book examines the use of biomedical signal processing 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, analysis of biomedical signals improves patient outcomes through early, reliable detection.

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