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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.
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