ENHANCED APPROACH IN BIOMEDICAL SIGNAL PROCESS AND ANALYSIS

Biomedical signal processing is a rapidly evolving field that
plays a critical role in modern healthcare, enabling the extraction and
interpretation of valuable information from physiological signals for
diagnostic and therapeutic applications. With the ever-growing
complexity and volume of biomedical data, there is an increasing
demand for advanced signal processing techniques that enhance the
accuracy, reliability, and efficiency of data analysis. This book, titled
“Enhanced Approach in Biomedical Signal Processing and
Analysis,” aims to provide a comprehensive exploration of both
fundamental and advanced concepts in biomedical signal processing,
with a special emphasis on practical applications, machine learning,
and artificial intelligence.
The book begins with an introduction to the basics of signals and
their processing, delving into different types of signals such as
analog, digital, and discrete, and how they can be transformed and
manipulated to extract meaningful features. The initial chapters
cover essential topics, including signal transformation, noise
filtering, feature extraction, and image processing, setting a strong
foundation for understanding the unique characteristics of
biomedical signals.
Subsequent chapters focus on specific types of biomedical signals,
such as electrocardiograms (ECG), electroencephalograms (EEG),
electromyograms (EMG), and other physiological signals. The
detailed discussions cover the engineering aspects of signal
acquisition, noise reduction, and feature extraction, providing
readers with a clear understanding of the challenges and
opportunities inherent in working with these complex datasets.
Particular attention is given to the clinical significance of these

signals and the implications of their analysis for medical diagnostics
and patient care.