Biomedical Robots and Devices in Healthcare

Opportunities and Challenges for Future Applications

1st Edition - November 14, 2024
Editors: Faiz Iqbal, Pushpendra Gupta, Vidyapati Kumar, Dilip Kumar Pratihar
Language: English
Hardback ISBN:
9 7 8 - 0 - 4 4 3 - 2 2 2 0 6 - 1
eBook ISBN:
9 7 8 - 0 - 4 4 3 - 2 2 2 0 7 - 8

Biomedical Robots and Devices in Healthcare: Opportunities and Challenges for Future Applications explores recent advances and challenges involved in using these techniques in hea… Read more

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Biomedical Robots and Devices in Healthcare: Opportunities and Challenges for Future Applications explores recent advances and challenges involved in using these techniques in healthcare and biomedical engineering, offering insights and guidance to researchers, professionals, and graduate students interested in this area. The book covers key topics such as the current state-of-the-art in biomedical robotics and devices, the role of emerging technologies like artificial intelligence and machine learning, rehabilitation robotics, and the optimization techniques for optimal design and control. The book concludes by exploring the potential future developments and trends in the field of biomedical robotics and devices and their healthcare implications.

Biomedical Robots and Devices in Healthcare
Cover image
Title page
Table of Contents
Copyright
Contributors
Chapter 1 Soft robotics and computational intelligence_ Transformative technologies reshaping biomedical engineering
Abstract
Keywords
1.1 Introduction
1.2 Soft robotics: Brief introduction
1.3 Potential and ongoing applications of soft robots
1.3.1 Surgical applications for soft robots
1.3.2 Exosuits
1.3.3 Prosthetics
1.3.4 Artificial organs
1.3.5 Assistive technologies
1.4 Limitations in soft robotics
1.5 Summary
References
Chapter 2 Advancements in biomedical devices: A comprehensive review
Abstract
Keywords
2.1 Introduction
2.1.1 Background
2.1.2 Objective
2.2 Automation in biomedical devices
2.2.1 Definition and scope
2.2.2 Overview and emergence of automation
2.3 Technological advancements in automation—Cyber physical systems, robots, and integration with digital platforms, and their advantages
2.3.1 Implantable devices
2.3.2 Wearable devices
2.3.3 Equipment for diagnosis and treatment
2.4 Case studies and applications
2.5 Regulatory and safety considerations
2.5.1 Compliance with medical device regulations
2.5.2 Standardization and validation
2.6 Drawbacks and challenges
2.6.1 Initial cost and investment
2.6.2 Specialized training and workforce adaptation
2.6.3 Technical failures and malfunctions
2.6.4 Cyber security and cyber-attacks
2.7 Conclusion
References
Chapter 3 Mathematics in biomedical robotics and devices and its role in healthcare delivery
Abstract
Keywords
3.1 Introduction
3.2 Mathematical foundations of robotics and biomedical robotics
3.2.1 Motion control
3.2.2 Force control
3.2.3 Mathematics in biomedical robotics
3.3 Applications of mathematics in biomedical robotics and devices
3.3.1 Mathematics in surgical robotics
3.3.2 Mathematics in rehabilitation robotics
3.3.3 Mathematics in medical robotics for diagnosis and monitoring
3.4 Future perspectives and limitations
3.5 Conclusion
References
Chapter 4 Advancing ankle–foot orthosis design through biomechanics, robotics, and additive manufacturing: A review
Abstract
Keywords
4.1 Introduction
4.2 Biomechanics of biological ankle and foot
4.3 Design of Orthoses for lower limb
4.3.1 Ankle–foot orthoses
4.3.2 Knee–ankle–foot orthosis
4.3.3 Hip–knee–ankle–foot orthosis
4.3.4 Advancements in mobility-enhancing orthotic systems
4.4 Advances in orthotic manufacturing
4.4.1 3D anatomical data acquisition technologies in orthotic device design
4.4.2 Rapid prototyping technologies transforming orthotic device manufacturing
4.5 Technical challenges
4.5.1 HRI challenges
4.5.2 Sensors and controllers challenges
4.5.3 Structural design challenges
4.5.4 Actuators and batteries challenges
4.5.5 Materials and safety challenges
4.5.6 Ergonomics challenges
4.6 Summary
4.7 Future directions
References
Chapter 5 Application of multibistatic frequency-domain measurements for enhanced medical sensing and imaging
Abstract
Keywords
5.1 Introduction
5.2 Advantages of integrating multibistatic antennas in the development of detecting hemorrhagic brain strokes using a scanner
5.2.1 Advancement of a microwave cerebral imaging trial product for the detection of stroke
5.2.2 HP in imaging: Algorithms and procedures
5.2.3 Design (methodology)
5.2.4 Description of signal preprocessing techniques
5.3 Experimental validation
5.3.1 Imaging results
5.4 Discussion
References
Chapter 6 Sleep posture analysis: state-of-the-art and opportunities of wearable technologies from clinical, sensing and intelligent perception perspectives
Abstract
Keywords
6.1 Introduction
6.2 Health complications: A sleep behavior perspective
6.2.1 The musculoskeletal system: A biomarker of and risk factor for sleep-related pathologies
6.2.2 Clinical assessment of sleep disorders
6.2.3 Management and treatment practices for sleep disorders
6.2.4 Clinical needs and challenges in sleep posture analysis
6.3 Sleep posture analysis: Current state of research
6.3.1 Human sleep posture sensing technologies
6.3.2 Algorithmic trends in wearable sensor-based sleep posture analysis
6.4 Monitoring sleep postures using wearable sensors
6.4.1 The standard four sleep postures
6.4.2 Beyond the standard four sleep postures
6.5 Temporal analysis of in-bed postural activity using wearable sensors
6.6 Conclusion
References
Chapter 7 Comparative evaluation of deep learning techniques for multistage Alzheimer's prediction from magnetic resonance images
Abstract
Keywords
7.1 Introduction
7.2 Methodology
7.2.1 Data set description
7.2.2 Data augmentation
7.2.3 Machine learning models
7.2.4 Evaluation metrics
7.3 Results and discussion
7.4 Conclusion
References
Chapter 8 Machine learning brain activation topography for individual skill classification: Need for leave-one-subject-out (LOSO) cross-validation
Abstract
Keywords
8.1 Background
8.2 Methods
8.2.1 Data collection: Electroencephalography
8.2.2 Data preprocessing
8.2.3 Processing for topography-preserving 3D-CNN
8.3 Results
8.3.1 Fivefold cross-validation results
8.3.2 Leave-one-subject-out cross-validation results
8.4 Discussion
References
Chapter 9 Transfer learning-based disease prognosis in Biomedicine 4.0: Challenges and opportunities
Abstract
Keywords
9.1 Introduction
9.2 Challenges in disease prognosis
9.2.1 Limited data availability
9.2.2 Disease complexity and variability
9.2.3 Lack of standardization in prognostic models
9.3 AI/ML in disease prognosis
9.3.1 Efficient analysis of medical data
9.3.2 Forecasting disease outcomes
9.4 Transfer learning for disease prognosis
9.4.1 Understanding transfer learning
9.4.2 Advantages over traditional ML methods
9.4.3 Eliminating the need to build models from scratch
9.5 Enhancing disease prognosis models
9.5.1 Enhanced accuracy in prognostic models
9.5.2 Superior results than other ML methods
9.5.3 Improved treatment outcomes
9.5.4 Reduced healthcare costs
9.6 Conclusion
References
Chapter 10 Voice and chatbot: A hybrid framework using XAI for improving mental health
Abstract
Keywords
Declaration of data availability
Declaration of conflicts of interest statement
10.1 Introduction
10.2 Problem statement
10.3 Literature survey
10.4 Preliminaries
10.4.1 RNN
10.4.2 CNN
10.4.3 Integrated stacked ensemble
10.4.4 NLP
10.4.5 Voice engines
10.4.6 XAI
10.5 Dataset description
10.6 Proposed method
10.7 Result and analysis
10.7.1 Experimental setup
10.7.2 Time complexity analysis
10.7.3 Optimizer analysis
10.7.4 Result
10.7.5 Comparison
10.7.6 Benefits
10.8 Limitation and conclusion
References
Further Reading
Chapter 11 Wearable sensors: The pathway to applications of on-body electronics
Abstract
Keywords
11.1 RFID wearables: Design consideration
11.1.1 RFID basic principles of design
11.1.2 Human tissue considerations for tag design
11.1.3 Ultra-lower power live streaming through UHF RFID
11.2 RFID wearable sensor fabrication and applications
11.2.1 Wearable sensor stretchability
11.2.2 Wearable sensors and variable human tissue dielectrics
11.3 Wearable sensor mass fabrication
11.4 Conclusion
References
Index

Faiz Iqbal

Dr. Faiz Iqbal received his B.Tech in Mechanical and Automation Engineering in 2011, M.Tech in Mechatronics Engineering in 2013, and PhD in Manufacturing Automation in 2019 from India. He is currently a Lecturer in the School of Engineering at the University of Lincoln in the UK. He has published several research papers and holds four patents, and has received multiple awards for his contributions in research and innovation. His research interests include Mechatronics, Industrial Automation, Smart Manufacturing, Fluidic logic/Soft Robotics, and Industry 4.0. He successfully delivered a COVID-19 project and was awarded the COVID-19 Engineering Medal by the School of Engineering at the University of Edinburgh.

Affiliations and expertise

Lecturer of Mechanical Engineering, School of Engineering, University of Lincoln, UK

Pushpendra Gupta

Pushpendra Gupta is pursuing a Ph.D. in Mechanical Engineering at the Indian Institute of Technology Kharagpur. He received his M.Tech in Production Engineering (Gold Medalist) in 2015 and B.Tech in Mechanical and Automation Engineering in 2011 from India. He has also worked as a faculty member for 2.5 years at MITRC Alwar before joining IIT Kharagpur. His research interests include humanoid robots, soft computing, evolutionary optimization, and their application in multi-criterion optimization, modeling, and machine learning.

Affiliations and expertise

Research Scholar, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India

Vidyapati Kumar

Vidyapati Kumar is a Ph.D. candidate in the Department of Mechanical Engineering at the Indian Institute of Technology, Kharagpur. He completed his Master’s in Engineering in Production Engineering in 2018 and Bachelor's in Technology in Mechanical Engineering in 2016. Before starting his Ph.D., he worked for 1.7 years as a project assistant at the CSIR-Central Institute of Mining and Fuel Research. He has published research in SCI/Scopus indexed journals and conference proceedings, and has obtained both an Australian and Indian patent for his innovative research. His research area includes Rehabilitation Robotics, Biomedical devices, and the application of soft computing tools in solving optimization and decision-making problems.

Affiliations and expertise

Research Scholar, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India

Dilip Kumar Pratihar

Dr. Dilip Kumar Pratihar is a Professor (HAG Scale) in the Mechanical Engineering Department at IIT Kharagpur, India and former Professor-in-charge of the Centre for Excellence in Robotics. He received his BE (Hons.), M.Tech. in Mechanical Engineering, and Ph.D. from various Indian institutions, as well as post-doctoral study at universities in Japan and Germany. He has received multiple awards, including the University Gold Medal, INSA Teachers' Award, Technologist of the Year Award, and Distinguished Alumnus Award. He has made significant contributions to Artificial Intelligence (AI) and its applications in fields such as Industrial Automation, Robotics, Health Care, and Education Technology. He has published several books and hundreds of publications in reputed journals, conferences, and book chapters. He is a regular reviewer for several international journals and a member of the editorial board of several international journals. He has filed patents and received 1 copyright. He is a Fellow of Institution of Engineers, a Senior Member of IEEE, a Member of ASME, and a Member of AMM.

Affiliations and expertise

Professor, Mechanical Engineering Department, Indian Institute of Technology Kharagpur, India

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Physical Sciences & Engineering

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Biomedical Robots and Devices in Healthcare

Opportunities and Challenges for Future Applications

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Save 50% on book bundles

Institutional subscription on ScienceDirect

Faiz Iqbal

Pushpendra Gupta

Vidyapati Kumar

Dilip Kumar Pratihar