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Evolution and Adoption of Next Generation IoT-Driven Health Care 4.0 Systems

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Abstract

The uprising of Internet of Things (IoT) has dramatically influenced the world’s technology in terms of interoperability, connectivity and interconnectivity with help of smart sensors, devices, objects, data and applications. General population aging, dearth of healthcare resources and upsurge in healthcare costs makes IoT advancements in healthcare all the more essential in order to confront these challenges. The revolution in IoT healthcare is redeveloping the healthcare sector in every aspect – social, technical and economical. This article presents a comprehensive survey on upcoming technologies helpful in healthcare 4.0 systems where the major focus is on emerging technologies like fog computing, cloud computing, machine learning and Bigdata analytics and that are all based on IoT based healthcare applications. In addition, the authors also provided an exhaustive survey on Wide Body Area Network (WBAN)-based IoT health care systems and discussed their network topology, architecture, platform, services and their applications. In addition, this study analyses IoT healthcare security challenges, possible threats, attack taxonomies and how blockchain technology can be helpful in countering these challenges. Lastly, exhaustive state-of-the-art technologies, challenges identified so far and possible future scope of this domain is also discussed in this survey.

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References

  1. Kuroda, T., Sasaki, H., Suenaga, T., Masuda, Y., Yasumuro, Y., Hori, K., Ohboshi, T., Takemura, K. C., & Yoshihara, H. (2012). Embedded ubiquitous services on hospital information systems. IEEE Transactions on Information Technology in Biomedicine, 16(6), 12161223.

    Google Scholar 

  2. Jeong, S., Youn, C.-H., Shim, E. B., Kim, M., Cho, Y. M., & Peng, L. (2012). An integrated healthcare system for personalized chronic disease care in home-hospital environments. IEEE Transactions on Information Technology in Biomedicine, 16(4), 572585.

    Google Scholar 

  3. Pang, Z. (2013) Technologies and architectures of the Internet-of-Things (IoT) for health and well-being. M.S. thesis, Dept. Electron. Comput. Syst., KTH-Roy. Inst. Technol

  4. Vasanth, K., Sbert, J. (2014) Creating solutions for health through technology innovation. Texas Instruments. [Online]. Available: http://www.ti.com/lit/wp/sszy006/sszy006.pdf, Accessed Dec. 7.

  5. Atzori, L., Iera, A., & Morabito, G. (2010). The internet of things: A survey. Computer Networks, 54(15), 2787–2805.

    MATH  Google Scholar 

  6. Ning, H., Liu, H., Ma, J., Yang, L. T., & Huang, R. (2016). Cybermatics: Cyber-physical social thinking hyperspace-based science and technology. Future Generation Computer Systems, 56, 504–522.

    Google Scholar 

  7. Evans, D. (2011). The internet of things: How the next evolution of the internet is changing everything. CISCO White Paper, 1, 1–11.

    Google Scholar 

  8. Cisco global cloud index: Forecast and methodology, 2014–2019 white paper.

  9. Cortes, R., Bonnaire, X., Marin, O., & Sens, P. (2015). Stream processing of healthcare sensor data: Studying user traces to identify challenges from a big data perspective. Procedia Computer Science, 52(1), 1004–1009.

    Google Scholar 

  10. He, Z., Cai, Z., Yu, J., Wang, X., Sun, Y., & Li, Y. (2017). Cost-efficient strategies for restraining rumor spreading in mobile social networks. IEEE Transactions on Vehicular Technology, 66(3), 2789–2800.

    Google Scholar 

  11. Market research report. Retrieved March 2017 from http://www.grandviewresearch.com/industry-analysis/fog-computing-market .

  12. Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., & Zaharia, M. (2010). A view of cloud computing. Communications of the Acm, 53(4), 50–58.

    Google Scholar 

  13. Fernando, N., Loke, S. W., & Rahayu, W. (2013). Mobile cloud computing: A survey. Future Generation Computer Systems, 29(1), 84106.

    Google Scholar 

  14. Qiu, T., Zheng, K., Song, H., Han, M., & Kantarci, B. (2017). A local-optimization emergency scheduling scheme with self-recovery for smart grid. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/TII.2017.2715844

    Article  Google Scholar 

  15. Cao, Y., Chen, S., Hou, P., Brown, D. (2015). Fast: A fog computing assisted distributed analytics system to monitor fall for stroke mitigation In IEEE International Conference on Networking, Architecture and Storage, pp. 2–11.

  16. Stantchev, V., Barnawi, A., Ghulam, S., Schubert, J., & Tamm, G. (2015). Smart items, fog and cloud computing as enablers of servitization in healthcare. Sensors & Transducers, 185(2), 121–128.

    Google Scholar 

  17. T. Qiu, R. Qiao, D. Wu, Eabs: An event-aware backpressure scheduling scheme for emergency internet of things, IEEE Transactions on Mobile Computing PP (99) (2017) 1–1. doi:https://doi.org/10.1109/TMC.2017.2702670.

  18. Arkian, H. R., Diyanat, A., & Pourkhalili, A. (2017). Mist: Fog-based data analytics scheme with cost efficient resource provisioning for IoT crowdsensing applications. Journal of Network & Computer Applications, 82, 152–165.

    Google Scholar 

  19. Yi, S., Hao, Z., Qin, Z., & Li, Q. (2015). Fog computing: Platform and applications, in. Third IEEE Workshop on Hot Topics in Web Systems and Technologies, 2015, 73–78.

    Google Scholar 

  20. Datta, S. K., Bonnet, Haerri, J. (2015). Fog computing architecture to enable consumer centric internet of things services. In International Symposium on Consumer Electronics, pp. 1–2.

  21. Bonomi, F., Milito, R., Zhu, J., Addepalli, S. (2012). Fog computing and its role in the internet of things, in: Edition of the Mcc Workshop on Mobile Cloud Computing, pp. 13–16.

  22. Sarkar, S., & Misra, S. (2016). Theoretical modelling of fog computing: A green computing paradigm to support IoT applications. IET Networks, 5(2), 23–29.

    Google Scholar 

  23. Hu, P., Ning, H., Qiu, T., Zhang, Y., & Luo, X. (2017). Fog computing based face identification and resolution scheme in internet of things. IEEE Transactions on Industrial Informatics, 13(4), 1910–1920.

    Google Scholar 

  24. Kang, K., Wang, C., & Luo, T. (2016). Fog computing for vehicular ad-hoc networks: Paradigms, scenarios, and issues. Journal of China Universities of Posts & Telecommunications, 23(2), 56–96.

    Google Scholar 

  25. Bonomi, F. Milito, R., Natarajan, P., Zhu, J. (2014) Fog computing: A platform for internet of things and analytics, Springer International Publishing.

  26. Dsouza, C., Ahn, G. J., Taguinod, M. (2015). Policy-driven security management for fog computing: Preliminary framework and a case study, In IEEE International Conference on Information Reuse and Integration, pp. 16–23

  27. Varshney, P., Simmhan, Y. (2017). Demystifying fog computing: Characterizing architectures, applications and abstractions, arXiv preprint arXiv:1702.06331 pp. 1–23.

  28. Luan, T. H., Gao, L., Li, Z., Xiang, Y., Wei, G., Sun, L. (2015). Fog computing: Focusing on mobile users at the edge, Computer Science pp. 1–11.

  29. Hossain, M. S., & Atiquzzaman, M. (2013). Cost analysis of mobility protocols. Telecommunication Systems, 52(4), 2271–2285.

    Google Scholar 

  30. Natal, A. R., Jakab, L., Portols, M., Ermagan, V., Natarajan, P., Maino, F., Meyer, D., & Aparicio, A. C. (2013). Lispmn: Mobile networking through lisp. Wireless Personal Communications, 70(1), 253–266.

    Google Scholar 

  31. Natraj, A. (2016). fog computing focusing on users at the edge of internet of things. International Journal of Engineering Research, 5(5), 1004–1008.

    Google Scholar 

  32. Vaquero, M. L., & RoderoMerino, L. (2014). Finding your way in the fog: Towards a comprehensive definition of fog computing. Acm Sigcomm Computer Communication Review, 44(5), 27–32.

    Google Scholar 

  33. Shi, C., Lakafosis, V., Ammar, M. H., Zegura, E. W. (2012) Serendipity: Enabling remote computing among intermittently connected mobile devices, in: ACM MOBIHOC, pp. 145–154.

  34. Hassan, M. A., Xiao, M., Wei, Q., Chen, S. (2015) Help your mobile applications with fog computing, In IEEE International Conference on Sensing, Communication, and Networking - Workshops, pp. 1–6.

  35. Chiuchisan, I., Costin, H.N., Geman, O. (2014). Adopting the Internet of things technolo- gies in health care systems, In Proceedings of the International Conference and Exposition on IEEE Electrical and Power Engineering, Iasi, Romania, pp. 532–535.

  36. Luo, J., Chen, Y., Tang, K., Luo, J. (2009). Remote monitoring information system and its applications based on the Internet of Things, in: Proceedings of the Biomedical Information Engineering. FBIE 2009, pp. 482–485.

  37. Gustafson, D.H., DuBenske, L.L., Atwood, A.K., Chih, M.Y., Johnson, R.A., Mc- Tavish, F., Quanbeck, A., Brown, R.L., Cleary, J.F., Shah, D. (2017). Reducing symptom dis- tress in patients with advanced cancer using an e-alert system for caregivers: pooled analysis of two randomized clinical trials, Journal of Medical Internet Research 19 (11) e354.

  38. Wang, W., Li, J., Wang, L., Zhao, W. (2011). The Internet of Things for resident health information service platform research, In Proceedings of the IET International Conference on Communication Technology and Application, pp. 631–635.

  39. Kiran, M.S., Rajalakshmi, P., Bharadwaj, K., Acharyya, A. (2014). Adaptive rule engine based IoT enabled remote health care data acquisition and smart transmission system, In Proceedings of the IEEE World Forum on Internet of Things, pp. 253–258.

  40. Chiuchisan, I., Costin, H.N., Geman, O. (2014) Adopting the Internet of things technologies in health care systems, In Proceedings of the International Conference and Exposition on IEEE Electrical and Power Engineering, pp. 532–535.

  41. Yuce, M. R. (2010). Implementation of wireless body area networks for healthcare systems. Sensors and Actuators, A: Physical, 162(1), 116–129.

    Google Scholar 

  42. Ko, J., Lu, C., Srivastava, M. B., Stankovic, J. A., Terzis, A., & Welsh, M. (2010). Wireless sensor networks for healthcare. Proceedings of the IEEE, 98(11), 1947–1960.

    Google Scholar 

  43. Viswanathan, H., Lee, E.K., Pompili, D. (2012). Mobile grid computing for data- and patient-centric ubiquitous healthcare, In Proceedings of the 1st IEEE Workshop Enabling Technologies for Smartphone Internet Things, pp. 36–41.

  44. Miorandi, D., Sicari, S., De Pellegrini, F., & Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497–1516.

    Google Scholar 

  45. Zhang, X.M., Zhang, N. (2011) An open, secure and flexible platform based on internet of things and cloud computing for ambient aiding living and telemedicine, In Proceedings of the International Conference on IEEE Computer and Management, pp. 1–4.

  46. Firdausi, A.: Overview the internet of things (IOT) system security, applications, architecture and businessmodels.https://s3.amazonaws.com/academia.edu.documents/46880206/Overview_The_Internet_Of_Things_IOT_System_Security_Applications_Architecture_And_Business_Models.pdf?AWSAccessKeyId=AKIAI WOWYY GZ2Y5 3UL3A &Expires=1524848582&Signature=rMY546kXEi3ekA%2BbZb8HFAxL9Bw%3D&response-content disposition=inline%3B%20filename %3DOverview The_Internet_Of_Things_IOT_Syst.pdf. Accessed 15 June 2017

  47. Uckelmann, D., Harrison, M., & Michahelles, F. (2011). An architectural approach towards the future internet of things. In D. Uckelmann, M. Harrison, & F. Michahelles (Eds.), Architecting the internet of things (pp. 1–24). Springer.

    Google Scholar 

  48. Mieronkoski, R., Azimi, I., Rahmani, A. M., Aantaa, R., Terävä, V., Liljeberg, P., et al. (2017). The internet of things for basic nursing care—a scoping review. International Journal of Nursing Studies, 69, 78–90.

    Google Scholar 

  49. Fox, G.C., Kamburugamuve, S., Hartman, R.D. (eds.) (2012). Architecture and measured characteristics of a cloud based internet of things. In Collaboration technologies and systems (CTS), 2012 international conference on. IEEE

  50. Ashraf, Q.M., Habaebi, M.H., Sinniah, G.R., Ahmed, M.M., Khan, S., Hameed, S. (eds.) (2014). Autonomic protocol and architecture for devices in Internet of Things. Innovative Smart Grid Technologies-Asia (ISGT Asia), 2014 IEEE. IEEE.

  51. Hemalatha, D., & Afreen, B. E. (2015). Development in RFID (radio frequency identification) technology in internet of things (IOT). International Journal of Advanced Research in Computer Engineering and Technology, 4(11), 4030–4038.

    Google Scholar 

  52. Krco, S., Pokric, B., Carrez, F. (eds.) (2014). Designing IoT architecture (s): a European perspective. Internet of Things (WF-IoT), 2014 IEEE World Forum on. IEEE.

  53. Ivascu, T., Manate, B., Negru, V. (eds.) (2015). A multi-agent architecture for ontology-based diagnosis of mental disorders. In: Symbolic and numeric algorithms for scientific computing (SYNASC), 2015 17th international symposium on. IEEE.

  54. Gupta, P. K., Maharaj, B., & Malekian, R. (2016). A novel and secure IoT based cloud centric architecture to perform predictive analysis of users activities in sustainable health centres. Multimedia Tools and Applications, 76(18), 18489–18512.

    Google Scholar 

  55. Zgheib, R., Bastide, R., Conchon, E. (eds.) (2015) A semantic web of-things architecture for monitoring the risk of bedsores. In Computational science and computational intelligence (CSCI), 2015 international conference on. IEEE.

  56. Bazzani, M., Conzon, D., Scalera, A., Spirito, M.A., Trainito, C.I. (eds.) (2012). Enabling the IoT paradigm in e-health solutions through the VIRTUS middleware. In Trust, security and privacy in computing and communications (TrustCom), 2012 IEEE 11th international conference on. IEEE

  57. Moosavi, S. R., Gia, T. N., Nigussie, E., Rahmani, A. M., Virtanen, S., Tenhunen, H., et al. (2016). End-to-end security scheme for mobility enabled healthcare internet of things. Future Generation Computer System, 64, 108–124.

    Google Scholar 

  58. Fazio, M., Celesti, A., Márquez, F.G., Glikson, A., Villari, M. (eds.) (2015). Exploiting the fiware cloud platform to develop a remote patient monitoring system. In Computers and communication (ISCC), 2015 IEEE symposium on. IEEE

  59. Ray, P.P. (ed.) (2014) Home Health Hub Internet of Things (H 3 IoT): an architectural framework for monitoring health of elderly people. In Science engineering and management research (ICSEMR), 2014 international conference on. IEEE.

  60. Gelogo, Y.E., Oh, J.-W., Park, J.W., Kim, H.-K. (eds.) (2015) Internet of things (IoT) driven U-Healthcare system architecture. In bio-science and bio-technology (BSBT), 2015 8th International Conference on. IEEE.

  61. Fan, Y. J., Yin, Y. H., Da Xu, L., Zeng, Y., & Wu, F. (2014). IoT-based smart rehabilitation system. IEEE Transactions of Industrial Informatics, 10(2), 1568–1577.

    Google Scholar 

  62. Spanò, E., Di Pascoli, S., & Iannaccone, G. (2016). Low-power wearable ECG monitoring system for multiple-patient remote monitoring. IEEE Sensors Journal, 16(13), 5452–5462.

    Google Scholar 

  63. Gómez, J., Oviedo, B., & Zhuma, E. (2016). Patient monitoring system based on internet of things. Procedia Computer Science, 83, 90–97.

    Google Scholar 

  64. Moosavi, S.R., Rahmani, A.-M., Westerlund, T., Yang, G., Liljeberg, P., Tenhunen, H. (2014). Pervasive health monitoring based on Internet of Things: two case studies. In Wireless mobile communication and healthcare (Mobihealth), 2014 EAI 4th international conference on. IEEE.

  65. Rahmani, A.-M., Thanigaivelan, N.K., Gia, T.N., Granados, J., Negash, B., Liljeberg, P., et al. (eds.) (2015). Smart e-health gateway: bringing intelligence to internet-of-things based ubiquitous healthcare systems. In Consumer communications and networking conference (CCNC), 2015 12th annual IEEE. IEEE.

  66. Ullah, K., Shah, M.A., Zhang, S. (eds.) (2016). Effective ways to use internet of things in the field of medical and smart health care. In Intelligent systems engineering (ICISE), 2016 international conference on. IEEE.

  67. Lee, J. D., Yoon, T. S., Chung, S. H., & Cha, H. S. (2015). Service-oriented security framework for remote medical services in the internet of things environment. Healthcare Informatics Research, 21(4), 271–282.

    Google Scholar 

  68. Monteiro, A., Dubey, H., Mahler, L., Yang, Q., Mankodiya, K. (eds.) (2016). Fit: a fog computing device for speech tele-treatments. In 2016 IEEE International Conference on Smart computing (SMARTCOMP). IEEE, St. Louis, MO.

  69. Cao, Y., Hou, P., Brown, D., Wang, J., Chen, S. (eds.) (2015). Distributed analytics and edge intelligence: pervasive health monitoring at the era of fog computing. In Proceedings of the 2015 workshop on mobile big data. ACM.

  70. Yang, L., Ge, Y., Li, W., Rao, W., Shen, W. (2014). A home mobile healthcare system for wheelchair users, In Proceedings of the IEEE International Conference on Computer Supported Cooperative Work in Design, Hsinchu, pp. 609–614.

  71. Shahamabadi, M. S., Ali, B. B. M., Varahram, P., Jara, A. J. (2013). A network mobility solution based on 6LoWPAN hospital wireless sensor network (NEMO-HWSN),'' In Proc. 7th Int. Conf. Innov. Mobile Internet Services Ubiquitous Comput. (IMIS), pp. 433_438.

  72. ICH Expert Working Group, (1996) Guidance for industry-E6 good clinical practice: Consolidated guidance,. U.S. Dept. Health Human Services, Food Drug Admin., Silver Spring, MD, USA

  73. Jara, A. J., Belchi, F. J., Alcolea, A. F., Santa, J., Zamora-Izquierdo, M. A., Gomez-Skarmeta, A. F. (2010) A pharmaceutical intelligent information system to detect allergies and adverse drugs reactions based on Internet of Things,'' In Proc. IEEE Int. Conf. Pervasive Comput. Commun. Workshops (PERCOM Workshops), Mar., pp. 809_812.

  74. Yang, G., et al. (2014) A health-IoT platform based on the integration of intelligent packaging, unobtrusive bio-sensor, and intelligent medicine box. IEEE Trans. Ind. Informat., vol. 10, no. 4, pp. 2180_2191.

  75. Mantas, G., Lymberopoulos, D., Komninos, N. (2010) A new framework for ubiquitous context-aware healthcare applications, In Proc. 10th IEEE Int. Conf. Inf. Technol. Appl. Biomed. (ITAB), Nov. 2010, pp. 1_4.

  76. Viswanathan, H., Chen, B., Pompili, D. (2012) Research challenges in computation, communication, and context awareness for ubiquitous healthcare,. IEEE Commun. Mag., vol. 50, no. 5, pp. 92_99.

  77. Sai Kiran, M. P. R., Rajalakshmi, P., Acharyya, A. (2014) Context predictor based sparse sensing technique and smart transmission architecture for IoT enabled remote health monitoring applications. In Proc. IEEE Int. Conf. Eng. Med. Biol. Soc. (EMBC), pp. 4151_4154.

  78. Istepanian, R. S. H., Jovanov, E., Zhang, Y. T. (2004) Guest editorial introduction to the special section on m-health: Beyond seamless mobility and global wireless health-care connectivity. IEEE Trans. Inf. Technol. Biomed., vol. 8, no. 4, pp. 405_414.

  79. Istepanian, R. S. H., Hu, S., Philip, N. Y., Sungoor, A. (2011). The potential of Internet of m-health Things `m-IoT' for non-invasive glucose level sensing,'' In Proc. IEEE Annu. Int. Conf. Eng. Med. Biol. Soc. (EMBC), pp. 5264_5266.

  80. Istepanian, R. S. H. (2011). The potential of Internet of Things (IoT) for assisted living applications. In Proc. IET Seminar Assist. Living, Apr., pp. 1_40

  81. Drew, B. J. et al. (2004). Practice standards for electrocardiographic monitoring in hospital settings, Circulation, vol. 110, no. 17, pp. 2721_2746.

  82. Jara, A. J., Zamora-Izquierdo, M. A., Skarmeta, A. F. (2013). Interconnection framework for mHealth and remote monitoring based on the Internet of Things,'' IEEE J. Sel. Areas Commun., vol. 31, no. 9, pp. 47_65.

  83. Rasid, M. F. A. et al. (2014). Embedded gateway services for Internet of Things applications in ubiquitous healthcare,'' In Proc. 2nd Int. Conf. Inf. Commun. Technol. (ICoICT), May 2014, pp. 145_148.

  84. You, L., Liu, C., S. Tong, (2011). Community medical network (CMN): Architecture and implementation,'' In Proc. Global Mobile Congr. (GMC), pp. 1_6

  85. Yang, L., Ge, Y., Li, W., Rao, W., Shen, W. (2014) A home mobile healthcare system for wheelchair users,'' In Proc. IEEE Int. Conf. Comput. Supported Cooperat. Work Design (CSCWD) pp. 609_614.

  86. Castillejo, P., Martinez, J.-F., Rodriguez-Molina, J., Cuerva, A. (2013). Integration of wearable devices in a wireless sensor network for an e-health application. IEEE Wireless Commun., vol. 20, no. 4, pp. 38_49.

  87. Agu, E. et al. (2013) The smartphone as a medical device: Assessing enablers, benefits and challenges. In Proc. IEEE Int. Workshop Internet-Things Netw. Control (IoT-NC), pp. 48_52.

  88. Liu, M.-L., Tao, L., Yan, Z. (2012) Internet of Things-based electrocardiogram monitoring system. Chinese Patent 102 764 118 A, Nov. 7

  89. Xiaogang, Y., Hongjiang, L., Jiaqing, W., Wentao, T. (2011) Realization of comprehensive detection algorithm of electrocardiogram signal at application layer electrocardiogram monitoring Internet of Thing. Chinese Patent 101 947 112 A.

  90. Khattak, H. A., Ruta, M., Di Sciascio, E. (2014) CoAP-based healthcare sensor networks: A survey In Proc. 11th Int. Bhurban Conf. Appl. Sci. Technol. (IBCAST), pp. 499_503.

  91. Larson, E. C., Goel, M., Boriello, G., Heltshe, S., Rosenfeld, M., Patel, S. N. (2012). SpiroSmart: Using a microphone to measure lung function on a mobile phone. In Proc. ACM Int. Conf. Ubiquitous Comput., pp. 280_289.

  92. Larson, E. C., Goel, M., Red_eld, M., Boriello, G., Rosenfeld, M., Patel, S. N. (2013) Tracking lung function on any phone. In Proc. ACM Symp. Comput. Develop. Art. ID 29.

  93. Pang, Z., Tian, J., Chen, Q. (2014). Intelligent packaging and intelligent medicine box for medication management towards the Internet-of-Things. In Proc. 16th Int. Conf. Adv. Commun. Technol. (ICACT), pp. 352_360.

  94. Laranjo, I., Macedo, J., Santos A. (2013). Internet of Things for medication control: E-health architecture and service implementation. Int. J. Rel. Quality E-Healthcare, vol. 2, no. 3, pp. 1_15

  95. Kolici, V., Spaho, E., Matsuo, K., Caballe, S., Barolli, L. Xhafa, F. (2014). Implementation of a medical support system considering P2P and IoT technologies. In Proc. 8th Int. Conf. Complex, Intell. Softw. Intensive Syst. (CISIS), pp. 101_106.

  96. Dr. Hawking's Connected Wheelchair Project. [Online]. (2014) Available: http://www.intel.co.kr/content/www/kr/ko/internet-of-things/videos/drhawkings-connected wheelchair-video.html, Accessed Dec. 8

  97. Beevers, G., Lip, G. Y. H., & O’Brien, E. (2001). ABC of hypertension: The pathophysiology of hypertension. BMJ, 322(7291), 912–916.

    Google Scholar 

  98. Mukkamala, R., Hahn, J.-O., Inan, O. T., Mestha, L. K., Kim, C.-S., T€oreyin, H., & Kyal, S. (2015). Towards ubiquitous blood pressure monitoring via pulse transit time: Theory and practice. IEEE Transactions of Biomedicine Engineering, 62, 1879–1901.

    Google Scholar 

  99. Jeong, G.-Y., Yu, K.-H., Kim, N.-G. (2005). In Continuous blood pressure monitoring using pulse wave transit time, International Conference on Control, Automation and Systems

  100. Kong, K., Bae, J., Jeon, D., Tomizuka, M. (2008) In: Design of smart shoes for measurement of ground contact forces, IEEE International Conference on Robotics and Automation

  101. Khan, Y., Ostfeld, A. E., Lochner, C. M., Pierre, A., & Arias, A. C. (2016). Monitoring of vital signs with flexible and wearable medical devices. Advanced Materials, 28(22), 4373–4395.

    Google Scholar 

  102. Nemati, E., Deen, M. J., & Mondal, T. (2012). A wireless wearable ECG sensor for long-term applications. IEEE Communications Magazine, 50(1), 36–43.

    Google Scholar 

  103. Chi, Y.M., Cauwenberghs G. (2010) In: Wireless non-contact EEG/ECG electrodes for body sensor networks, International Conference on Body Sensor Networks (BSN)

  104. Caicedo, D., & Pandharipande, A. (2015). Sensor-driven lighting control with illumination and dimming constraints. IEEE Sensor J., 99, 5169–5176.

    Google Scholar 

  105. Wikipedia (2017) Activity Tracker, Wikipedia, 23 August. Available from: https://en.wikipedia.org/wiki/Activity_tracker.

  106. Wareable (2017) Fitness Trackers, Wareable. Available from: https://www.wareable.com/fitness-trackers. Accessed August 2017.

  107. Pourhomayoun, M., Alshurafa, N., Dabiri, F., Ardestani, E., Samiee, A., Ghasemzadeh H., Sarrafzadeh, M. (2017) Why do we need a remote health monitoring system? A study on predictive analytics for heart failure patients”. 11th International Conference on Body Area Networks

  108. EarlySense “Early Sense One”. (2017). Retrieved from http://www.earlysense.com/earlysense-one/,

  109. Stevens, J. A., & Rudd, R. A. (2014). Circumstances and contributing causes of fall deaths among persons aged 65 and older. Journal of the American Geriatrics Society, 62, 470–475.

    Google Scholar 

  110. Fade, “Fade: Fall Detector”. (2017). Retrieved from: http://fade.iter.es/

  111. Assisted Living Technologies (2017). BeClose Remote Monitoring System”. Retrieved from: http://www.assistedlivingtechnologies.com/remote-monitoringelderly/11-beclose.html

  112. Piwek, L., Ellis, D. A., Andrew, S., & Joinson, A. (2016). The rise of consumer health wearables: Promises and barriers. PloS Medicine, 13, e1001953.

    Google Scholar 

  113. MC10, “BioStampMD”. (2017). Retrieved from https://www.mc10inc.com/our-products#BioStampMD

  114. Bittium, “IoT and Wearable Solutions”. (2017) Retrieved from https://www.bittium.com/products__services/iot_and_wearable_solutions/healthcare_market#concept_examples

  115. Apple, “Apple Watch Series 2”. (2017). Retrieved from: https://www.apple.com/br/watch/

  116. Saúde Business, “O que é Mobile Health” (2017).. http://saudebusiness.com/noticias/o-que-e-mobile-healthinfografico/

  117. OnTrack, “OnTrack Diabetes App (2017). Retrieved from https://www.ontrack.org.au/diabetes/

  118. Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., & Kwak, K.-S. (2015). The internet of things for health care: A comprehensive survey. IEEE Access, 3, 678–708.

    Google Scholar 

  119. Yang, L., Ge, Y., Li, W., Rao, W., Shen, W. (eds.) (2014). A home mobile healthcare system for wheelchair users. In Computer supported cooperative work in design (CSCWD), proceedings of the 2014 IEEE 18th international conference on. IEEE

  120. Woznowski, P., Burrows, A., Diethe, T., Fafoutis, X., Hall, J., Hannuna, S., et al. (2017). SPHERE: a sensor platform for healthcare in a residential environment, designing, developing, pp. 315–333. Springer

  121. Mainetti, L., Manco, L., Patrono, L., Secco, A., Sergi, I., Vergallo, R. (eds.) (2016). An ambient assisted living system for elderly assistance applications. In Personal, indoor, and mobile radio communications (PIMRC), 2016 IEEE 27th annual international symposium on. IEEE

  122. Khoi, N.M., Saguna, S., Mitra, K., Ǻhlund, C. (eds.) (2015). Irehmo: an efficient IOT-based remote health monitoring system for smart regions. In E-health Networking, Application & Services (HealthCom), 2015, 17th International Conference on. IEEE

  123. Catarinucci, L., De Donno, D., Mainetti, L., Palano, L., Patrono, L., Stefanizzi, M. L., et al. (2015). An IoT-aware architecture for smart healthcare systems. IEEE Internet of Things Journal, 2(6), 515–526.

    Google Scholar 

  124. Al-Adhab, A., Altmimi, H., Alhawashi, M., Alabduljabbar, H., Harrathi, F., ALmubarek, H. (eds.) (2016). IoT for remote elderly patient care based on Fuzzy logic. In Networks, computers and communications (ISNCC), 2016 international symposium on. IEEE.

  125. Jara, A.J., Zamora, M.A., Skarmeta, A.F. (eds.) (2012). Knowledge acquisition and management architecture for mobile and personal health environments based on the internet of things. In Trust, security and privacy in computing and communications (TrustCom), 2012 IEEE 11th international conference on. IEEE.

  126. Istepanian, R.S., Hu, S., Philip, N.Y., Sungoor, A. (eds.) (2011). The potential of internet of m-health Things “m-IoT” for non-invasive glucose level sensing. In Engineering in medicine and biology society, EMBC, 2011 annual international conference of the IEEE.

  127. Hossain, M. S., & Muhammad, G. (2016). Cloud-assisted industrial internet of things (iiot)–enabled framework for health monitoring. Computer Networks, 101, 192–202.

    Google Scholar 

  128. Sung, W.-T., & Chang, K.-Y. (2013). Evidence-based multi-sensor information fusion for remote health care systems. Sensors and Actuators, A: Physical, 204, 1–19.

    Google Scholar 

  129. Jara, A. J., Zamora, M. A., & Skarmeta, A. F. (2014). Drug identification and interaction checker based on IoT to minimize adverse drug reactions and improve drug compliance. Pers. Ubiquitous Computer, 18(1), 5–17.

    Google Scholar 

  130. Bhatia, M., & Sood, S. K. (2016). Temporal informative analysis in smart-ICU Monitoring: M-HealthCare perspective. Journal of Medical Systems, 40(8), 1–15.

    Google Scholar 

  131. Pang, Z., Tian, J., Chen, Q. (eds.) (2014) Intelligent packaging and intelligent medicine box for medication management towards the Internet-of-Things. In Advanced communication technology (ICACT), 2014 16th international conference on. IEEE

  132. Ji, Z., Anwen, Q. (eds.) (2010) The application of internet of things (IoT) in emergency management system in China. In: Technologies for homeland security (HST), 2010 IEEE international conference on. IEEE

  133. Ray, P.P. (2014) Internet of things based physical activity monitoring (PAMIoT): an architectural framework to monitor human physical activity. In Proceeding of IEEE CALCON, Kolkata, pp. 32–34

  134. Qi, J., Yang, P., Fan, D., Deng, Z. (eds.) (2015). A survey of physical activity monitoring and assessment using internet of things technology. In Computer and information technology; ubiquitous computing and communications; dependable, autonomic and secure computing; pervasive intelligence and computing (CIT/IUCC/DASC/PICOM), 2015 IEEE international conference on IEEE

  135. Rathore, M. M., Ahmad, A., Paul, A., Wan, J., & Zhang, D. (2016). Real time medical emergency response system: Exploiting IoT and big data for public health. Journal of Medical Systems, 40(12), 283.

    Google Scholar 

  136. Al-Taee, M.A., Al-Nuaimy, W., Al-Ataby, A., Muhsin, Z.J., Abood, S.N. (eds.) (2015). Mobile health platform for diabetes management based on the Internet-of-Things. In Applied electrical engineering and computing technologies (AEECT), 2015 IEEE Jordan conference on. IEEE.

  137. Valera, AJJ, Zamora, M.A., Skarmeta, A.F. (eds.) (2010). An architecture based on internet of things to support mobility and security in medical environments. In Consumer communications and networking conference (CCNC), 2010 7th IEEE. IEEE.

  138. Coelho, C., Coelho, D., Wolf, M. (eds.) (2015). An IoT smart home architecture for long-term care of people with special needs. In Internet of things (WF-IoT), 2015 IEEE 2nd world forum on.IEEE.

  139. Pir, A., Akram, M.U., Khan, M.A. (eds.) (2015). Internet of things based context awareness architectural framework for HMIS. In: E-health networking, application & services (HealthCom), 2015 17th international conference on. IEEE

  140. Mohammed, J., Lung, C.-H., Ocneanu, A., Thakral, A., Jones, C., Adler, A. (eds.) (2014). Internet of things: remote patient monitoring using web services and cloud computing. In Internet of things (iThings), 2014 IEEE international conference on, and green computing and communications (GreenCom), IEEE and cyber, physical and social computing (CPSCom), IEEE

  141. Santos, J., Rodrigues, J. J., Silva, B. M., Casal, J., Saleem, K., & Denisov, V. (2016). An IoT-based mobile gateway for intelligent personal assistants on mobile health environments. Journal of Network and Computer Applications, 71, 194–204.

    Google Scholar 

  142. Blazek, P., Krejcar, O., Jun, D., & Kuca, K. (2016). Device security implementation model based on internet of things for a laboratory environment. IFAC PapersOnLine, 49(25), 419–424.

    Google Scholar 

  143. Hussain, A., Wenbi, R., da Silva, A. L., Nadher, M., & Mudhish, M. (2015). Health and emergency-care platform for the elderly and disabled people in the Smart City. Journal of Systems and Software, 110, 253–263.

    Google Scholar 

  144. Distefano, S., Bruneo, D., Longo, F., Merlino, G., & Puliafito, A. (2016). Hospitalized patient monitoring and early treatment using IoT and cloud. BioNanoScience, 7(2), 1–4.

    Google Scholar 

  145. Roy, S., Bhattacharya, U. (eds.) (2015) Smart mom: an architecture to monitor children at home. In Proceedings of the third international symposium on women in computing and informatics. ACM

  146. Stefanov, D. H., Bien, Z., & Bang, W.-C. (2004). The smart house for older persons and persons with physical disabilities: Structure, technology arrangements, and perspectives. IEEE Transactions Neural System Rehabilition Engineering, 12(2), 228–250.

    Google Scholar 

  147. Jara, A.J., Alcolea, A.F., Zamora, M., Skarmeta, A.G., Alsaedy, M. (eds.) (2017) Drugs interaction checker based on IoT. In Internet of Things (IOT), 2010. IEEE (2010). https ://www.resea rchga te.net/profile/Antonio_Skarm eta/publication/22420 8800_Drugs interaction_checker_based on_IoT/links /546dd ed70c f2193 b94c5 d9f3.pdf. Accessed July 2017

  148. Thang, T.C., Pham, A.T., Cheng, Z., Ngoc, N.P. (eds.) (2011) Towards a full-duplex emergency alert system based on IPTV platform. In Awareness science and technology (iCAST), 2011 3rd international conference on. IEEE

  149. Jara, A.J., Belchi, F.J., Alcolea, A.F., Santa, J., Zamora-Izquierdo, M.A., Gómez-Skarmeta, A.F. (eds.) (2010) A Pharmaceutical Intelligent Information System to detect allergies and Adverse Drugs Reactions based on internet of things. In Pervasive computing and communications workshops (PERCOM Workshops), 2010 8th IEEE international conference on. IEEE

  150. Zhang, H., Liu, K., Kong, W., Tian, F., Yang, Y., Feng, C., et al. (eds.) (2016) A mobile health solution for chronic disease management at retail pharmacy. In e-Health networking, applications and services (Healthcom), 2016 IEEE 18th international conference on. IEEE

  151. F. Yuan Jie, Y. Yue Hong, X. Li Da, Z. Yan, and W. Fan (2014) IoT-Based Smart Rehabilitation System. Industrial Informatics, IEEE Transactions on, vol. 10, pp. 1568–1577

  152. Jin, J., Gubbi, J., Marusic, S., & Palaniswami, M. (2014). An information framework for creating a smart city through Internet of Things. IEEE Internet of Things Journal, 1, 112–121.

    Google Scholar 

  153. Jara, A. J., Zamora-Izquierdo, M. A., & Skarmeta, A. F. (2013). Interconnection framework for mHealth and remote monitoring based on the internet of things. Selected Areas in Communications, IEEE Journal on, 31, 47–65.

    Google Scholar 

  154. Wei, Z., Chaowei, W., & Nakahira, Y. (2011). "Medical application on internet of things. In communication technology and application (ICCTA. IET International Conference on, 2011, 660–665.

    Google Scholar 

  155. Castillejo, P., Martinez, J. F., Rodriguez-Molina, J., & Cuerva, A. (2013). Integration of wearable devices in a wireless sensor network for an Ehealth application. Wireless Communications, IEEE, 20, 38–49.

    Google Scholar 

  156. Yang, G., Xie, L., Mantysalo, M., Zhou, X., Pang, Z., Xu, L. D., et al. (2014). A Health-IoT Platform Based on the Integration of Intelligent Packaging, Unobtrusive Bio-Sensor, and Intelligent Medicine Box. Industrial Informatics, IEEE Transactions on, 10, 2180–2191.

    Google Scholar 

  157. Istepanian, R. S. H., Hu, S., Philip, N. Y., & Sungoor, A. (2011). "The potential of Internet of m-health Things & #x201C;m-IoT” for noninvasive glucose level sensing," in Engineering in Medicine and Biology Society, EMBC. Annual International Conference of the IEEE, 2011, 5264–5266.

    Google Scholar 

  158. Amendola, S., Lodato, R., Manzari, S., Occhiuzzi, C., & Marrocco, G. (2014). RFID Technology for IoT-based personal healthcare in smart spaces. Internet of Things Journal, IEEE, 1, 144–152.

    Google Scholar 

  159. Turcu, C. E., Turcu, C. O. (2013). Internet of Things as Key Enabler for Sustainable Healthcare Delivery. Procedia - Social and Behavioral Sciences, vol. 73, pp. 251–256, 2/27/

  160. Boric-Lubecke, O., Xiaomeng, G., Yavari, E., Baboli, M., Singh, A., & Lubecke, V. M. (2014). “E-healthcare: Remote monitoring, privacy, and security,” in Microwave Symposium (IMS). IEEE MTT-S International, 2014, 1–3.

    Google Scholar 

  161. Sebestyen, G., Hangan, A., Oniga, S., & Gal, Z. (2014). "eHealth solutions in the context of internet of things. In automation, quality and testing, robotics. IEEE International Conference on, 2014, 1–6.

    Google Scholar 

  162. Boyi, X., Li, X., Da., Hongming, C., Cheng, X., Jingyuan, H., Fenglin, B. (2014). Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services. Industrial Informatics, IEEE Transactions on, vol. 10, pp. 1578–1586

  163. Fang, H., Dan, X., Shaowu S. (2013). On the application of the internet of things in the field of medical and health care. In Green Computing and Communications (GreenCom), 2013 IEEE and Internet of Things (iThings/CPSCom), IEEE International Conference on and IEEE Cyber, Physical and Social Computing, pp. 2053-2058

  164. Weihua, W., Jiangong, L., Ling, W., & Wendong, Z. (2011). The internet of things for resident health information service platform research. In Communication Technology and Application (ICCTA. IET International Conference on, 2011, 631–635.

    Google Scholar 

  165. Swiatek, P., Rucinski, A. (2013). IoT as a service system for eHealth. In e-Health Networking, Applications & Services (Healthcom), 2013 IEEE 5th International Conference on, pp. 81–84.

  166. Min, C., Gonzalez, S., Leung, V., Qian, Z., & Ming, L. (2010). A 2G-RFID based e-healthcare system. Wireless Communications, IEEE, 17, 37–43.

    Google Scholar 

  167. Xu, L., Rongxing, L., Xiaohui, L., Xuemin, S., Jiming, C., & Xiaodong, L. (2011). Smart community: An internet of things application. Communications Magazine, IEEE, 49, 68–75.

    Google Scholar 

  168. Tabish, R., Ghaleb, A. M., Hussein, R., Touati, F., Ben Mnaouer, A., Khriji, L. et al. (2014) A 3G/WiFi-enabled 6LoWPAN-based U-healthcare system for ubiquitous real-time monitoring and data logging. In Biomedical Engineering (MECBME), 2014 Middle East Conference on, pp. 277–280

  169. Dongxin, L., Tao L. (2011). The application of IOT in medical system. In IT in Medicine and Education (ITME), 2011 International Symposium on, pp. 272–275.

  170. Jingran, L., Yulu, C., Kai, T., Junwen, L. (2009) Remote monitoring information system and its applications based on the Internet of Things. In BioMedical Information Engineering, 2009. FBIE 2009. International Conference on Future, pp. 482-485.

  171. Atzori, L., Iera, A., Morabito, G. (2010) The Internet of Things: A survey," Computer Networks, vol. 54, pp. 2787–2805, 10/28/2010.

  172. Chen, S., Zhu, X., Zhang, S., Wang, J. (2012). A framework for massive data transmission in a remote real-time health monitoring system. In Automation and Computing (ICAC), 2012 18th International Conference on, pp. 1–5.

  173. Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: Promise and potential. Health Information and Science System, 2, 3.

    Google Scholar 

  174. Manogaran, G., Varatharajan, R., Lopez, D., Kumar, P. M., Sundarasekar, R., & Thota, C. (2018). A new architecture of Internet of things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generations Computer System, 82, 375–387.

    Google Scholar 

  175. Kalid, N., Zaidan, A. A., Zaidan, B. B., Salman, O. H., Hashim, M., & Muzammil, H. (2018). Based real time remote health monitoring systems: A review on patients prioritization and related ‘Big Data’ using body sensors information and communication technology. Journal of Medical Systems, 42, 2.

    Google Scholar 

  176. Firouzi, F., et al. (2018). Internet-of-Things and Big Data for smarter healthcare: From device to architecture, applications and analytics. Future Gen Comput Syst., 78, 583–586.

    Google Scholar 

  177. Hu, Y., Duan, K., Zhang, Y., Hossain, M. S., Mizanur-Rahman, S. M., & Alelaiwi, A. (2018). Simultaneously aided diagnosis model for outpatient departments via healthcare big data analytics. Multimed Tools Applications, 77(3), 3729–3743.

    Google Scholar 

  178. Sandhu, R., Kaur, N., Sood, S. K., & Buyya, R. (2017). TDRM: Tensor-based data representation and mining for healthcare data in cloud computing environments. The Journal of Supercomputing, 74(2), 592–614.

    Google Scholar 

  179. Saleh, N., Kassem, A., & Haidar, A. M. (2018). Energy-efficient architecture for wireless sensor networks in healthcare applications. IEEE Access., 6, 6478–6486.

    Google Scholar 

  180. Vidal, M., Turner, J., Bulling, A., & Gellersen, H. (2012). Wearable eye tracking for mental health monitoring. Computer Communications, 35(11), 1306–1311.

    Google Scholar 

  181. Wijsman, J., Grundlehner, B., Liu, H., Hermens, H., Penders, J. (2011). Towards mental stress detection using wearable physiological sensors. In Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE, pp. 1798–1801. IEEE

  182. Yang, Z.,Wang, Z., Zhang, J., Huang, C., Zhang, Q. (2015) Wearables can afford: light-weight indoor positioning with visible light. In: Proceedings of the 13th Annual International Conference on Mobile Systems, Applications, and Services, pp. 317–330. ACM

  183. Lee, Y. H., & Medioni, G. (2016). RGB-D camera based wearable navigation system for the visually impaired. Computer Vision and Image Understanding, 149, 3–20.

    Google Scholar 

  184. Anzaldo, D. (2015) Wearable sports technology—market landscape and compute SoC trends. In: 2015 International SoC Design Conference (ISOCC), pp. 217–218. IEEE.

  185. Apple Inc. (2016). Apple Pay: simple, secure and private. https://www.apple.com/apple-pay/

  186. Visa Inc. (2016). Payment technology. https://www.visa.com.au/visa-everywhere/future-ofpayments.html

  187. IDC Research, Inc. (2016). IDC forecasts worldwide shipments of wearables to surpass 200 million in 2019, driven by strong smartwatch growth and the emergence of smarter watches. https://www.idc.com

  188. Gartner Inc. (2016) Gartner says worldwide wearable devices sales to grow 18.4% in 2016. http://www.gartner.com

  189. Wearable technology market (2017) Global opportunity analysis and industry forecast, 2014–2022. http://www.prnewswire.com/news-releases/

  190. Gravina, R., Alinia, P., Ghasemzadeh, H., & Fortino, G. (2016). Multi-sensor fusion in body sensor networks: State of-the-art and research challenges. Inf. Fusion, 35, 68–80. https://doi.org/10.1016/j.inffus.2016.09.005

    Article  Google Scholar 

  191. He, D., & Zeadally, S. (2015). Authentication protocol for an ambient assisted living system. IEEE Communications Magazine, 53(1), 71–77. https://doi.org/10.1109/MCOM.2015.7010518

    Article  Google Scholar 

  192. Wu, T., Wu, F., Redouté, J. M., & Yuce, M. R. (2017). An autonomous wireless body area network implementation towards IoT connected healthcare applications. IEEE Access Journal, 5, 11413–11422. https://doi.org/10.1109/ACCESS.2017.2716344

    Article  Google Scholar 

  193. Barakah, D.M., Ammad-uddin, M. (2012) A survey of challenges and applications of wireless body area network (WBAN) and role of a virtual doctor server in existing architecture, In Proceedings of the 3rd IEEE Intelligent Systems Modelling and Simulation (ISMS), pp. 214–219, doi: https://doi.org/10.1109/ISMS.2012.

  194. Antonescu, B., Basagni, S. (2013) Wireless body area Networks: challenges, trends and emerging technologies. In Proceedings of the 8th International Confer- ence on Body Area Networks (BodyNets), doi: https://doi.org/10.4108/icst.bodynets.2013.253722.

  195. Sicari, S., Rizzardi, A., Grieco, L. A., Piro, G., & Coen-Porisini, A. (2017). A policy enforce- ment framework for internet of things applications in the smart health. Smart Health, 3, 39–74.

    Google Scholar 

  196. Gope, P., & Hwang, T. (2016). BSN-Care: A secure IoT-based modern healthcare system using body sensor network. IEEE Sensors Journal, 16(5), 1368–1376.

    Google Scholar 

  197. La, A., Kumar, K.N. (2017). E-health application over 5G using content-centric net- working, In Proceedings of the International Conference on IEEE IoT and Ap- plication, pp. 1–5.

  198. Boukerche, A., & Ren, Y. (2009). A secure mobile healthcare system using trust-based multicast scheme. IEEE Journal on Selected Areas in Communications, 27(4), 387–399.

    Google Scholar 

  199. Iqbal, M.A., Bayoumi, M. (2016). A novel authentication and key agreement protocol for internet of things based resource-constrained body area sensors. In Proceedings of the IEEE International Conference on IEEE Future Internet of Things and Cloud Workshops, pp. 315–320 .

  200. Wu, L., Zhang, Y., Li, L., & Shen, J. (2016). Efficient and anonymous authentication scheme for wireless body area networks. Journal of Medical Systems, 40(6), 134.

    Google Scholar 

  201. Ara, A., Al-Rodhaan, M., Tian, Y., & Al-Dhelaan, A. (2017). A secure privacy-preserving data aggregation scheme based on bilinear ElGamal cryptosystem for remote health monitoring systems. IEEE Access, 5, 12601–12617.

    Google Scholar 

  202. Shen, J., Tan, H., Moh, S., Chung, I., Liu, Q., & Sun, X. (2015). Enhanced secure sensor association and key management in wireless body area networks. Journal of the Communications Network, 17(5), 453–462.

    Google Scholar 

  203. Wu, T., Wu, F., Redouté, J. M., & Yuce, M. R. (2017). An autonomous wireless body area net- work implementation towards IoT connected healthcare applications. IEEE Access, 5, 11413–11422.

    Google Scholar 

  204. Mehmood, N.Q., Culmone, R. (2015) An ANT + protocol based health care system. In Proceedings of the IEEE 29th International Conference on Advanced Information Networking and Applications Workshops, Gwangiu, pp. 193–198 .

  205. Omeni, O., Wong, A. C., Burdett, A. J., & Toumazou, C. (2008). Energy efficient medium access protocol for wireless medical body area sensor networks. IEEE Transactions on Biomedical Circuits and Systems, 2(4), 251–259.

    Google Scholar 

  206. Hoang, D.C., Tan, Y.K., Chng, H.B., Panda, S.K. (2009). Thermal energy harvesting from human warmth for wireless body area network in medical healthcare system, In Proceedings of the International Conference on IEEE Power Electronics and Drive Systems, PEDS 20 09, pp. 1277–1282

  207. Deepu, C. J., Heng, C. H., & Lian, Y. (2017). A hybrid data compression scheme for power reduction in wireless sensors for IoT. IEEE Transactions on Biomedical Circuits and Systems, 11(2), 245–254.

    Google Scholar 

  208. Ullah, S., & Kwak, K. S. (2012). An ultra-low-power and traffic-adaptive medium access control protocol for wireless body area network. Journal of Medical Systems, 36(3), 1021–1030.

    Google Scholar 

  209. Rahmani, A.M., Thanigaivelan, N.K., Gia, T.N., Granados, J., Negash, B., Lilje- berg, P., Tenhunen, H. (2015) Smart e-health gateway: bringing intelligence to inter- net-of-things based ubiquitous healthcare systems. In Proceedings of the 12th Annual IEEE Consumer Communications and Networking Conference, Las Vegas, pp. 826–834

  210. Wang, H., Choi, H.S., Agoulmine, N., Deen M.J., Hong, J.W. (2010) Information-based sensor tasking wireless body area networks in U-health systems. In Proceed- ings of the International Conference on IEEE Network and Service Management, Niagara Falls, 2010, pp. 517–522 .

  211. Chung, W.Y., Lee, Y.D., Jung, S.J. (2008). A wireless sensor network compatible wear- able u-healthcare monitoring system using integrated ECG, accelerometer and SpO 2, In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2008, pp. 1529–1532.

  212. Jeong, Y. S., & Shin, S. S. (2016). An IoT healthcare service model of a vehicle using implantable devices. Cluster Computer, 21, 1059–1068.

    Google Scholar 

  213. Al-Aubidy, K.M., Derbas, A.M., Al-Mutairi, A.W. (2016) Real-time patient health monitoring and alarming using wireless-sensor-network, In Proceedings of the 13thInternational Multi-Conference on IEEE Systems, Signals & Devices, pp. 416–423.

  214. Kisseleff, S., Akyildiz, I.F., Gerstacker, W. (2016) Distributed beamforming for magnetic induction based body area sensor networks, in: Proceedings of the Global Communications Conference, IEEE Washington, DC, USA, 2016, pp. 1–7.

  215. Satija, U., Ramkumar, B., & Manikandan, M. S. (2017). Real-time signal quality-aware ecg telemetry system for IoT-based health care monitoring. IEEE Internet of Things Journal, 4(3), 815–823.

    Google Scholar 

  216. Velrani, K.S., Geetha, G. (2016). Sensor based healthcare information system, In Proceedings of the Technological Innovations in ICT for Agriculture and Rural Development, IEEE, pp. 86–92.

  217. Bal, M., Abrishambaf, R. (2017). A system for monitoring hand hygiene compliance based-on Internet-of-Things, in: Proceedings of the IEEE International Conference on IEEE Industrial Technology, pp. 1348–1353

  218. Aljumah, A., Ahanger T. A. (2018) Fog computing and security issues: A review. 2018 7th International Conference on Computers Communications and Control (ICCCC), pp. 237–239

  219. Zhang L, Jia W, Wen S, Yao D. A man-in-the-middle attack on 3G-WLAN interworking. International Conference on Communications and Mobile Computing (CMC), Vol. 1, Zhangjiajie, China, April 2010; 121–125.

  220. Broadcom BCM 5354. (Available from: http://www.broadcom.com.) [Accessed on 2 April 2015].

  221. Wikipedia. Hooking, what is hooking? 2014. (Available from: http://en.wikipedia.org/wiki/Hooking) [Accessed on 2 April 2015].

  222. Greer N, Blank B, Depew B (2018) Impact engine Inc, Multimedia Communication System And Method. U.S. Patent Application 16/119,915

  223. Ackerman, M. J. (2007). Next generation networking: Distributed multimedia information for healthcare. Multimed Tools Applications, 33(1), 5–11.

    MathSciNet  Google Scholar 

  224. Cheung, S. C. S. (2015). Integrating multimedia into autism intervention. IEEE Multimedia, 22(4), 4–10.

    Google Scholar 

  225. AlhamidMF (2017) Investigation of mammograms in the cloud for smart healthcare.Multimed Tools Appl: pp. 1–13

  226. Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., & Ayyash, M. (2015). Internet of things: A survey on enabling technologies, protocols, and applications. IEEE Commun Survey Tutor, 17(4), 2347–2376.

    Google Scholar 

  227. Li, S., Da Xu, L., & Zhao, S. (2015). The internet of things: A survey. Information Systems Frontiers, 17(2), 243–259.

    Google Scholar 

  228. Scheuerman, W. E. (2014). Whistleblowing as civil disobedience: The case of Edward Snowden. Philo Social Crit, 40(7), 609–628.

    Google Scholar 

  229. Alassaf, N, Gutub, A., Parah, S.A., Ghamdi, M. (2018). Enhancing speed of SIMON: a light weight cryptographic algorithm for IoT applications, Multimed Tools Appl: pp. 1–25

  230. Mayron, L. M. (2010). Secure multimedia communications. IEEE Sec Privacy, 8(6), 76–79.

    Google Scholar 

  231. Wu, L., Du, X., & Fu, X. (2014). Security threats to mobile multimedia applications: Camera-based attacks on mobile phones. IEEE Communications Magazine, 52(3), 80–87.

    Google Scholar 

  232. Fernandez-Carames TM, Fraga-Lamas P (2018) A review on the use of Blockchain for the internet of things. IEEE Access

  233. Praveena D, Rangarajan P (2018). A machine learning application for reducing the security risks in hybrid cloud networks. Multimed Tools Appl: pp. 1–13

  234. Al-Taee, M.A., Al-Nuaimy, W., Al-Ataby, A., Muhsin, Z.J., Abood S.N. (2015) Mobile health platform for Diabetes management based on the Internet-of-things. IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies

  235. Gomes, B., Muniz, L., Silva, F., Rios, L.T., Endler M. (2015) A Comprehensive Cloud-based IoT Software Infrastructure for Ambient Assisted Living, International Conference on Cloud Computing Technologies and Applications,

  236. Ray P.P. (2014) Home Health Hub Internet of Things (H3IoT): An architectural framework for monitoring health of elderly people”. International Conference on Science, Engineering and Management Research.

  237. Murakami, A., Kobayashi, L.O.M.A U. Tachinardi, M.A. Gutierrez, S.S. Furuie and F.A. Pires (2004) Acesso a informações médicas através do uso de sistemas de computação móvel. Congresso Brasileiro deInformática na Saúde

  238. Matar, G., Lina, J., Carrier, J., Riley, A., Kaddoum, G. (2016). Internet of things in sleep monitoring: an application for posture recognition using supervised learning. 18th International Conference on e-Health Networking, Applications and Services

  239. Mano, L., Funes, M., Volpato, T., & Neto, J. (2016). Explorando tecnologias de IoT no contexto de Health Smart Home: Uma abordagem para detecção de quedas em pessoas idosas. Journal on Advances in Theoretical and Applied Informatics, 2, 46–57. [in Portuguese].

    Google Scholar 

  240. Mainetti, L., Patrono, L., Secco, A., Sergi, I. (2016) An IoT-aware AAL System for Elderly People.. International Multidisciplinary Conference on Computer and Energy Science

  241. Maia, P., Batista, T., Cavalcante, E., Baffa, A., Delicato, F. C., Pires, P. F., & Zomaya, A. (2014). A web platform for interconnecting body sensors and improving health care. Procedia Computer Science, 40, 135–142.

    Google Scholar 

  242. Machado, F.M., Koehler, I.M., Ferreira, M.S., Sovierzoski, M.A. (2016) An mHealth remote monitor system approach applied to MCC Using ECG Signal in an Android Application. In: Rocha Á., Correia A., Adeli H., Reis L., Mendonça Teixeira M. (Eds). New Advances in Information Systems and Technologies: Advances in Intelligent Systems and Computing, pp. 43–49.

  243. Ma, Y., Wang, Y., Yang, J., Miao, Y., & Li, W. (2016). Big health application system based on health Internet of things and big data. IEEE Access, 5, 7885–7897.

    Google Scholar 

  244. Kumar, P. D., Kumar, R. S., Sujatha, K., Ponmagal, R. S., Rajavarman, V. N. (2016) Big data analytics of IoT based health care monitoring system. In Proc. IEEE Uttar Pradesh Section Int. Conf. Elect. Comput. Electron. Eng. (UPCON), pp. 55–60.

  245. Manogaran, G., Varatharajan, R., Lopez, D., Kumar, P. M., Sundarasekar, R., & Thota, C. (2018). A new architecture of Internet of Things and big data ecosystem for secured smart healthcare monitoring and alerting system. Future Generations Computer System, 82, 375–387.

    Google Scholar 

  246. Ukil, S. Bandyoapdhyay, C. Puri, and A. Pal (2016) IoT healthcare analytics: The importance of anomaly detection. In: Proc. IEEE 30th Int. Conf. Adv. Inf. Netw. Appl (AINA), pp. 994–997.

  247. Plageras, A. P. et al. (2017). Efficient large-scale medical data (eHealth big data) analytics in Internet of Things,” in Proc. IEEE 19th Conf. Bus. Informat. (CBI) pp. 21–27

  248. Elhoseny, M., et al. (2018). Secure medical data transmission model for IoTbased healthcare systems. IEEE Access, 6, 20596–20608.

    Google Scholar 

  249. Chen, M., Yang, J., Zhou, J., Hao, Y., Zhang, J., & Youn, C. H. (2018). 5Gsmart diabetes: Toward personalized diabetes diagnosis with healthcare big data clouds. IEEE Communications Magazine, 56(4), 16–23.

    Google Scholar 

  250. Luo, E., Bhuiyan, M. Z. A., Wang, G., Rahman, M. A., Wu, J., & Atiquzzaman, M. (2018). PrivacyProtector: Privacy-protected patient data collection in IoT-based healthcare systems. IEEE Communications Magazine, 56(2), 163–168.

    Google Scholar 

  251. Alamri, A. (2019). Big data with integrated cloud computing for prediction of health conditions. In Proc. Int. Conf. Platform Technol. Service (PlatCon), pp. 1–6.

  252. Sharma, S., Chen, K., & Sheth, A. (2018). Toward practical privacypreserving analytics for IoT and cloud-based healthcare systems. IEEE Internet Computing, 22(2), 42–51.

    Google Scholar 

  253. Vuppalapati, A., Ilapakurti, A., Kedari, S. (2016) The role of big data in creating sense EHR, an integrated approach to create next generation mobile sensor and wearable data driven electronic health record (EHR),” In Proc. IEEE 2nd Int. Conf. Big Data Comput. Service Appl. (BigDataService), pp. 293–296.

  254. Yang, Y., Zheng, X., Guo, W., Liu, X., & Chang, V. (2019). Privacy-preserving smart IoT-based healthcare big data storage and self-adaptive access control system. Information Sciences, 479, 567–592.

    Google Scholar 

  255. Sahoo, P. K., Mohapatra, S. K., & Wu, S. (2016). Analyzing healthcare big data with prediction for future health condition. IEEE Access, 4, 9786–9799.

    Google Scholar 

  256. Malek, Y. N., et al. (2017). On the use of IoT and big data technologies for real-time monitoring and data processing. Procedia Comput. Sci., 113, 429–434.

    Google Scholar 

  257. Yacchirema, A. C., Sarabia-Jácome, D., Palau, C. E., & Esteve, M. (2018). A smart system for sleep monitoring by integrating IoT with big data analytics. IEEE Access, 6, 35988–36001.

    Google Scholar 

  258. Hossain, M. S., & Muhammad, G. (2016). Healthcare big data voice pathology assessment framework. IEEE Access, 4, 7806–7815.

    Google Scholar 

  259. Yassine, S. Singh, and A. Alamri (2017) Mining human activity patterns from smart home big data for health care applications. IEEE Access, vol. 5, pp. 13131–13141.

  260. Arruda, de D., Hancke, G. P. (2016). Wearable device localisation using machine learning techniques. In Proc. IEEE 25th Int. Symp. Ind. Electron. (ISIE), pp. 1110–1115.

  261. Walinjkar, A., Woods, J. (2017). Personalized wearable systems for realtime ECG classification and healthcare interoperability: Real-time ECG classification and FHIR interoperability. In Proc. Internet Technol. Appl. (ITA), Wrexham, U.K., pp. 9–14.

  262. Savazzi, S., Kianoush, S., Rampa, R., Spagnolini U (2018). Cellular data analytics for detection and discrimination of body movements. IEEE Access, vol. 6, Art. no. 51484.

  263. Satija, U., Ramkumar, B., & Manikandan, M. S. (2017). Real-time signal quality-aware ECG telemetry system for IoT-based health care monitoring. IEEE Internet of Things Journal, 4(3), 815–823.

    Google Scholar 

  264. Kiani, F. (2017) Reinforcement learning based routing protocol for wireless body sensor networks. In Proc. IEEE 7th Int. Symp. Cloud Service Comput. (SC2), pp. 71–78.

  265. Yang, G., et al. (2018). An IoT-enabled stroke rehabilitation system based on smart wearable armband and machine learning. IEEE J. Transl. Eng. Health Med., 6, 1–10.

    Google Scholar 

  266. Ghate, V. V., & Vijayakumar, V. (2018). Machine learning for data aggregation in WSN: A survey. Int. J. Pure Appl. Math., 118(24), 1–12.

    Google Scholar 

  267. Hsu, C. C., Wang, M. Y., Shen, H. C. H.., Chiang, R. H., Wen, C. H. P. (2017) FallCare+: An IoT surveillance system for fall detection. In Proc. Int. Conf. Appl. Syst. Innov. (ICASI), pp. 921–922.

  268. Firouzi, F. Farahani, B., Ibrahim, M., Chakrabarty, K. (2018). From EDA to IoT eHealth: Promises, challenges, and solutions. IEEE Trans. Comput.-Aided Design Integr. Circuits Syst., vol. 37, no. 12, pp. 2965–2978

  269. Anupama, K. R., Adarsh, R., Pahwa, P., Ramachandran, A. (2018) Machine learning-based techniques for fall detection in geriatric healthcare systems, In Proc. 9th Int. Conf. Inf. Technol. Med. Educ. (ITME), pp. 232–237.

  270. Ara, A., Ara, A. (2017) Case study: Integrating IoT, streaming analytics and machine learning to improve intelligent diabetes management system. In Proc. Int. Conf. Energy Commun. Data Anal. Soft Comput. (ICECDS), pp. 3179–3182.

  271. Hong, J., Yoon, J. (2017). Multivariate time-series classification of sleep patterns using a hybrid deep learning architecture. In Proc. IEEE 19th Int. Conf. e-Health Netw. Appl. Services (Healthcom), pp. 1–6.

  272. Kanagasabai, P. S., Gautam, R., Rathna, G. N. (2016). Brain–computer interface learning system for quadriplegics. In Proc. IEEE 4th Int. Conf. MOOCs Innov. Technol. Educ. (MITE), pp. 258–262.

  273. Matar, G., Lina, J., Carrier, J., Riley, J., Kaddoum, G. (2016). Internet of Things in sleep monitoring: An application for posture recognition using supervised learning. In Proc. IEEE 18th Int. Conf.e-Health Netw. Appl. Services (Healthcom), pp. 1–6.

  274. Shrivastwa, R. R., Pudi, V., Chattopadhyay, A. (2018) An FPGA-based brain computer interfacing using compressive sensing and machine learning. In Proc. IEEE Comput. Soc. Annu. Symp. VLSI (ISVLSI), Hong Kong, pp. 726–731.

  275. Fafoutis, X., Marchegiani, L., Elsts, A., Pope, J., Piechocki, R., Craddock, I. (2018) Extending the battery lifetime of wearable sensors with embedded machine learning,” In Proc. IEEE 4th World Forum Internet Things (WF-IoT), Singapore, 2018, pp. 269–274.

  276. Ravì, D., Wong, C., Lo, B., & Yang, G. (2017). A deep learning approach to on-node sensor data analytics for mobile or wearable devices. IEEE J. Biomed. Health Informat., 21(1), 56–64.

    Google Scholar 

  277. Psychoula et al. (2018) A deep learning approach for privacy preservation in assisted living,” in Proc. IEEE Int. Conf. Pervasive Comput. Commun. Workshops (PerCom Workshops), Athens, Greece, pp. 710–715.

  278. Knickerbocker et al (2018) Heterogeneous integration technology demonstrations for future healthcare, IoT, and AI computing solutions,” In Proc. IEEE 68th Electron. Compon. Technol. Conf. (ECTC), San Diego, CA, USA, 2018, pp. 1308–1313.

  279. Ahmed, T. Ahmed, F., Le Moullec, Y. (2016) Optimization of channel allocation in wireless body area networks by means of reinforcement learning,” In Proc. IEEE Asia–Pac. Conf. Wireless Mobile (APWiMob), Bandung, Indonesia, pp. 120–123.

  280. Verner, A., Butvinik, D. (2017). A machine learning approach to detecting sensor data modification intrusions in WBANs,” In Proc. 16th IEEE Int. Conf. Mach. Learn. Appl. (ICMLA), pp. 161–169.

  281. Negra, R., Jemili, I., Zemmari, A., Mosbah, M., Belghith, A. (2018). WBAN path loss based approach for human activity recognition with machine learning techniques. In Proc. 14th Int. Wireless Commun. Mobile Comput. Conf. (IWCMC), pp. 470–475.

  282. Shanthamallu, U. S., Spanias, A., Tepedelenlioglu, C., Stanley, M. (2017). A brief survey of machine learning methods and their sensor and IoT applications,” In Proc. 8th Int. Conf. Inf. Intell. Syst. Appl. (IISA), Larnaca, Cyprus, pp. 1–8.

  283. Asthana, S., Megahed, A., Strong, R. (2017). A recommendation system for proactive health monitoring using IoT and wearable technologies,” In Proc. IEEE Int. Conf. AI Mobile Services (AIMS), Honolulu, HI, USA, pp. 14–21.

  284. Jagadish, B., Kiran, M. P. R. S., Rajalakshmi R. (2017). A novel system architecture for brain controlled IoT enabled environments. In Proc. IEEE 19th Int. Conf. e-Health Netw. Appl. Services (Healthcom), pp. 1–5.

  285. Yang, Y., et al. (2019). GAN-based semi-supervised learning approach for clinical decision support in health-IoT platform. IEEE Access, 7, 8048–8057.

    Google Scholar 

  286. Zhang, X., Yao, L., Zhang, S., Kanhere, S., Sheng, M., & Liu, Y. (2019). Internet of things meets brain–computer interface: A unified deep learning framework for enabling human-thing cognitive interactivity. IEEE Internet of Things Journal, 6(2), 2084–2092.

    Google Scholar 

  287. Ahmadi, H., Arji, G., Shahmoradi, L., Safdari, R., Nilashi, M., & Alizadeh, M. (2019). The application of internet of things in healthcare: A systematic literature review and classification. Universal Access in the Information Society, 18(4), 837–869.

    Google Scholar 

  288. Tanwar, S, Tanwar (2021) Fog computing for Healthcare 4.0 environments. Springer International Publishing

  289. Ketu, S., & Mishra, P. K. (2021). Internet of Healthcare Things: A contemporary survey.". Journal of Network and Computer Applications, 192, 103179.

    Google Scholar 

  290. Dhanvijay, M. M., & Patil, S. C. (2019). Internet of things: A survey of enabling technologies in healthcare and its applications. Computer Networks, 153, 113–131.

    Google Scholar 

  291. Qadri, Y. A., Nauman, A., Zikria, Y. B., Vasilakos, A. V., & Kim, S. W. (2020). The future of healthcare internet of things: a survey of emerging technologies. IEEE Communications Surveys & Tutorials, 22, 1121–1167.

    Google Scholar 

  292. Zeadally, S., & Bello, O. (2021). Harnessing the power of Internet of Things based connectivity to improve healthcare. Internet of Things, 14, 100074.

    Google Scholar 

  293. Pramanik, P. K. D., Bijoy Kumar, U., Saurabh, P., Tanmoy, P (2019) Internet of things, smart sensors, and pervasive systems: Enabling connected and pervasive healthcare." In Healthcare data analytics and management, pp. 1–58. Academic Press

  294. Ghosh, U., Chinmay, C., Lalit, G., Gautam, S (2022). Intelligent Internet of Things for Healthcare and Industry.

  295. Bhuiyan, M. N., Md Mahbubur Rahman, Md Masum B., Dipanita, S. (2021). Internet of Things (IoT): A review of its enabling technologies in healthcare applications, standards protocols, security and market opportunities. IEEE Internet of Things Journal

  296. Nauman, A., Yazdan Ahmad, Q., Rashid, A., Sung Won, K. (2021) Machine learning-enabled Internet of Things for medical informatics. In Machine Learning, Big Data, and IoT for Medical Informatics, pp. 111–126. Academic Press.

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Arora, D., Gupta, S. & Anpalagan, A. Evolution and Adoption of Next Generation IoT-Driven Health Care 4.0 Systems. Wireless Pers Commun 127, 3533–3613 (2022). https://doi.org/10.1007/s11277-022-09932-3

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