Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications
- 1st Edition - November 30, 2019
- Latest edition
- Editor: Ahmad Taher Azar
- Language: English
Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications delivers essential and advanced bioengineering information on the application of control a… Read more
Control Systems Design of Bio-Robotics and Bio-Mechatronics with Advanced Applications delivers essential and advanced bioengineering information on the application of control and robotics technologies in the life sciences. Judging by what we have witnessed so far, this exciting field of control systems and robotics in bioengineering is likely to produce revolutionary breakthroughs over the next decade. While this book is intended for senior undergraduate or graduate students in both control engineering and biomedical engineering programs, it will also appeal to medical researchers and practitioners who want to enhance their quantitative understanding of physiological processes.
- Focuses on the engineering and scientific principles underlying the extraordinary performance of biomedical robotics and bio-mechatronics
- Demonstrates the application of principles for designing corresponding algorithms
- Presents the latest innovative approaches to medical diagnostics and procedures, as well as clinical rehabilitation from the point-of-view of dynamic modeling, system analysis and control
1. Human-Robot Interaction for Rehabilitation Scenarios
2. State Observation and Feedback Control in Robotic Systems for Surgery and Therapy
3. Robin Heart Surgical Robot: Description and future challenges
4. Real-Time Object Detection and Manipulation Using Biomemetic Musculoskeletal Soft Robotic Grasper Addressing Robotic Fan Handling Challenge
5. Formal Verification of Robotic Cell Injection Systems
6. Identifying Vessel Branching from Fluid Stresses on Microscopic Robots
7. Navigation and Control of Endovascular Helical Swimming Microrobot Using Dynamic Programing and Adaptive Sliding Mode Strategy
8. Robotics in endoscopic transnasal skull base surgery: literature review and personal experience
9. Strategies for mimicking the movements of an upper extremity using superficial electromyographic signals
10. Automated Transportation of Micro-particles in vivo
11. Medical Nanorobots: Design, applications and future challenges
12. Impedance Control Applications in Therapeutic Exercise Robots
13. Architecture and Application of Nanorobots in Medicine
- Edition: 1
- Latest edition
- Published: November 30, 2019
- Language: English
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Ahmad Taher Azar
Prof. Ahmad Azar is a full Professor at Prince Sultan University, Riyadh, Kingdom Saudi Arabia. He is the leader of Automated Systems and Computing Lab (ASCL), Prince Sultan University, Saudi Arabia.
Prof. Azar is the Editor in Chief of the International Journal of Intelligent Engineering Informatics (IJIEI), Inderscience Publishers, Olney, UK. He is also the Editor in Chief of International Journal of Service Science, Management, Engineering, and Technology (IJSSMET) and International Journal of Sociotechnology and Knowledge Development (IJSKD) published by IGI Global, USA. From 2013 to 2017, Prof. Azar was an associate editor of ISA Transactions, Elsevier.
He is currently an editor for IEEE Transactions on Fuzzy Systems, IEEE Systems Journal, IEEE Transactions on Neural Networks and Learning Systems, Springer's Human-centric Computing and Information Sciences.
Prof. Azar specializes in artificial intelligence (AI), robotics, machine learning, control theory and applications, computational intelligence, reinforcement learning, and dynamic system modeling. He has published or co-published over 550 research papers, book chapters, and conference proceedings in prestigious peer-reviewed journals.
Dr. Ahmad Azar has received several awards, including the Benha University Prize for Scientific Excellence (2015, 2016, 2017, and 2018) and the Benha University Highest Citation Award (2015, 2016, 2017, and 2018).
In June 2018, he was awarded the Egyptian State Encouragement Award in Engineering Sciences by the Ministry of Higher Education and Scientific Research. In August 2018, he was elected as a senior member of the International Rough Set Society (IRSS).
Prof. Azar was named one of the top computer scientists in Saudi Arabia by Research.com since December 2019.
He was awarded the Egyptian President's Distinguished Egyptian Order of the First Class in February 2020.
In October 2020, Prof. Azar received Abdul Hameed Shoman Arab Researchers Award in Machine Learning and Big Data Analytics.
From October 2020 to September 2023, Prof. Azar was recognized as a Distinguished researcher at Prince Sultan University, Riyadh, Saudi Arabia.
In November 2020, October 2021, October 2022, October 2023, September 2024, and September 2025 Prof. Azar was named one of the top 2% of scientists in the world in Artificial Intelligence by Stanford University, based on single-year impact and career-long impact. These rankings were published by Stanford University in the PLOS journal and were based on the SCOPUS database.
Prof. Ahmad Azar has been recognized as one of the top ten researchers at Prince Sultan University, based on his Scopus H-index. He has also received a university award for being among his top publication of research.
Prof. Azar has received Prince Sultan University’s Research Excellence Award. He is also the recipient of the university’s Highest Impact Researcher Award, based on his H-index. Additionally, he has earned a PSU research award for having publications ranked among the top five by impact factor.
Prof. Ahmad Azar is the Vice Chair of the International Federation of Automatic Control (IFAC) Technical Committee of Control Design, Vice chair of IFAC Technical committee 4.3 Robotics, Vice chair of IFAC Technical committee 9.3 “Control for Smart Cities”. He is a technical Committee Member of Data Mining and Big Data Analytics of IEEE Computational Intelligence Society (CIS), IFAC Technical committee Member TC 2.2. Linear Control Systems, IFAC Technical committee Member TC 1.2. Adaptive and Learning Systems.