Skip to main content
SpringerLink
Log in

Health Monitoring Using Wearable Technologies and Cognitive Radio for IoT

  • Chapter
  • First Online:
Cognitive Radio, Mobile Communications and Wireless Networks

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

Abstract

This book chapter presents technological aspects regarding cognitive radio and communication technology for IoT (Internet of Things). In addition, health monitoring by cognitive radio for IoT is a technological challenge for communication because it involves the connection of electronic devices used for medical monitoring. For medical monitoring in the IoT context, it should consider the risks of electromagnetic interference between medical devices and aggregators (4G/5G cellular phone). The cellular phones emit EM radiation during the ringing, sending/receiving data and standby phase. In hospital are used for monitoring sophisticated devices, the inference can occur due to the medical staff and patients who useb cellular phone for personal commutation. Cognitive radio can solve the inference problem for electronic device networks connected by WLAN, through radio links. The IoT requirements, such as cognitive radio and 5G, are integrated parts of the Future Internet. For IoT cognitive radio the requirement is to reduce the channel inference with primary licensed users and alternative spectrum management (e.g. each unlicensed user will sense and access the spectrum when the spectrum is unoccupied by licensed users) to reduce the EMI. The scientific literature shows that there have been numerous concerns to model the cognitive radio using various algorithms, such as fuzzy logic, neural networks, hidden Markov model, genetic algorithms or classification algorithms. In our research we used cognitive radio modelling for medical devices by several algorithms, such as neural network and genetic algorithms.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Amato A, Coronato A (2017) An IoT-aware architecture for smart healthcare coaching systems. IEEE 31st International Conference on Advanced Information Networking and Applications (AINA), pp. 1027–1034. Taipei, 2017

    Google Scholar 

  2. Asthana S et al (2017) A Recommendation system for proactive health monitoring using IoT and wearable technologies. IEEE International Conference on AI & Mobile Services (AIMS), pp. 14–21, Honolulu, 2017

    Google Scholar 

  3. Cao H et al (2009) Enabling technologies for wireless body area networks: a survey and outlook. IEEE Commun Mag 47(12):84

    Article  Google Scholar 

  4. Amendola S et al (2014) RFID technology for IoT – based personal healthcare in smart spaces. IEEE Internet Things J 1(2):144–152

    Article  Google Scholar 

  5. Coustasse A et al (2015) Benefits and barriers of implementation and utilization of radio- frequency identification (RFID) systems in transfusion medicine. Perspect Heath Inf Manag 1d:12

    Google Scholar 

  6. Chávez-Santiago R et al. (2014) Dual-band cognitive radio for wearable sensors in hospitals. 8th International Symposium on Medical Information and Communication Technology (ISMICT), pp. 1–52, Firenze, 2014

    Google Scholar 

  7. Arase Y et al (2011) Mobile search assistance from HCI aspect. IJSSC 1(1):18–29. https://doi.org/10.1504/IJSSC.2011.039104

    Article  Google Scholar 

  8. Sabzevar AP, Sousa JP (2011) Authentication, authorisation and auditing for ubiquitous computing: a survey and vision. IJSSC 1(1):59–67. https://doi.org/10.1504/IJSSC.2011.039107

    Article  Google Scholar 

  9. Suciu G et al (2015) Big data, internet of things and cloud convergence – an architecture for secure E-health applications. J Med Syst 39(11):1–8

    Article  Google Scholar 

  10. Gao W, Emaminejad S (2016) Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis. Nature 529(7587):509–514

    Article  Google Scholar 

  11. Anliker U et al (2004) A wearable multiparameter medical monitoring and alert system. IEEE Trans Inf Technol Biomed 8(4):415–427

    Article  Google Scholar 

  12. Mayagoitia RE et al (2002) Accelerometer and rate gyroscope measurement of kinematics: an inexpensive alternative to optical motion analysis systems. J Biomech 35(4):537–542

    Article  Google Scholar 

  13. Baker SB et al (2017) Internet of things for smart healthcare: technologies, challenges, and opportunities. IEEE Access 5:26521–26544

    Article  Google Scholar 

  14. van der Togt R et al (2008) Electromagnetic interference from radio frequency identification inducing potentially hazardous incidents in critical care medical equipment. JAMA 299(24):2884–2890

    Article  Google Scholar 

  15. Hassanalieragh M. et al. (2015) Health monitoring and management using internet-of-things (IoT) sensing with cloud-based processing: opportunities and challenges. IEEE International Conference on Services Computing, pp. 285–292, New York, 2015

    Google Scholar 

  16. Bui N, Zorzi M (2011) Health care applications: a solution based on the internet of things. Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, p. 131

    Google Scholar 

  17. Liu ML et al (2012) Internet of things-based electrocardiogram monitoring system. Chinese Patent 102(764):118

    Google Scholar 

  18. Islam SMR et al (2015) The internet of things for health care: a comprehensive survey. IEEE Access 3:678–708

    Article  Google Scholar 

  19. Amjad M et al (2018) Wireless multimedia cognitive radio networks: a comprehensive survey. IEEE Commun Surv Tutorials 1(1):99

    Google Scholar 

  20. Hassan MR et al (2017) Exclusive use Spectrum access trading models in cognitive radio networks: a survey. IEEE Commun Surv Tutorials 19(4):2192–2231

    Article  Google Scholar 

  21. Elderini T et al (2017) Channel quality estimation metrics in cognitive radio networks: a survey. IET Commun 11(8):1173–1179

    Article  Google Scholar 

  22. Khan AA et al (2017) Cognitive-radio-based internet of things: applications, architectures, Spectrum related functionalities, and future research directions. IEEE Wirel Commun 24(3):17–25

    Article  Google Scholar 

  23. Amjad M et al (2017) Full-duplex communication in cognitive radio networks: a survey. IEEE Commun Surv Tutorials 19(4):2158–2191

    Article  Google Scholar 

  24. Shah MA et al. (2013) Cognitive radio networks for internet of things: applications, challenges and future. 19th International Conference on Automation and Computing, pp. 1–6, London

    Google Scholar 

  25. Setiawan D et al (2009) Interference analysis of guard band and geographical separation between DVB-T and EUTRA in digital dividend UHF band. International Conference on Instrumentation, Communication, Information Technology, and Biomedical Engineering, pp. 1–6

    Google Scholar 

  26. Novák V et al (1999) Mathematical principles of fuzzy logic. Springer Science & Business Media, 0-7923-8595-0

    Google Scholar 

  27. “Fuzzy Logic”. Stanford Encyclopedia of Philosophy. Bryant University. 2006-07-23. Retrieved 2008-09-30

    Google Scholar 

  28. Lee CC (1990) Fuzzy logic control systems: Fuzzy logic controller. IEEE Trans Syst Man Cybern 20(2):404–435

    Article  MathSciNet  Google Scholar 

  29. Phuong NH, Kreinovich V (2001) Fuzzy logic and its applications in medicine. Int J Med Inform 62(2–3):165–173

    Article  Google Scholar 

  30. Kaestle S (2001), Quality indicator for measurement signals, in particular, for medical measurement signals such as those used in measuring oxygen saturation, EP1196862A1, US6725074, WO2000077659A1

    Google Scholar 

  31. Ciocoiu IB (2001) Reţele neurale artificiale. Cantes Publishing, Iasi, Romania

    Google Scholar 

  32. Burse K et al (2011) Convergence analysis of complex valued multiplicative neural network for various activation functions. IEEE International Conference on Computational Intelligence and Communication System (CICN 2011), pp. 279–282

    Google Scholar 

  33. Poli R et al (2008) A field guide to genetic programming. Lulu Enterprises, UK

    Google Scholar 

  34. Shah S, Kusiak A (2007) Cancer gene search with data-mining and genetic algorithms. Comput Biol Med 37(2):251–261

    Article  Google Scholar 

  35. Handels H et al (1999) Feature selection for optimized skin tumor recognition using genetic algorithms. Artif Intell Med 16(3):283–297

    Article  Google Scholar 

  36. Rawata P (2016) Cognitive radio for M2M and internet of things: a survey. Comput Commun 94:1–29

    Article  Google Scholar 

  37. Cisco connections counter. https://blogs.cisco.com/news/cisco-connections-counter

  38. Nekovee M (2009) A survey of cognitive radio access to TV white spaces. Ultra Modern Telecommunications & Workshops, ICUMT’09. International Conference IEEE, pp. 1–8

    Google Scholar 

  39. Internet of Things (2015) IERC Position Paper on Standardization for IoT technologies published by IoT European Research Cluster (IERC)

    Google Scholar 

  40. RERUM, Reliable, Resilient and secure IoT for smart city applications. Available at: https://ict-rerum.eu

  41. Pantazis NA (2013) Energy-efficient routing protocols in wireless sensor networks: a survey. IEEE Commun Surv Tutorials 15(2):551–591

    Article  Google Scholar 

  42. Umer T et al. (2016) Hybrid rapid response routing approach for delay-sensitive data in hospital body area sensor network. Proceedings of the 7th International Conference on Computing Communication and Networking Technologies, p. 3

    Google Scholar 

  43. Amjad M et al (2016a) TinyOS-new trends, comparative views, and supported sensing applications: a review. IEEE Sensors J 16(9):2865–2889

    Article  Google Scholar 

  44. Amjad M (2017) QoS-aware and heterogeneously clustered routing protocol for wireless sensor networks. IEEE Access 5:10250–10262

    Article  Google Scholar 

  45. Akhtar F, Rehmani MH (2015) Energy replenishment using renewable and traditional energy resources for sustainable wireless sensor networks: a review. Renew Sust Energ Rev 45:769–784

    Article  Google Scholar 

  46. Khasawneh M, Agarwal A (2016) A collaborative approach towards securing spectrum sensing in cognitive radio networks. Proced Comput Sci 94:302–309

    Article  Google Scholar 

  47. Amjad MF et al (2016b) Towards trustworthy collaboration in spectrum sensing for ad hoc cognitive radio networks. Wirel Netw 22(3):781–797

    Article  Google Scholar 

  48. Akyildiz IF et al (2002) A survey on sensor networks. IEEE Commun Mag 40(8):102–114

    Article  Google Scholar 

  49. Rashid B, Rehmani MH (2016) Applications of wireless sensor networks for urban areas: a survey. J Netw Comput Appl 60:192–219

    Article  Google Scholar 

Download references

Acknowledgement

This paper was partially supported by ESTABLISH, WINS@HI and EmoSpaces projects.

Author information

Authors and Affiliations

  1. Telecommunication and Information Technology, Politehnica University of Bucharest, 060042, Iuliu Maniu 1-3, Bucharest, 060042, Romania

    Raluca Maria Aileni, George Suciu, Victor Suciu, Sever Pasca & Rodica Strungaru

Authors
  1. Raluca Maria Aileni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. George Suciu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor Suciu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sever Pasca
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Rodica Strungaru
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Telecommunications Software and Systems Group, Waterford Institute of Technology, Waterford, Ireland

    Mubashir Husain Rehmani

  2. National Polytechnic Institute of Toulouse, Toulouse, France

    Riadh Dhaou

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Aileni, R.M., Suciu, G., Suciu, V., Pasca, S., Strungaru, R. (2019). Health Monitoring Using Wearable Technologies and Cognitive Radio for IoT. In: Rehmani, M., Dhaou, R. (eds) Cognitive Radio, Mobile Communications and Wireless Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-91002-4_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-91002-4_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-91001-7

  • Online ISBN: 978-3-319-91002-4

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation