Skip to main content
Log in

Cardiac Care Assistance using Self Configured Sensor Network—a Remote Patient Monitoring System

  • Original Contribution
  • Published:
Journal of The Institution of Engineers (India): Series B Aims and scope Submit manuscript

Abstract

Pervasive health care systems are used to monitor patients remotely without disturbing the normal day-to-day activities in real-time. Wearable physiological sensors required to monitor various significant ecological parameters of the patients are connected to Body Central Unit (BCU). Body Sensor Network (BSN) updates data in real-time and are designed to transmit alerts against abnormalities which enables quick response by medical units in case of an emergency. BSN helps monitoring patient without any need for attention to the subject. BSN helps in reducing the stress and strain caused by hospital environment. In this paper, mathematical models for heartbeat signal, electro cardio graph (ECG) signal and pulse rate are introduced. These signals are compared and their RMS difference-fast Fourier transforms (PRD-FFT) are processed. In the context of cardiac arrest, alert messages of these parameters and first aid for post-surgical operations has been suggested.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. C.C. Chiang, W.C. Tzeng, H.C. Cheng, C.T. Lin, Y.C. Yang, S.F. Liang, S.B. Lim, Construction and application of an electronic ECG management system. J. Inf. Technol. Appl. 2(3), 135–140 (2007)

    Google Scholar 

  2. M.F.A. Rasid, B. Woodward, Bluetooth telemedicine processor for multi-channel biomedical signal transmission via mobile cellular networks. IEEE Trans. Inf. Technol. Biomed. 9(1), 35–43 (2005)

    Article  Google Scholar 

  3. V.Shnayder, B.Chen, K.Lorincz, T.R.F.Fulford-Jones, M.Welsh, Sensor networks for medicalcare, Div. Eng. Appl. Sci. Harvard Univ., Cambridge, MA, Tech. Rep., TR-08-05, 2005

  4. D. Blasi, V. Cacace, L. Casone, M. Rizzello, S. Rotolo, L. Bononi, Ad hoc wireless sensor networking: Challenges and issues. ST J. Res. 4(1), 19–32 (2006)

    Google Scholar 

  5. Y.Guang-Zhong, Body sensor network, ISBN-978-1-84628-272-0, Springer Verlag, 2006

  6. J.P.Carmo, P.M.Mendes, C.Couto, J.H. Correia, 2.4 GHz wireless sensor network for smart electronic shirts, Smart Sens Actuators MEMS Proc SPIE, 5836, 579-86, 2005

  7. R.S.H. Istepanian, L.J. Hadjileontiadis, S.M. Panas, ECG data compression using wavelets and higher order statistics methods. IEEETrans. Inf. Technol. Biomed. 5(2), 108–115 (2001)

    Article  Google Scholar 

  8. R.S.H. Istepanian, A.A. Petrosian, Optimal zonal wavelet-based ECG data compression for a mobile telecardiology system. IEEE Trans. Inf. Technol. Biomed. 4(3), 200–211 (2000)

    Article  Google Scholar 

  9. S. Zhou, G. Guillemette, R. Antinoro, F. Fulton, New approaches in philips ECG database management system design. Comput. Cardiol. 30, 267–270 (2003)

    Google Scholar 

  10. H. Jumaa, J. Fayn, P. Rubel, XML based mediation for automating the storage of SCP-ECG data into relational databases. Comput. Cardiol. 35, 445–448 (2008)

    Google Scholar 

  11. J.J.Segura-Ju´arez, D.Cuesta-Frau, L.Samblas-Pena, M.Aboy, A microcontroller-based portable electrocardiograph recorder’, IEEE Trans.Biomed. Eng., 51(9), 1686-1690, 2004

  12. H.S. Liu, T. Zhang, F.S. Yang, A multistage, multi-method approach for automatic detection and classification of epileptiform EEG. IEEE Trans. Biomed. Eng. 49(12), 1557–1566 (2002)

    Article  Google Scholar 

  13. N. Acir, A modified hybrid neural network for pattern recognition and its application to SSW complex in EEG’. Neural Comput. Appl. 15(1), 49–54 (2005)

    Article  Google Scholar 

  14. P. Bonato, P.J. Mork, D.M. Sherrill, R.H. Westgaard, Data mining of motor patterns recorded with wearable technology’. IEEE Eng. Med. Biol. Mag. 22(3), 110–119 (2003)

    Article  Google Scholar 

  15. D. Ganesan, A. Cerpa, W. Yu, Y. Ye, J. Zhao, D. Estrin, Networking issues in wireless sensor networks. J. Parallel Distrib. Comput. 64(7), 799–814 (2004)

    Article  Google Scholar 

  16. E. Spinelli, R. Pallas-Areny, M. Mayosky, AC-coupled front-end for bio-potential measurements. IEEE Trans. Biomed. Eng. 50(3), 391–395 (2003)

    Article  Google Scholar 

  17. D.Malan, T.Fulford-Jones, M.Welsh, S.Moulton, CodeBlue: An ad hoc sensor network infrastructure for emergency medical care, presented at the MobiSys 2004 Workshop Appl. Mobile Embedded Syst. (WAMES 2004), Boston, MA, 2004

  18. C.Park, P.H.Chou, Y.Bai, R.Matthews, A.Hibbs, An ultrawearable, wireless, low power ECG monitoring system, Proceedings of IEEE Biomed. Circuits Syst. Conf. (BioCAS 2006), Dec., 241-244

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to V. R. Sarma Dhulipala.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sarma Dhulipala, V.R., Kanagachidambaresan, G.R. Cardiac Care Assistance using Self Configured Sensor Network—a Remote Patient Monitoring System. J. Inst. Eng. India Ser. B 95, 101–106 (2014). https://doi.org/10.1007/s40031-014-0084-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40031-014-0084-1

Keywords

Navigation