Deep Learning For Cardiac Signal Analysis In Robotic Applications
Language: English
Published by Academic Press, 2026
- Softcover
- Used

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- Title
- Deep Learning For Cardiac Signal Analysis In Robotic Applications
- Publisher
- Academic Press
- Publication year
- 2026
- Condition
- As New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 0443452423
- ISBN 13
- 9780443452420
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. 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.
- 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
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About the Author
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.
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