Skip to main content
SpringerLink
Log in

An Evaluative Review on Various Tele-Health Systems Proposed in COVID Phase

  • Conference paper
  • First Online:
Computational Intelligence in Pattern Recognition (CIPR 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 480))

  • 551 Accesses

Abstract

With the rise of Covid-19, the importance of health monitoring has risen to a new peak. Keeping a check on the symptoms of covid is an integral part of our lifestyle now. Using Tele-Health systems can quickly achieve this feat. The Tele-Health field has vastly improved in the span of the uprise of the pandemic and has helped provide medical and non-medical individuals with the help they require. Much work has been done in this field, integrating IoT with the medical field to monitor an individual’s physical parameters efficiently and safely remotely. We have done a systematic review of the works that have helped develop this field during the pandemic. Bringing forward the pros and cons of these systems, we try to draw a clear picture to clearly understand the systems that have helped improve our daily lifestyle over this pandemic period.

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 189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 249.99
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. Wang, W., Sun, L., Liu, T., Lai, T.: The use of E-health during the COVID-19 pandemic: a case study in China’s Hubei province. Health Sociol. Rev. 1–17 (2021). https://doi.org/10.1080/14461242.2021.1941184. Epub ahead of print. PMID: 34161186

  2. Bhowmik, T., Mojumder, R., Ghosh, D., Banerjee, I.: IoT based smart home-health monitoring system using dempster-shafer evidence theory for pandemic situation. In: 23rd International Conference on Distributed Computing and Networking (ICDCN 2022), pp. 260–265. Association for Computing Machinery, New York (2022). https://doi.org/10.1145/3491003.3493232

  3. Bhowmik, T., Mojumder, R., Banerjee, I., Bhattacharya, A., Das, G.: IoT based data aggregation method for E-health monitoring system. In: International Conference on Computing Communication and Networking Technologies (ICCCNT) (2021). https://doi.org/10.1109/ICCCNT51525.2021.9579885

  4. Baskaran, K., Baskaran, P., Rajaram, V., Kumaratharan, N.: IoT based COVID preventive system for work environment. In: Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), pp. 65–71 (2020). https://doi.org/10.1109/I-SMAC49090.2020.9243471.

  5. Choyon, M.M.S., Rahman, M., Kabir, Md.M., Mridha, M.F.: IoT based health monitoring & automated predictive system to confront COVID-19. In: 17th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET), pp. 189–193 (2020). https://doi.org/10.1109/HONET50430.2020.9322811

  6. Kamarozaman, N.B., Awang, A.H.: IOT COVID-19 portable health monitoring system using Raspberry Pi, node-red and ThingSpeak. In: IEEE Symposium on Wireless Technology & Applications, pp. 107–112 (2021). https://doi.org/10.1109/ISWTA52208.2021.9587444.

  7. Sathyaseelan, M.P., Chakravarthi, M.K., Sathyaseelan, A.P., Sudipta, S.: IoT based COVID de-escalation system using Bluetooth low level energy. In: Proceedings of the Sixth International Conference on Inventive Computation Technologies, pp. 174 - 177 (2021). https://doi.org/10.1109/ICICT50816.2021.9358718.

  8. Bhowmik, T., Mojumder, R., Banerjee, I., Bhattacharya, A., Das, G.: IoT based non-contact portable thermal scanner for COVID patient screening. In: IEEE 17th India Council International Conference (2020). https://doi.org/10.1109/INDICON49873.2020.9342203

  9. Vedaei, S.S., et al.: COVID-SAFE: an IoT-based system for automated health monitoring and surveillance. IEEE Access 8, 188538–188551 (2020). https://doi.org/10.1109/ACCESS.2020.3030194

    Article  Google Scholar 

  10. Sami, R., et al.: A one-year hospital-based prospective Covid-19 open-cohort in the eastern Mediterranean Region: the Khorshid Covid Cohort (KCC) study (2020). https://www.medrxiv.org/content/10.1101/2020.05.11.20096727v2

  11. Mamdani, E.H., Assilian, S.: An experiment in linguistic synthesis with a fuzzy logic controller. Int. J. Hum.-Comput. Stud. 51(2), 135–147 (1999). https://doi.org/10.1006/ijhc.1973.0303

    Article  MATH  Google Scholar 

  12. Karaboga, D., Kaya, E.: Adaptive network based fuzzy inference system (ANFIS) training approaches: a comprehensive survey. Artif. Intell. Rev. 52(4), 2263–2293 (2019). https://doi.org/10.1007/s10462-017-9610-2

    Article  Google Scholar 

  13. Burges, C.J.C.: A tutorial on support vector machines for pattern recognition. Data Min. Knowl. Discov. 2(2), 121–167 (1998). https://doi.org/10.1023/A:1009715923555

    Article  Google Scholar 

  14. Farid, D.M., Zhang, L., Rahman, C.M., Hossain, M.A., Strachan, R.: Hybrid decision tree and naïve bayes classifiers for multi-class classification tasks. Expert Syst. Appl. 41(4), 1937–1946 (2014). https://doi.org/10.1016/j.eswa.2013.08.089

    Article  Google Scholar 

  15. Barroca Filho, I.M., de Aquino Junior, G.S.: Proposing an IoT-based healthcare platform to integrate patients, physicians and ambulance services. In: Gervasi, O., et al. (eds.) ICCSA 2017. LNCS, vol. 10409, pp. 188–202. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62407-5_13

    Chapter  Google Scholar 

  16. De Morais Barroca Filho, I., Aquino, G., Malaquias, R., Girão, G., Melo, S.R.M.: IoT-based healthcare platform for patients in ICU beds during the COVID-19 outbreak. IEEE Access 9, 27262–27277 (2021). https://doi.org/10.1109/ACCESS.2021.3058448

    Article  Google Scholar 

  17. de Morais Barroca Filho, I., Aquino Junior, G.S., Vasconcelos, T.B.: Extending and instantiating a software reference architecture for IoT-based healthcare applications. In: Misra, S., et al. (eds.) ICCSA 2019. LNCS, vol. 11623, pp. 203–218. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-24308-1_17

    Chapter  Google Scholar 

  18. de Morais Barroca Filho, I.: Architectural design of IoT-based healthcare applications. Ph.D. dissertation, Department of Applied Mathematics, Federal University of Rio Grande do Norte, Natal, Brazil (2005). https://repositorio.ufrn.br/jspui/handle/123456789/26767

  19. Rehman, M., et al.: Contactless small-scale movement monitoring system using software defined radio for early diagnosis of COVID-19. IEEE Sens. J. 21(15), 17180–17188 (2021). https://doi.org/10.1109/JSEN.2021.3077530

    Article  Google Scholar 

  20. Schrumpf, F., Sturm, M., Bausch, G., Fuchs, M.: Derivation of the respiratory rate from directly and indirectly measured respiratory signals using autocorrelation. Curr. Direct. Biomed. Eng. 2(1), 241–245 (2016). https://doi.org/10.1515/cdbme-2016-0054

    Article  Google Scholar 

  21. Raspberry Pi: Raspberry Pi 3 Model B (2015). https://www.raspberrypi.org. Accessed 12 Jan 2022

Download references

Author information

Authors and Affiliations

  1. Department of IT, IIEST Shibpur, Shibpur, Howrah, 711103, India

    Tanima Bhowmik & Indrajit Banerjee

  2. Department of ECE, C.I.E.M Kolkata, Kolkata, 700040, India

    Rohan Mojumder & Dibyendu Ghosh

Authors
  1. Tanima Bhowmik
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rohan Mojumder
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dibyendu Ghosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Indrajit Banerjee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tanima Bhowmik .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, West Bengal, India

    Asit Kumar Das

  2. P. G. Department of Computer Science, Maharaja Sriram Chandra Bhanja Deo (MSCB) University, Baripada, Mayurbhanj, Odisha, India

    Janmenjoy Nayak

  3. Department of Computer Application, Veer Surendra Sai University of Technology, Sambalpur, Odisha, India

    Bighnaraj Naik

  4. Department of Artificial Intelligence and Data Science, Ramco Institute of Technology, Rajapalayam, Tamil Nadu, India

    S. Vimal

  5. Communication Sciences, University of Teramo, Teramo, Italy

    Danilo Pelusi

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Bhowmik, T., Mojumder, R., Ghosh, D., Banerjee, I. (2022). An Evaluative Review on Various Tele-Health Systems Proposed in COVID Phase. In: Das, A.K., Nayak, J., Naik, B., Vimal, S., Pelusi, D. (eds) Computational Intelligence in Pattern Recognition. CIPR 2022. Lecture Notes in Networks and Systems, vol 480. Springer, Singapore. https://doi.org/10.1007/978-981-19-3089-8_20

Download citation

Publish with us

Policies and ethics

Search

Navigation