Early Warning System for Possible Heart Attacks Using IOT

Authors

  • Tushar A Shah  Assistant Professor, Computer Engineering Department, Madhuben and Bhanubhai Patel Institute of Technology, V.V.Nagar, Anand, Gujarat, India

DOI:

https://doi.org//10.32628/IJSRSET229655

Keywords:

Raspberry Pi, IoT, GSM, Heartbeat sensor, SpO2 sensor, Blood pressure sensor, Body Temperature sensor, ECG sensor.

Abstract

Now-a-days, diseases related to heart are mounting at a very great speed. Due to these problems, timely health check up has become vital. A modern concept of health monitoring a patient includes wirelessly monitoring. It is a major development in medical arena. This system depends on doctor examining patient continuously without patient being physically present for check up. In medical science, excellent and cost effective gadgets related to monitoring health utilizing popular technologies such as wireless communications and portable remote health monitoring device are developed. This development provides ease to the patients having various diseases. As a result, visit of patients to the doctors constantly has lowered because various types of reports can be generated remotely and wirelessly at doctor’s end at regular interval of time. Because of this recent development in scientific technology, doctors are saving several lives. Internet of Things provides platform for development of many intelligent gadgets & applications. IoT infrastructure provides base of connectivity and technology. IoT intelligent devices can implement the facilities of monitoring health remotely and notifying any health issues in emergency. In this paper, we propose a design for transfer of personal medical information and facility for storing the same over cloud infrastructure. The hardware devices like Raspberry Pi, Heartbeat sensor, Blood Pressure sensor, SpO2 sensor, Body Temperature sensor will be used in this system. Raspberry Pi will perform dual role of being a sensor node as well as system controller.

References

  1. K. Navya, Dr. M. B. R. Murthy, “A Zigbee Based Patient Health Monitoring System”, Int. Journal of Engineering Research and Applications Vol. 3, Issue 5, Sep-Oct 2013, pp.483-486
  2. Matthew D'Souza, Montserrat Ros, Adam Postula, “Wireless Medical Information System Network for Patient ECG Monitoring” Digital System Design:Architectures, Methods and Tools, 2006, DSD 2006, 9th EUROMICRO Conference, 2006, pp.617-624.
  3. C.C.Gavimath, Krishnamurthy Bhat, C.L. Chayalakshmi , R. S. Hooli and B.E.Ravishankera, “Design and Development of versatile saline flow rate measuring system and GSM based remote monitoring device”, International Journal of Pharmaceutical Applications ISSN 0976-2639. Vol 3, Issue 1,2012, pp 277-281.
  4. NakulPadhye and Preet Jain, “Implementation of ARM Embedded Web Server for DAS using Raspberry pi”, VSRD IJEECE April 2013.
  5. Ch. Sandeep Kumar Subudhi and S. Sivanandam, “Intelligent Wireless Patient Monitoring and Tracking System (Using Sensor Network and Wireless Communication)”, International Journal of Interdisciplinary and Multidisciplinary Studies,2014,Vol 1,No.3,97-104.
  6. Hossein Fotouhi, Aida Causevic, Kristina lundqvist, Mats bjorkman, “Communication and Security in Health monitoring System – A Review”, 2016 IEEE 40th Annual computer software and application conference, DOI 10.1109/ COMPSAC.2016.8.
  7. M. U. Ahmed, M. Bj¨orkman, and A. Cau?sevic, et al. “An overview on the internet of things for health monitoring systems in IoT Technologies for HealthCare”, 2015.
  8. F. Samie and L. Bauer and C.-M. Hsieh et al. Online binding of applications to multiple clock domains in shared fpga based systems., pp. 25–30, 2015.
  9. C. Perera and A. Zaslavsky and P. Christen et al. Context aware computing for the Internet of Things: A survey. IEEE Communications Surveys & Tutorials, 16(1):414–454, 2014.
  10. FarzadSamie, Lars Bauer, Jörg Henkel, “IoT T echnologies for Embedded Computing: A Survey”, ESWEEK’16, October 2-7 2016, Pittsburgh, PA, USA.
  11. V. K. Chippaand S. T .Chakradhar and K. Roy, “Analysis and characterization of inherent application resilience for approximate computing”, in DAC, 2013.
  12. S. Qaisar, R. M. Bilal, and W. Iqbal, “Compressive sensing: From theory to applications, a survey”, Journal of Communications and Networks, pp. 443–456, 2013.
  13. K. Ma, Y. Zheng, S. Li, “Architecture exploration for ambient energy harvesting nonvolatile processors”, in HPCA, pp. 526–537, 2015.
  14. https://www.raspberrypi.org/blog/libraries-codecs-oss/
  15. D. Kelf. IoT: A Return to Our Favorite EDA Requirements. Online: www.eetimes.com/author.asp?doc id=1322009, 2014.
  16. J. Kwong and A. P. Chandrakasan, “An energy-efficient biomedical signal processing platform”, IEEE Journal of SolidState Circuits, 46(7):1742–1753, 2011.
  17. V. Shnayder, B.-r. Chen, and K. Lorincz, “Sensor networks for medical care”, in SenSys, pp. 314–314, 2005.
  18. Pankaj S. Hage, Sanjay B. Pokle, VenkateshwarluGudur, “Discrete Wavelet Transform Based Video Signal Processing”, IEEE ICACACT, 2014
  19. Vivek Pardeshi, Saurabh Sagar, Swapnil Murmurwar, Pankaj Hage, “Health Monitoring Systems using IoT and Raspberry Pi”, IEEE ICIMIA, 2017
  20. Sunehra, Pini Ramakrishna, “Web Based Patient Health Monitoring System using Raspberry Pi, pp. 568-574, “IEEE ICCCI, 2016
  21. https://www.elprocus.com/microcontroller-based-project-on-patient- monitoring-system/
  22. https://www.researchgate.net/ figure/305335459_fig2_Figure-3-General-architecture-of-an-IoT-embedded-device
  23. https://www.researchgate.net/publication/305335459_IoT_Technologies_for_Embedded_Computing_A_Survey
  24. www.maximintegrated.com
  25. https://hacktronics.co.in/ sensors/light-ir-related-sensors/pulseheart-beat-sensor
  26. https://www.tweaking4all.com/hardware/arduino/arduino-ds18b20-temperature-sensor/
  27. https://www.cooking-hacks.com/documentation/tutorials/ehealth-biometric-sensor-platform-arduino-raspberry-pi-medical

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2021-06-30

Issue

Volume 8, Issue 3, May-June-2021

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Tushar A Shah, " Early Warning System for Possible Heart Attacks Using IOT, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 8, Issue 3, pp.572-580, May-June-2021. Available at doi : https://doi.org/10.32628/IJSRSET229655