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Biosignal processing is an important tool in medicine. As such, this book presents a comprehensive overview of novel methods in biosignal theory, biosignal processing algorithms and applications, and biosignal sensors. Chapters examine biosignal processing for glucose detection, tissue engineering, electrocardiogram processing, soft tissue tomography, and much more. The book also discusses applications of artificial intelligence and machine learning for biosignal processing.
Characteristic Profiles of Heart Rate Variability in Depression and Anxiety
Mathematical Morphology and the Heart Signals
Applications of Quantum Mechanics, Laws of Classical Physics, and Differential Calculus to Evaluate Source Localization According to the Electroencephalogram
Protecting Bioelectric Signals from Electromagnetic Interference in a Wireless World
Non-Invasive Approach for Glucose Detection in Urine Quality Using Its Image Analysis
Deep Learning Algorithms for Efficient Analysis of ECG Signals to Detect Heart Disorders
EEG Authentication System Using Fuzzy Vault Scheme
Automatic Noise Reduction in Ultrasonic Computed Tomography Image for Adult Bone Fracture Detection
Soft Tissue Image Reconstruction Using Diffuse Optical Tomography
Effective EEG Artifact Removal from EEG Signal
Developmental Studies on Practical Enzymatic Phosphate Ion Biosensors and Microbial BOD Biosensors, and New Insights into the Future Perspectives of These Biosensor Fields
Nanostructures in Biosensors: Development and Applications
Biological Sensing Using Infrared SPR Devices Based on ZnO
Development of Simple and Portable Surface Acoustic Wave Biosensors for Applications in Biology and Medicine
Recent Advances in Biosensing in Tissue Engineering and Regenerative Medicine
NanoBioSensors: From Electrochemical Sensors Improvement to Theranostic Applications