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Labview based Electrocardiograph (ECG) Patient Monitoring System for Cardiovascular Patient using WSNs

Vijay Srivastava, Krati Varshney, Vibhav Kumar Sachan. Published in Wireless.

Communications on Applied Electronics
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Vijay Srivastava, Krati Varshney, Vibhav Kumar Sachan
10.5120/cae2017652541

Vijay Srivastava, Krati Varshney and Vibhav Kumar Sachan. Labview based Electrocardiograph (ECG) Patient Monitoring System for Cardiovascular Patient using WSNs. Communications on Applied Electronics 6(8):28-34, March 2017. BibTeX

@article{10.5120/cae2017652541,
	author = {Vijay Srivastava and Krati Varshney and Vibhav Kumar Sachan},
	title = {Labview based Electrocardiograph (ECG) Patient Monitoring System for Cardiovascular Patient using WSNs},
	journal = {Communications on Applied Electronics},
	issue_date = {March 2017},
	volume = {6},
	number = {8},
	month = {Mar},
	year = {2017},
	issn = {2394-4714},
	pages = {28-34},
	numpages = {7},
	url = {http://www.caeaccess.org/archives/volume6/number8/714-2017652541},
	doi = {10.5120/cae2017652541},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Lab VIEW and the signal processing-related toolkits can offer a tough and efficient environment and tools for resolving ECG signal processing problem. This paper prove how to use these advance powerful tools in de noising, analyzing, and extracting ECG signals easily and usefully not only in heart illness diagnosis but also in ECG signal processing research. Data is introduced from online data bank files, as Physic bank MIT-BIH data to the applications in this equipment for analysis. The proposed method arrangements with the study and analysis of ECG signal using biomedical toolkit effectively. In the first phase, ECG signal is acquired which is then monitored by filtering the raw ECG signal to remove undesirable noises. The next phase focuses on extracting the features from the acquired signal and at last picturing and analyzing the extraction of the signal results.

This paper helps to developing a Lab view based ECG patient monitoring system for cardiovascular patient using wireless sensor networks. The designed device has been divided into three parts. First part is ECG amplifier circuit, built using instrumentation amplifier followed by signal conditioning circuit with the operation amplifier Secondly, the ELVIS card is used to convert the analog signal into digital form for the further process. Furthermore, the data has been processed in Lab view where the digital filter systems have been applied to remove the noise from the developed signal. After processing, the algorithm was developed to calculate the heart rate and to study the arrhythmia condition. Finally, WSN technology has been added in our work to make device more communicative and much more cost-effective solution in telemedicine technology which has been key-problem to realize the tale diagnosis and monitoring of ECG signals. The technology also can be easily applied over already existing Internet.

References

  1. [zone.ni.com › ... › Manuals › LabVIEW 2013 Biomedical Toolkit Help]
  2. Ali Reza Vakilian1, Farhad Iranmanesh1, Ali EsmaeiliNadimi, and Jafar Ahmadi Kahnali, “Heart RateVariability and QT Dispersion Study in Brain DeathPatients and Comatose Patients with Normal BrainstemFunction”, Journal of the College of Physicians and Surgeons Pakistan., Vol.21,no.3,pp.130-133,2011.
  3. Biomedical User Group Forum; http://decible.ni.com/content/groups/biomedical-usergroup.
  4. D.C.Reddy, “Biomedical Signal Processing: Priniciples and Techniques”, 2nd edition Tata McGraw-Hill, New Delhi, 2005.
  5. Diptyajit Das, Arnab Pal, Souvik Tewary, Shreyosi Chakraborty, Sauvik Das Gupta “A Smart and Wearable Cardiac Healthcare System with Monitoring of Sudden Fall for Elderly and Post-Operative Patients”, IOSR Journal of Computer Engineering (IOSR-JCE) Volume 16, Issue 2, Ver. VIII (Mar-Apr. 2014), PP 126-133
  6. Jigar D. Shah, M. S. Panse, “EEG purging using LABVIEW based wavelet analysis”, National Conference on Computational Instrumentation CSIO Chandigarh, INDIA, pp.19-20, March ,2010
  7. Joseph..D.Bronzino, “Biomedical Engineering Handbook”, 3rd edition CRC Press, 2005
  8. LabVIEW 2013 Biomedical Toolkit Help Edition Date: June 2013 Part Number: 373696B-01 »View Product Info June 2013, 373696B-01
  9. labView for ECG Signal Processsing: http://zone ni.com/devzone/cda/plid/5832
  10. Mihaela ascu, Dan Lascu Proceeding SSIP'07 Proceedings of the 7th WSEAS International Conference on Signal, Speech and Image Processing Pages 38-43
  11. Rajendra Acharya U, Paul Joseph K, Kannathal N, Lim Choo Min and Jasjit Suri S, Heart Rate Variability, Advances in Cardiac Signal Processing, Springer-Verlag Berlin Heidelberg 2007,pp.121-165.
  12. Using Lab VIEW for Heart Rate Variability Analysis http://www. ni.com/white-paper/6349/en
  13. P. Khanja, S. Wattanasirichaigoon, J. Natwichai, L. Ramingwong, and S. Noimanee, “A WEB base system for ECG data transferred using ZIGBEE/IEEE technology,” in Proceedings of the 3rd International Symposium on Biomedical Engineering (ISBME ’08), Bangkok,Thailand, 2008.
  14. A. A. M. Adam and M. B. M. Amin, “Design and implementation of portable PC-based ECG machine,” International Journal of Sciences: Basic and Applied Research, vol. 15, no. 2, 2014.
  15. Rappaport, T. S. ,“Wireless communications: principles and practice,”New York: Prentice Hall, 1996.
  16. Anna, H.: Wireless sensor network design (Wiley), 2003
  17. Sharma and Banerjee, “Performance Analysis of Energy-Efficient Modulation Techniques for Wireless Sensor Networks “, 978-1-4244-2746-8/08c 2008 IEEE
  18. www.ni.com/example/3083/en/

Keywords

Wireless sensor network (WSN), Lab VIEW Biomedical Toolkit, Biomedical workbench, ECG, ECG Feature Extraction