While doctors and physicians are more than capable of detecting diseases of the brain, the most agile human mind cannot compete with the processing power of modern technology. Utilizing algorithmic systems in healthcare in this way may provide a way to treat neurological diseases before they happen. Early Detection of Neurological Disorders Using Machine Learning Systems provides innovative insights into implementing smart systems to detect neurological diseases at a faster rate than by normal means. The topics included in this book are artificial intelligence, data analysis, and biomedical informatics. It is designed for clinicians, doctors, neurologists, physiotherapists, neurorehabilitation specialists, scholars, academics, and students interested in topics centered on biomedical engineering, bio-electronics, medical electronics, physiology, neurosciences, life sciences, and physics.

Technological advancements in the last few decades have significantly revolutionized the healthcare industry, resulting in life expectancy improvement in human beings. The use of automated machines in healthcare has reduced human errors and has notably improved disease diagnosis efficiency. Design and Development of Affordable Healthcare Technologies provides emerging research on biomedical instrumentation, bio-signal processing, and device development within the healthcare industry. This book provides insight into various subjects including patient monitoring, medical imaging, and disease classification. This book is a vital reference source for medical professionals, biomedical engineers, scientists, researchers, and medical students interested in the comprehensive research on the advancements in healthcare technologies.

Advanced Methods in Biomedical Signal Processing and Analysis presents state-of-the-art methods in biosignal processing, including recurrence quantification analysis, heart rate variability, analysis of the RRI time-series signals, joint time-frequency analyses, wavelet transforms and wavelet packet decomposition, empirical mode decomposition, modeling of biosignals, Gabor Transform, empirical mode decomposition. The book also gives an understanding of feature extraction, feature ranking, and feature selection methods, while also demonstrating how to apply artificial intelligence and machine learning to biosignal techniques.