Deep Learning for Cardiac Signal Analysis in Robotic Applications

Nyhet

Häftad, Engelska, 2026

2 319 kr

Kommande

Deep Learning for Cardiac Signal Analysis in Robotic Applications delves into the transformative role of artificial intelligence in enhancing robotic-assisted cardiovascular procedures. Addressing the complexities of heart signal interpretation amidst the dynamic environment of cardiac surgery, this book meets the critical need for a comprehensive resource that bridges deep learning advances with practical surgical applications. It responds to the challenge of understanding intricate bio-signals, such as ECG, VCG, and BCG, by providing clear explanations, case studies, and methodological insights tailored to improve surgical precision, safety, and patient outcomes. The book is organized into three parts, starting with the fundamentals of cardiac signals and deep learning. It introduces key heart modalities, including the physiological underpinnings and challenges of signals like ECG and BCG, followed by an overview of deep learning architectures relevant to signal processing. Pre-processing and feature extraction techniques are detailed to prepare readers for advanced analysis. Part II focuses on AI-enhanced cardiac signal analysis, covering arrhythmia detection, myocardial ischemia diagnostics, hypertension monitoring via BCG, and explainable AI approaches for fetal arrhythmia monitoring. The final section integrates AI with robotic cardiac surgery, addressing real-time signal integration, AI-guided intervention precision, intraoperative decision support, postoperative monitoring, and future trends in cardiac AI and robotic-assisted surgery.

This book is an invaluable resource for engineering students and academicians seeking to deepen their understanding of AI applications in healthcare. It equips readers with practical knowledge to tackle challenges in cardiac signal processing and robotic application, fostering interdisciplinary expertise that spans biomedical engineering, computer science, and clinical practice. This book not only advances academic research but also supports innovation in developing intelligent surgical systems and improving patient care.

Bridges deep learning techniques with practical cardiac robotic surgery applications for improved clinical outcomes and safety
Offers clear explanations and case studies to simplify complex AI concepts for multidisciplinary audiences
Provides comprehensive coverage of cardiac signal processing, including noise reduction and anomaly detection methods
Highlights real-time AI integration for enhanced surgical decision-making and precision in robotic interventions
Explores ethical, regulatory, and future trends in AI-assisted cardiac healthcare and robotic surgery advancements

Produktinformation

Utgivningsdatum2026-05-01
Mått191 x 235 x undefined mm
Vikt450 g
FormatHäftad
SpråkEngelska
SerieMedical Robotics and Computer Assisted Surgery: AI-enhanced, Data-driven, and Evidence-based Approaches
Antal sidor300
FörlagElsevier Science
ISBN9780443452420

Tillhör följande kategorier

Biomedicinsk teknik inom Medicin
Biokemisk teknik inom Naturvetenskap och teknik
Maskinteknik och material inom Naturvetenskap och teknik
Artificiell intelligens inom Data och it
Systemvetenskap och AI inom Data och it

Dr. Kapil Gupta earned his Ph.D. from the Indian Institute of Information Technology, Design and Manufacturing (IIITDM), Jabalpur, India. He served as an Assistant Professor in Electronics and Communication Engineering at Oriental College of Technology, Bhopal, from 2013 to 2020. He holds a B.E. with Honors in Electronics and Communication Engineering and an M.Tech. in Nano Technology. His research interests encompass signal processing in biomedical applications, time-frequency analysis, artificial intelligence, and cardiovascular systems. Dr. Gupta has published extensively in reputed journals and serves as a reviewer for IEEE and Elsevier. He has organized numerous national and international conferences and has been involved in various technical committees. Dr. Varun Bajaj is an Associate Professor in Electronics and Communication Engineering at Maulana Azad National Institute of Technology Bhopal, India, starting January 2024. Previously, he served at the Indian Institute of Information Technology, Design and Manufacturing (IIITDM) Jabalpur from 2014 to 2024, initially as an Assistant Professor and later as an Associate Professor. He earned his Ph.D. in Electrical Engineering from IIT Indore in 2014, following an M.Tech. in Microelectronics and VLSI Design in 2009, and a B.E. in Electronics and Communication Engineering in 2006. Dr. Bajaj holds various editorial roles, including Associate Editor for the IEEE Sensor Journal and Subject Editor-in-Chief for IET Electronics Letters. A Senior Member of IEEE since 2020, he actively reviews for numerous journals and has delivered over 50 expert talks. He has received multiple awards for his research and has been recognized among the top 2% of researchers globally by Stanford University from 2020 to 2023.

Part I: Fundamental of Cardiac Signals and Deep Learning1. The Rhythm of the Heart: Understanding Cardiac Modalities2. Deep Learning Essentials for Cardiac Signal Processing3. Pre-processing and Feature Extraction of Cardiac Signals4. Case Studies from Diverse Healthcare SettingsPart II: AI-Enhanced Cardiac Signal Analysis5. Deep Learning for Arrhythmia Detection and Classification6. Myocardial Ischemia and Infarction: Deep Learning-Based Diagnostics7. Hypertension Monitoring and Prediction with BCG Signal Processing8. Monitoring of Arrhythmic Fetus Using Explainable AIPart III: Integrating AI with Robotic Cardiac Surgery9. Real-Time Cardiac Signal Integration in Robotic Surgical Systems10. AI-Guided Robotic Cardiac Interventions: Precision and Safety11. Intraoperative Cardiac Monitoring and Decision Support with AI12. Post-Operative Cardiac Monitoring and Outcome Prediction13. Future Directions and Emerging Trends in Cardiac AI and Robotic Surgery14. XAI Techniques Applicable to Robotic Cardiac Systems