An E-health system for monitoring elderly health based on Internet of Things and Fog computing

  • Hafedh Ben HassenEmail author
  • Wael Dghais
  • Belgacem Hamdi


With the significant increase in the number of elderly in the world and the resulting health problems of these increasing, finding technical solutions to address this problem has become a pressing necessity, particularly in the field of health care. This paper proposes an e-health system for monitoring elderly health based on the Internet of Things (IoT) and Fog computing. The system was developed using Mysignals HW V2 platform and an Android app that plays the role of Fog server, which enables the collection of physiological parameters and general health parameters from elderly periodically. This Android app enables also the elderly and their families to follow their health, and they can also communicate with health care providers (administrators and doctors) and receive recommendations, notifications and alerts. By evaluating this system, we find the most users they consider useful, easy to use and learn, suggesting that our proposal can improve the quality of health care for elderly.


E-health Elderly health monitoring Biomedical sensors Internet of Things (IoT) Fog computing 



This project is carried out under the MOBIDOC scheme, funded by the EU through the EMORI program and managed by the ANPR.


  1. 1.
    García-Sánchez P, González J, Mora AM, Prieto A. Deploying intelligent e-health services in a mobile gateway. Expert Syst Appl. 2013;40(4):1231–9. Scholar
  2. 2.
    Morabia A, Abel T. The WHO report “preventing chronic diseases: a vital investment” and us. Sozial- und Präventivmedizin SPM. 2006;51(2):74. Scholar
  3. 3.
    Khan ZA, Sivakumar S, Phillips W, Aslam N. A new patient monitoring framework and Energy-aware Peering Routing Protocol (EPR) for Body Area Network communication. J Ambient Intell Humaniz Comput. 2013;5(3):409–23. Scholar
  4. 4.
    Kao HY, Wei CW, Yu MC, Liang TY, Wu WH, et al. Integrating a mobile health applications for self-management to enhance Telecare system. Telemat Inform. 2018;35(4):815–25. Scholar
  5. 5.
    Iyengar A, Kundu A, Pallis G. Healthcare informatics and privacy. IEEE Internet Comput. 2018;22(2):29–31. Scholar
  6. 6.
    He D, Ye R, Chan S, Guizani M, Xu Y. Privacy in the internet of things for smart healthcare. IEEE Commun Mag. 2018;56(4):38–44. Scholar
  7. 7.
    Sundarasekar R, Thanjaivadivel M, Manogaran G, Kumar PM, Varatharajan R, et al. Internet of things with maximal overlap discrete wavelet transform for remote health monitoring of abnormal ECG signals. J Med Syst. 2018;42(11):228. Scholar
  8. 8.
    Rodrigues JJPC, Segundo DBDR, Junqueira HA, Sabino MH, Prince RM, et al. Enabling technologies for the internet of health things. IEEE Access. 2018;6:13129–41. Scholar
  9. 9.
    Yami MA, Schaefer D. Fog computing as a complementary approach to cloud computing. In: IEEE international conference on computer and information sciences (ICCIS), Sakaka, Saudi Arabia; 2019.
  10. 10.
    Bellavista P, Berrocal J, Corradi A, Das SK, Foschini L, et al. A survey on fog computing for the Internet of Things. Pervasive Mob Comput. 2019;52:71–99. Scholar
  11. 11.
    Hallfors NG, Alhawari M, Jaoude MA, Kifle Y, Saleh H, et al. Graphene oxide: nylon ECG sensors for wearable IoT healthcare-nanomaterial and SoC interface. Analog Integr Circuits Signal Process. 2018;96(2):253–60. Scholar
  12. 12.
    Romero LE, Chatterjee P, Armentano RL. An IoT approach for integration of computational intelligence and wearable sensors for Parkinson’s disease diagnosis and monitoring. Health Technol. 2016;6(3):167–72. Scholar
  13. 13.
    Varatharajan R, Manogaran R, Priyan MK, Sundarasekar R. Wearable sensor devices for early detection of Alzheimer disease using dynamic time warping algorithm. Cluster Comput. 2017;21(1):681–90. Scholar
  14. 14.
    Cornet VP, Holden RJ. Systematic review of smartphone-based passive sensing for health and wellbeing. J Biomed Inform. 2018;77:120–32. Scholar
  15. 15.
    Hussain M, Zaidan A, Zidan B, Iqbal S, Ahmed M, et al. Conceptual framework for the security of mobile health applications on android platform. Telemat Inform. 2018;35(5):1335–54. Scholar
  16. 16.
    Reza T, Shoilee SBA, Akhand SM, Khan MM. Development of android based pulse monitoring system. In: IEEE second international conference on electrical, computer and communication technologies (ICECCT), Coimbatore, India; 2017.
  17. 17.
    Wartzek T, Czaplik M, Antink CH, et al. UnoViS: the MedIT public unobtrusive vital signs database. Health Inf Sci Syst. 2015;3:2. Scholar
  18. 18.
    Weller RS, Foard KL, Harwood TN. Evaluation of a wireless, portable, wearable multi-parameter vital signs monitor in hospitalized neurological and neurosurgical patients. J Clin Monit Comput. 2017;32(5):945–51. Scholar
  19. 19.
    Fajkus M, Nedoma J, Martinek R, Vasinek V, Nazeran H, et al. A non-invasive multichannel hybrid fiber-optic sensor system for vital sign monitoring. Sensors. 2017;17(12):111. Scholar
  20. 20.
    Sadek I, Seet E, Biswas J, Abdulrazak B, Mokhtari M. Nonintrusive vital signs monitoring for sleep apnea patients: a preliminary study. IEEE Access. 2018;6:2506–14. Scholar
  21. 21.
    Fatmi H, Hussain S, Al-Rubaie A. Secure and cost-effective remote monitoring health-guard system. In: IEEE Canada international humanitarian technology conference (IHTC), Toronto, ON, Canada; 2017.
  22. 22.
    Lounis A, Hadjidj A, Bouabdallah A, Challal Y. Healing on the cloud: secure cloud architecture for medical wireless sensor networks. Future Gener Comput Syst. 2016;55:266–77. Scholar
  23. 23.
    Escobar LJV, Salinas SA. e-Health prototype system for cardiac telemonitoring. In: IEEE 38th annual international conference of the IEEE engineering in medicine and biology society (EMBC), Orlando, FL, USA; 2016.
  24. 24.
    Mahmud R, Kotagiri R, Buyya R. Fog computing: a taxonomy, survey and future directions. In: Di Martino B, Li KC, Yang L, Esposito A, editors. Internet of everything. Internet of things (technology, communications and computing). Singapore: Springer; 2018. p. 103–30. Scholar
  25. 25.
    Mukherjee M, Shu L, Wang D. Survey of fog computing: fundamental, network applications, and research challenges. IEEE Commun Surv Tutor. 2018;20(3):1826–57. Scholar
  26. 26.
    Negash B, Gia TN, Anzanpour A, Azimi I, Jiang M, et al. Leveraging fog computing for healthcare IoT. In: Rahmani A, Liljeberg P, Preden JS, Jantsch A, editors. Fog computing in the internet of things. Cham: Springer; 2017. p. 145–69. Scholar
  27. 27.
    Vijayakumar V, Malathi D, Subramaniyaswamy V, Saravanan P, Logesh R. Fog computing-based intelligent healthcare system for the detection and prevention of mosquito-borne diseases. Comput Hum Behav. 2018;100:275–85. Scholar
  28. 28.
    Jagadeeswari V, Subramaniyaswamy V, Logesh R, et al. A study on medical Internet of Things and Big Data in personalized healthcare system. Health Inf Sci Syst. 2018;6:14. Scholar
  29. 29.
    Verma P, Sood SK. Fog assisted-IoT enabled patient health monitoring in smart homes. IEEE Internet Things J. 2018;5(3):1789–96. Scholar
  30. 30.
    Wang H, Wang Y, Taleb T, Jiang X. Editorial: special issue on security and privacy in network computing. World Wide Web. 2019.
  31. 31.
    Iqbal S, Kiah MLM, Zaidan AA, Zaidan BB, et al. Real-time-based E-health systems: design and implementation of a lightweight key management protocol for securing sensitive information of patients. Health Technol. 2019;9(2):93–111. Scholar
  32. 32.
    Azeta AA, Omoregbe NA, Misra S, Iboroma DA, et al. Preserving patient records with biometrics identification in e-Health systems. In: Shukla R, Agrawal J, Sharma S, Singh Tomer G, editors. Data, engineering and applications. Singapore: Springer; 2019. p. 181–91. Scholar
  33. 33.
    Qin Y, Sheng QZ, Falkner NJG, Dustdar S, et al. When things matter: a survey on data-centric internet of things. J Netw Comput Appl. 2016;64:137–53. Scholar
  34. 34.
    Elkhodr M, Alsinglawi B, Alshehri M. A privacy risk assessment for the internet of things in healthcare. EAI/Springer innovations in communication and computing. In: Khan F, Jan M, Alam M, editors. Applications of intelligent technologies in healthcare. Cham: Springer; 2018. p. 47–54. Scholar
  35. 35.
    Fazeldehkordi E, Owe O, Noll J. Security and privacy in IoT systems: a case study of healthcare products. In: 13th international symposium on medical information and communication technology (ISMICT), Oslo, Norway; 2019.
  36. 36.
    Martins P, Abbasi M, Sá F. A study over NoSQL performance. In: Rocha Á, Adeli H, Reis L, Costanzo S, editors. New knowledge in information systems and technologies. WorldCIST’19. Advances in intelligent systems and computing, vol. 2019. Cham: Springer; 2019. p. 603–11. Scholar
  37. 37.
    Ma Z, Yan L. Towards massive RDF storage in NoSQL databases. In: Advances in data mining and database management emerging technologies and applications in data processing and management. IGI Global; 2019. pp. 263-284. Scholar
  38. 38.
    Batra R. A history of SQL and relational databases. In: SQL Primer. Berkeley: Apress; 2018. pp. 183–187. Scholar
  39. 39.
    Manoj AS, Hussain MA, Teja PS. Patient health monitoring using IoT. In: Advances in healthcare information systems and administration. IGI Global; 2019. pp. 30-45. Scholar
  40. 40.
    Maria AR, Sever P, Suciu G. MIoT applications for wearable technologies used for health monitoring. In: IEEE 10th international conference on electronics, computers and artificial intelligence (ECAI), Iasi, Romania; 2018.
  41. 41.
    Barzilai N, Cuervo AM, Austad S. Aging as a biological target for prevention and therapy. JAMA. 2018;320(13):1321. Scholar
  42. 42.
    Haveman M. Aging and physical health. In: Prasher V, Janicki M, editors. Physical health of adults with intellectual and developmental disabilities. Cham: Springer; 2018. p. 305–33. Scholar
  43. 43.
    Dantu K, Ko SY, Ziarek L. RAINA: reliability and adaptability in android for fog computing. IEEE Commun Mag. 2017;55(4):41–5. Scholar
  44. 44.
    Guan Y, Shao J, Wei G, Xie M. Data security and privacy in fog computing. IEEE Netw. 2018;32(5):106–11. Scholar
  45. 45.
    Gu L, Zeng D, Guo S, Barnawi A, Xiang Y. Cost efficient resource management in fog computing supported medical cyber-physical system. IEEE Trans Emerg Top Comput. 2017;5(1):108–19. Scholar
  46. 46.
    Abdul W, Ali Z, Ghouzali S, Alfawaz B, Muhammad G, et al. Biometric security through visual encryption for fog edge computing. IEEE Access. 2017;5:5531–8. Scholar
  47. 47.
    Alrawais A, Alhothaily A, Hu C, Xing X, Cheng X. An attribute-based encryption scheme to secure fog communications. IEEE Access. 2017;5:9131–8. Scholar
  48. 48.
    Mardan A. Intro to MongoDB. In: Full Stack JavaScript. Berkeley: Apress; 2018. pp. 239–256. Scholar
  49. 49.
    Schreibmann V, Braun P. Model-driven development of RESTful APIs. In: Proceedings of the 11th international conference on web information systems and technologies. SCITEPRESS—Science and and Technology Publications; 2015.
  50. 50.
    Chaniotis IK, Kyriakou KID, Tselikas ND. Is Node.js a viable option for building modern web applications? A performance evaluation study. Computing. 2014;97(10):1023–44. Scholar
  51. 51.
    Bangare SL, Gupta S, Dalal M, Inamdar A. Using Node.Js to build high speed and scalable backend database server. Int J Res Advent Technol. 2016;4:61–4.Google Scholar
  52. 52.
    Lewis JR. The system usability scale: past, present, and future. Int J Hum-Comput Interact. 2018;34(7):577–90. Scholar
  53. 53.
    Kaya A, Ozturk R, Gumussoy CA. Usability measurement of mobile applications with system usability scale (SUS). In: Calisir F, Cevikcan E, Camgoz AH (eds) Industrial engineering in the big data era. Lecture notes in management and industrial engineering. Cham: Springer; 2019. pp. 389-400. Scholar
  54. 54.
    Zahidi Z, Lim YP, Woods PC. Understanding the user experience (UX) factors that influence user satisfaction in digital culture heritage online collections for non-expert users. In: IEEE 2014, science and information conference, London, UK; 2014.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Electronic & Microelectronics’ LAB, Faculty of Sciences of MonastirUniversity of MonastirMonastirTunisia
  2. 2.Department of Electrical Engineering, National Engineering School of MonastirUniversity of MonastirMonastirTunisia
  3. 3.Department of Electronics, Higher Institute of Applied Science and Technology of SousseUniversity of SousseSousseTunisia

Personalised recommendations