Nothing Special   »   [go: up one dir, main page]

Skip to main content

An Architecture Proposal to Support E-Healthcare Notifications

  • Conference paper
  • First Online:
Advanced Information Networking and Applications (AINA 2023)

Abstract

By constantly focusing on the demands of everyday life, people easily put their health in second place. Such behavior can lead to both physical and psychological risks. This work proposes an architecture capable of sending users notifications regarding their health, thus helping them become aware of their habits. The research was designed to develop a system based on the Fog-Cloud paradigm and machine learning algorithms. The system collects the user’s heart rate data and processes it to generate notifications regarding unusual heart rate frequency. A feasibility experiment was conducted for three months, collecting real data from the user. The generated results showed the moments in the day when the user had more instability, thus indicating possible moments for a notification to be sent, demonstrating the proposal’s viability.

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

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Similar content being viewed by others

References

  1. Android api reference  —  google fit  —  google developers. https://developers.google.com/fit/android/reference

  2. Alpaydin, E.: Introduction to Machine Learning. MIT press, Cambridge (2020)

    MATH  Google Scholar 

  3. Artazcoz, L., Cortès, I., Escribà-Agüir, V., Cascant, L., Villegas, R.: Understanding the relationship of long working hours with health status and health-related behaviours. J. Epidemiol. Commun. Health 63(7), 521–527 (2009). https://doi.org/10.1136/jech.2008.082123

    Article  Google Scholar 

  4. Cao, K., Liu, Y., Meng, G., Sun, Q.: An overview on edge computing research. IEEE Access 8, 85714–85728 (2020). https://doi.org/10.1109/ACCESS.2020.2991734

    Article  Google Scholar 

  5. Chintapalli, S., et al.: Benchmarking streaming computation engines: Storm, flink and spark streaming. In: 2016 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), pp. 1789–1792. IEEE (2016)

    Google Scholar 

  6. Ciabattoni, L., Ferracuti, F., Longhi, S., Pepa, L., Romeo, L., Verdini, F.: Real-time mental stress detection based on smartwatch. In: 2017 IEEE International Conference on Consumer Electronics (ICCE), pp. 110–111. IEEE (2017). https://doi.org/10.1109/ICCE.2017.7889247

  7. Deng, R., Lu, R., Lai, C., Luan, T.H., Liang, H.: Optimal workload allocation in fog-cloud computing toward balanced delay and power consumption. IEEE Internet Things J. 3(6), 1171–1181 (2016). https://doi.org/10.1109/AINA.2010.187

    Article  Google Scholar 

  8. Eysenbach, G., et al.: What is e-health? J. Med. Internet Res. 3(2), e833 (2001). https://doi.org/10.2196/jmir.3.2.e20

  9. Fbiego. Fbiego/dt78-app-android: Alternative app for the dt78 smartwatch. https://github.com/fbiego/DT78-App-Android

  10. Firouzi, F., Farahani, B., Ibrahim, M., Chakrabarty, K.: Keynote paper: from eda to iot ehealth: promises, challenges, and solutions. IEEE Trans. Comput.-Aided Des. Integr. Circ. Syst. 37(12), 2965–2978 (2018). https://doi.org/10.1109/TCAD.2018.2801227

  11. Gomes, E., Costa, F., De Rolt, C., Plentz, P., Dantas, M.: A survey from real-time to near real-time applications in fog computing environments. In: Telecom, vol. 2, pp. 489–517. MDPI (2021). https://doi.org/10.3390/telecom2040028

  12. Gravina, R., Fortino, G.: Wearable body sensor networks: state-of-the-art and research directions. IEEE Sensors J. 21(11), 12511–12522 (2021). https://doi.org/10.1109/jsen.2020.3044447

    Article  Google Scholar 

  13. Di iorio Silva, G., Sergio, W.L., Ströele, V., Dantas, M.A.R.: ASAP - academic support aid proposal for student recommendations. In: Barolli, L., Woungang, I., Enokido, T. (eds.) AINA 2021. LNNS, vol. 226, pp. 40–53. Springer, Cham (2021). https://doi.org/10.1007/978-3-030-75075-6_4

    Chapter  Google Scholar 

  14. Di iorio Silva, G., Sergio, W.L., Ströele, V., Dantas, M.A.R.: A watchdog proposal to a personal e-health approach. In: Barolli, L., Hussain, F., Enokido, T. (eds.) AINA 2022. LNNS, vol. 450, pp. 81–94. Springer, Cham (2022). https://doi.org/10.1007/978-3-030-99587-4_8

    Chapter  Google Scholar 

  15. Kim, H., Xie, B.: Health literacy in the ehealth era: a systematic review of the literature. Pat. Educ. Counsel. 100(6), 1073–1082 (2017). https://doi.org/10.1016/j.pec.2017.01.015

    Article  Google Scholar 

  16. Kiran, M., Murphy, P., Monga, I., Dugan, J., Baveja, S.S.: Lambda architecture for cost-effective batch and speed big data processing. In 2015 IEEE International Conference on Big Data (Big Data), pp. 2785–2792. IEEE (2015). https://doi.org/10.1109/BigData.2015.7364082

  17. Klein, A., Lehner, W.: Representing data quality in sensor data streaming environments. J. Data Inf. Qual. (JDIQ) 1(2), 1–28 (2009). https://doi.org/10.1145/1577840.1577845

  18. Larcher, L., Stroele, V., Dantas, M., Bauer, M.: Event-driven framework for detecting unusual patterns in AAL environments. In: 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS). IEEE (2020). https://doi.org/10.1109/cbms49503.2020.00065

  19. Miloslavskaya, N., Tolstoy, A.: Big data, fast data and data lake concepts. Procedia Comput. Sci. 88, 300–305 (2016). https://doi.org/10.1016/j.procs.2016.07.439

  20. Munir, A., Kansakar, P., Khan, S.U.: IFCIOT: integrated fog cloud IoT: a novel architectural paradigm for the future internet of things. IEEE Cons. Electron. Maga. 6(3), 74–82 (2017). https://doi.org/10.1109/MCE.2017.2684981

    Article  Google Scholar 

  21. Norman, C.D., Skinner, H.A.: ehealth literacy: essential skills for consumer health in a networked world. J. Med. Internet Res. 8(2), e506 (2006). https://doi.org/10.2196/jmir.8.2.e9

  22. Pantelopoulos, A., Bourbakis, N.G.: A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans. Syst. Man Cybern. Part C (Appl. Rev.) 40(1), 1–12 (2010). https://doi.org/10.1109/TSMCC.2009.2032660

  23. Prasad, B., Thakur, C.: Chronic overworking: cause extremely negative impact on health and quality of life, pp. 11–15 (2019)

    Google Scholar 

  24. Shahverdi, E., Awad, A., Sakr, S.: Big stream processing systems: an experimental evaluation. In: 2019 IEEE 35th International Conference on Data Engineering Workshops (ICDEW), pp. 53–60. IEEE (2019)

    Google Scholar 

  25. Sutton, A.: Measuring the effects of self-awareness: construction of the self-awareness outcomes questionnaire. Eur. J. Psychol. 12(4), 645 (2016). https://doi.org/10.5964/ejop.v12i4.1178

    Article  MathSciNet  Google Scholar 

  26. Uddin, M.Z., Khaksar, W., Torresen, J.: Ambient sensors for elderly care and independent living: a survey. Sensors 18(7) (2018). https://www.mdpi.com/1424-8220/18/7/2027, https://doi.org/10.3390/s18072027

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Victor Ströele .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sergio, W.L., di Iorio Silva, G., Ströele, V., Dantas, M.A.R. (2023). An Architecture Proposal to Support E-Healthcare Notifications. In: Barolli, L. (eds) Advanced Information Networking and Applications. AINA 2023. Lecture Notes in Networks and Systems, vol 661. Springer, Cham. https://doi.org/10.1007/978-3-031-29056-5_16

Download citation

Publish with us

Policies and ethics