Biomedical signal processing stands at the intersection of engineering innovation and medical advancement, offering transformative solutions for healthcare diagnostics and monitoring. Over recent decades, the field has evolved from basic signal filtering to encompass sophisticated analysis techniques across time and frequency domains, driving progress in wearable technology, telemedicine, and artificial intelligence.

This book, “Biomedical Signal Processing: Techniques and Applications,” represents the collective vision and expertise of its authors, each contributing insights from clinical research, academic innovation, and technical development. Our aim is to offer readers a comprehensive resource that bridges theory and practice, covering essential topics such as acquisition, preprocessing, feature extraction, and classification of physiological signals like ECG, EEG, EMG, and blood pressure. Real-world examples and practical case studies illuminate the application of advanced algorithms—ranging from digital filtering to machine learning—underscoring their impact on diagnostic reliability and patient outcomes.

The audience for this book spans postgraduate students, researchers, and professionals in biomedical engineering and health informatics, as well as technical experts seeking deeper understanding of biomedical data analysis. Throughout the chapters, readers will encounter discussions of signal transformation methods, statistical modeling, and intelligent decision-making systems—all informed by the authors’ experience in clinical and research settings.

It is our hope that this volume serves not only as an academic guide but also as an inspiration for future innovation in biomedical signal processing. We thank our collaborators, students, and supporters who fostered valuable discussions and contributed to the growth of this discipline. May this book empower its readers to make meaningful advances in both engineering and medicine.