Advanced Engineering Applications of Machine Learning, Deep Learning, and IoT

Biomedical signals provide measurable representations of physiological processes occurring within the human body and form an essential foundation for modern biomedical engineering and medical diagnostics. Electrical activity of the heart, brain, and muscles, along with mechanical, thermal, biochemical, and acoustic phenomena generated during physiological function, produce signals that reflect the dynamic behaviour of biological systems. Careful acquisition, analysis, and interpretation of these signals enable observation of organ function, detection of abnormalities, and continuous monitoring of patient health. This monograph, Fundamental Physiology and Dynamic Characteristics of Biomedical Signals, presents a comprehensive introduction to the physiological origins, classification, acquisition systems, and analytical techniques associated with biomedical signals. The text explores fundamental aspects of human physiology, mechanisms of bioelectric signal generation, signal acquisition hardware, characteristics of physiological signals, and important biomedical signals such as ECG, EEG, and EMG. Modern signal processing methods, feature extraction techniques, and machine learning approaches for medical diagnosis are also discussed alongside emerging applications in smart healthcare technologies. The content aims to provide clear conceptual understanding for students, researchers, and professionals interested in biomedical engineering, healthcare technology, and physiological signal analysis, while highlighting the importance of biomedical signals in advancing diagnostic medicine, patient monitoring, and intelligent healthcare systems.