Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices
- 1st Edition - September 4, 2025
- Editors: S. Sountharrajan, M. Karthiga, Balamurugan Balusamy, Ali Kashif Bashir
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 3 3 5 1 4 - 3
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 3 3 5 1 5 - 0
Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices delves into the innovative convergence of mathematical frameworks and biomedical engineering. The book b… Read more
Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices delves into the innovative convergence of mathematical frameworks and biomedical engineering. The book begins by exploring how advanced mathematical modelling underpins the development and optimization of robotic systems and wearable technologies tailored for medical applications. With a strong emphasis on practical implementation, it serves as a bridge between theoretical concepts and real-world engineering challenges in the healthcare sector. Readers will gain insights into the transformative role of mathematical techniques that drive precision, functionality, and human-centric design in cutting-edge medical technologies.
The book also covers interdisciplinary applications, integrating domains like biomechanics, sensor technology, and data analytics. By highlighting case studies and real-world scenarios, it showcases practical advancements in wearable devices that monitor health metrics and robotic systems that assist in surgical procedures.
The book also covers interdisciplinary applications, integrating domains like biomechanics, sensor technology, and data analytics. By highlighting case studies and real-world scenarios, it showcases practical advancements in wearable devices that monitor health metrics and robotic systems that assist in surgical procedures.
- Examines the role of applied mathematical modeling in the design, analysis, and optimization of biomedical robots and wearable devices
- Provides an insightful exploration of cutting-edge developments in robotics and wearable devices
- Bridges the gap between the areas of mathematics, engineering, and healthcare
Researchers and academicians, advanced undergraduate and graduate students pursuing degrees in biomedical engineering, mathematics, or related disciplines
1. Introduction to Biomedical Robotics and Wearable Devices in Healthcare
2. Mathematical Modelling in Healthcare Engineering
3. Mathematical Foundations and Computational Techniques for Robotic Motion: A Unified Approach
4. Advanced Bio signal Processing and Emotion Recognition Through Artificial Intelligence
5. Optimization Algorithms for Design and Control
6. Kinematics and Dynamics of Surgical Robots
7. Sensor Fusion and Data Processing for Robot Control
8. Motion Planning and Trajectory Optimization for Robots
9. Safety and Stability Analysis of Robot Systems
10. Rehabilitation Robotics: Transforming Motor Recovery and Enhancing Patient-Centered Therapies
11. Biosignal Acquisition and Processing for Wearable Sensors
12. Principal Components with Folds For Feature Extraction And Anomaly Detection in Physiological Data Using Deep Neural Network
13. AI-enabled decision-making and predictive analytics applications
14. A Novel Ensemble Learning Approach for Leukemia Prediction using Hybrid Machine Learning Techniques
15. Ethical Considerations of Biomedical Robots and Wearable Devices
2. Mathematical Modelling in Healthcare Engineering
3. Mathematical Foundations and Computational Techniques for Robotic Motion: A Unified Approach
4. Advanced Bio signal Processing and Emotion Recognition Through Artificial Intelligence
5. Optimization Algorithms for Design and Control
6. Kinematics and Dynamics of Surgical Robots
7. Sensor Fusion and Data Processing for Robot Control
8. Motion Planning and Trajectory Optimization for Robots
9. Safety and Stability Analysis of Robot Systems
10. Rehabilitation Robotics: Transforming Motor Recovery and Enhancing Patient-Centered Therapies
11. Biosignal Acquisition and Processing for Wearable Sensors
12. Principal Components with Folds For Feature Extraction And Anomaly Detection in Physiological Data Using Deep Neural Network
13. AI-enabled decision-making and predictive analytics applications
14. A Novel Ensemble Learning Approach for Leukemia Prediction using Hybrid Machine Learning Techniques
15. Ethical Considerations of Biomedical Robots and Wearable Devices
- Edition: 1
- Published: September 4, 2025
- Language: English
SS
S. Sountharrajan
S. Sountharrajan completed his PhD from Anna University in Information and Communication Engineering in the year 2017 and is currently working as Associate Professor in the School of Computing (SOC) at Amrita Vishwa Vidyapeetham, Chennai Campus. He is Program Head, B. Tech Computer Science and Engineering. He was sanctioned an amount of Rs. 38,00,000 from the funding agencies like DST, AICTE and ICMR. He has also published papers in 10 International / 6 National Conferences. He was published 35 International journals including 50 Scopus index and 12 SCI. He has been certified from reputed companies of India like the IBM, DELL EMC Corporation. He has delivered 33 Guest Lectures in reputed universities and Institutions in India. He has worked on Big Data, cloud computing show the importance of cloud deployed applications.
Affiliations and expertise
Department of Computer Science and Engineering , School of Computing, Amrita Vishwa Vidyapeetham, Chennai, IndiaMK
M. Karthiga
Dr. M. Karthiga is currently working as an Associate Professor in the Department of Computer science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, India. She holds more than 11 years of professional experience. She is presently working in Machine Learning and Deep Learning Projects. She is involved in Data Science Lab. She published 28 articles in leading National and International journals. She is a reviewer in reputed journals like Knowledge based Systems, Signals, Image and Video Processing, Future Generation Computer Systems, MDPI journals and etc., She published more than 11 book chapters in leading books of Elsevier and Springer. She is an active researcher in the field of Machine learning and Data Analytics. Also, her research interest includes Data mining, Image Mining, Internet of Things, Artificial Intelligence and Deep Learning. She has received 5 patent grants and filed more than 13 National level Patents under Machine Learning and Internet of Things. She is a Lifetime member of ISTE professional society.
Affiliations and expertise
Department of Computer Science and Engineering, Bannari Amman Institute of Technology, Sathyamangalam, IndiaBB
Balamurugan Balusamy
Balamurugan Balusamy is Associate Dean Student in Shiv Nadar University, Delhi-NCR. Prior to this assignment he was Professor, School of Computing Sciences & Engineering and Director International Relations at Galgotias University, Greater Noida, India. His contributions focus on Engineering Education, Block chain and Data Sciences. His Academic degrees and twelve years of experience working as a faculty in a global University like VIT University, Vellore has made him more receptive and prominent in his domain. He does have 200 plus high impact factor papers in Springer, Elsevier and IEEE. He has done more than 80 Edited and authored books and collaborated with eminent professors across the world from top QS ranked university. Prof. Balamurugan Balusamy has served up to the position of Associate Professor in his stint of 12 years of experience with VIT University, Vellore. He had completed his Bachelors, Masters and PhD Degrees from Top premier institutions from India. His passion is teaching and adapts different design thinking principles while delivering his lectures. He has published 80+ books on various technologies and visited 15 plus countries for his technical course. He has several top-notch conferences in his resume and has published over 200 of quality journal, conference and book chapters combined. He serves in the advisory committee for several start-ups and forums and does consultancy work for industry on Industrial IOT. He has given over 195 talks in various events and symposium.
Affiliations and expertise
Shiv Nadar University, Delhi-NCR Campus, IndiaAB
Ali Kashif Bashir
Ali Kashif Bashir holds the position of Professor of Computer Networks and Cybersecurity at the Manchester Metropolitan University in the United Kingdom. Additionally, he serves as the leader of the Future Networks lab. Throughout his career, Ali has presented more than 45 keynote speeches at international conferences, produced over 300 research articles, and successfully overseen multimillion-dollar projects worldwide. His students have won best paper awards, best PhD thesis awards, and several other recognitions. His research interests include internet of things/cyber physical systems, smart infrastructures, cybersecurity, and AI algorithms to solve interdisciplinary problems of networks and security. Ali is member of Council of Professors and Heads of Computing (CPHC), UK; an expert reviewer of EPSRC, UK, Irish Research Council, Ireland, National Sciences and Engineering Research Council (NSERC), Canada, MITACS, Accelerate, Canada, Qatar National Research Fund (QNRF), and Commonwealth, UK. He enjoys 7 honorary and adjunct professor positions across the globe. He was listed as IEEE Featured Author in 2021, highly cited 2% researchers by Stanford University 2021 and 2022, shortlisted for Clarivate Highly Cited award 2023. He is AE of over 10 international ISI indexed journals including two IEEE Transactions, and Scientific Reports, Nature, and EIC of IEEE Technology, Policy and Ethics, and Journal of Autonomous Intelligence.
Affiliations and expertise
Professor, Computer Networks and Cybersecurity, Manchester Metropolitan University, Manchester, UKRead Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices on ScienceDirect