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Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy

  • Chirag Vashisht , Rohit Kaushik and Eva Kaushik
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Digital Transformation in Healthcare 5.0
This chapter is in the book Digital Transformation in Healthcare 5.0

Abstract

Medical cyber-physical systems (MCPS), which seamlessly combine medical equipment, information systems, and physical settings, have been developed as a result of the rapid technological advancement that has transformed healthcare. To enhance patient care, streamline clinical workflows, and optimize resource allocation, MCPS uses the power of connection, data analytics, and automation. This chapter provides a thorough analysis of the developments, difficulties, and potential prospects in the MCPS sector. A network of detecting and acting devices that are wirelessly connected is collectively known by the name “wireless body area network” (WBAN). WBANs called cyber-physical systems are employed in the storage and distribution of biometric data. The main goal of WBANs, which recommends using biomechanics readings as an authentication method, is to safeguard user security and privacy. The many approaches (such as epidermal impedance, gait, head/arm motions, ECG, and EEG) have been the subject of several researches. This chapter analyzes and evaluates the effectiveness, viability, and cost of the most widely used biometric authentication techniques. This chapter provides a thorough analysis of the developments, difficulties, and potential future prospects in the MCPS sector. It intends to motivate academics, practitioners, and policymakers to actively participate in the development and adoption of MCPS, thereby enhancing patient outcomes and healthcare effectiveness. It does this by addressing the current status of MCPS research and identifying future paths.

Abstract

Medical cyber-physical systems (MCPS), which seamlessly combine medical equipment, information systems, and physical settings, have been developed as a result of the rapid technological advancement that has transformed healthcare. To enhance patient care, streamline clinical workflows, and optimize resource allocation, MCPS uses the power of connection, data analytics, and automation. This chapter provides a thorough analysis of the developments, difficulties, and potential prospects in the MCPS sector. A network of detecting and acting devices that are wirelessly connected is collectively known by the name “wireless body area network” (WBAN). WBANs called cyber-physical systems are employed in the storage and distribution of biometric data. The main goal of WBANs, which recommends using biomechanics readings as an authentication method, is to safeguard user security and privacy. The many approaches (such as epidermal impedance, gait, head/arm motions, ECG, and EEG) have been the subject of several researches. This chapter analyzes and evaluates the effectiveness, viability, and cost of the most widely used biometric authentication techniques. This chapter provides a thorough analysis of the developments, difficulties, and potential future prospects in the MCPS sector. It intends to motivate academics, practitioners, and policymakers to actively participate in the development and adoption of MCPS, thereby enhancing patient outcomes and healthcare effectiveness. It does this by addressing the current status of MCPS research and identifying future paths.

Chapters in this book

  1. Frontmatter I
  2. About the book V
  3. Preface VII
  4. Foreword IX
  5. Contents XI
  6. List of contributors XV
  7. Chapter 1 The impact of blockchain technology on the healthcare system 1
  8. Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
  9. Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
  10. Chapter 4 Role of artificial intelligence in disease diagnosis 89
  11. Chapter 5 Machine learning for twinning the human body 105
  12. Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
  13. Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
  14. Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
  15. Chapter 9 Nanorobots in healthcare 209
  16. Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
  17. Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
  18. Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
  19. Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
  20. Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
  21. Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
  22. Index 375
https://doi.org/10.1515/9783111398549-010

Chapters in this book

  1. Frontmatter I
  2. About the book V
  3. Preface VII
  4. Foreword IX
  5. Contents XI
  6. List of contributors XV
  7. Chapter 1 The impact of blockchain technology on the healthcare system 1
  8. Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
  9. Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
  10. Chapter 4 Role of artificial intelligence in disease diagnosis 89
  11. Chapter 5 Machine learning for twinning the human body 105
  12. Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
  13. Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
  14. Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
  15. Chapter 9 Nanorobots in healthcare 209
  16. Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
  17. Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
  18. Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
  19. Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
  20. Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
  21. Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
  22. Index 375
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