Control Applications for Biomedical Engineering Systems
- 1st Edition - January 22, 2020
- Latest edition
- Editor: Ahmad Taher Azar
- Language: English
Control Applications for Biomedical Engineering Systems presents different control engineering and modeling applications in the biomedical field. It is intended for senior un… Read more
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Description
Description
Control Applications for Biomedical Engineering Systems presents different control engineering and modeling applications in the biomedical field. It is intended for senior undergraduate or graduate students in both control engineering and biomedical engineering programs. For control engineering students, it presents the application of various techniques already learned in theoretical lectures in the biomedical arena. For biomedical engineering students, it presents solutions to various problems in the field using methods commonly used by control engineers.
Key features
Key features
- Points out theoretical and practical issues to biomedical control systems
- Brings together solutions developed under different settings with specific attention to the validation of these tools in biomedical settings using real-life datasets and experiments
- Presents significant case studies on devices and applications
Readership
Readership
Table of contents
Table of contents
1. Neuro-fuzzy inverse optimal control incorporating a multistep predictor as applied to T1DM patients
2. Blood glucose regulation in patients with type 1 diabetes by means of output-feedback sliding mode control
3. Impulsive MPC schemes for biomedical processes: Application to type 1 diabetes
4. Robust control applications in biomedical engineering: Control of depth of hypnosis
5. Robust control strategy for HBV treatment: Considering parametric and nonparametric uncertainties
6. A closed loop robust control system for electrosurgical generators
7. Application of a T-S unknown input observer for studying sitting control for people living with spinal cord injury
8. Epidemic modeling and control of HIV/AIDS dynamics in populations under external interactions: A worldwide challenge
9. Reinforcement learning-based control of drug dosing with applications to anesthesia and cancer therapy
10. Control strategies in general anesthesia administration
11. Computational modeling of the control mechanisms involved in the respiratory system
12. Intelligent decision support for lung ventilation
13. Customized modeling and optimal control of superovulation stage in in vitro fertilization (IVF) treatment
14. Models based on cellular automata for the analysis of biomedical systems
Product details
Product details
- Edition: 1
- Latest edition
- Published: January 22, 2020
- Language: English
About the editor
About the editor
AT
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.