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A Study of Telecardiology-Based Methods for Detection of Cardiovascular Diseases

  • Nisha Raheja
  • Amit Kumar ManoachaEmail author
Chapter
  • 21 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1124)

Abstract

In India, Cardiovascular diseases (CVDs) have now become the main reason for death, due to poor lifestyle management. Population living in rural and distant places is devoid of access to medical experts, especially in the field of cardiology, which leads to worst healthcare services. For this purpose, the proposed technology has an advantage for development of a novel diagnostic system for real-time predictive analysis based on ECG data and related health parameters/symptoms to get instant opinion from cardiologists across the globe. On the other side, India is facing a big challenge of shortfall in highly skilled specialists, particularly in remote areas. So there is a need to save the lives of patients living in remote areas of the country by giving proper diagnosis and timely treatment. Telecardiology may provide a better possible solution by providing timely diagnosis and medication to rural populations and hence can save human lives.

Keywords

ECG Telecardiology Internet of things (IOT) Cloud computing 

References

  1. 1.
    India State-Level Disease Burden Initiative CVD Collaborators, The Changing patterns of cardiovascular diseases and their risk factors in the states of India: the Global Burden of Disease Study, 1990–2016, vol. 6, pp. 1339–1351, December (2018)Google Scholar
  2. 2.
    News on Healthcare crisis: Short of 5 lakh doctors, India has just 1 for 1,674 people. Sep 01, 11:20 IST (2016). Available at http://www.hindustantimes.com/india-news/healthcare-crisisshort-of-5-lakh-doctors-india-has-just-1-for-1-674-people/story-SZepTyjJ78WgOVIo93tBVK.html
  3. 3.
    S. Maheshwari et al., Tele-cardiology: a solution whose time has come. Cardiol. Today 18(2), 50–52 (2014)Google Scholar
  4. 4.
    G. Molinari, M. Molinari, Telecardiology and its settings of application: an update. J. Telemed. Telecare 24(5), 373–381 (2017)CrossRefGoogle Scholar
  5. 5.
    M. D’Aloia, A. Longo et al., Noisy ECG signal analysis for automatic peak detection. Information (2019)Google Scholar
  6. 6.
    G. Kada, P.C. Bhaska, Reduction of power line interference in ECG signal using FIR filter. Int. J. Comput. Eng. Res. (2012)Google Scholar
  7. 7.
    A. Kumar, M. Singh, Optimal selection of wavelet function and decomposition level for removal of ECG signal artifacts. J. Med. Imaging Health Inf. 5, 138–146 (2015)CrossRefGoogle Scholar
  8. 8.
    J.-C. Hsieh, A.-H. Li et al., Mobile, cloud, and big data computing: contributions, challenges, and new directions in telecardiology. Int. J. Environ. Res. Public Health (2013)Google Scholar
  9. 9.
    C.-K. Chen, C.-L. Lin, Data encryption and transmission based on personal ECG signals. Int. J. Sens. Netw. Data Commun. (2015)Google Scholar
  10. 10.
    O. El B’charri, R. Latif, The ECG signal compression using an efficient algorithm based on the DWT. Int. J. Adv. Comput. Sci. Appl. 7(3), (2016)Google Scholar
  11. 11.
    A. Nemcova, R. Smísek, A comparative analysis of methods for evaluation of ECG signal quality after compression. Hindawi BioMed Res. Int. (2018)Google Scholar
  12. 12.
    S.Y. Mumtaj, A. Umamakeswari, Neuro fuzzy based healthcare system using IoT, in International Conference on Energy, Communication, Data Analytics and Soft Computing (2017)Google Scholar
  13. 13.
    M.R.F. Nurdin, S. Hadiyoso et al., A low-cost Internet of Things (IoT) system for multi-patient ECG’s monitoring, in International Conference on Control, Electronics, Renewable Energy and Communications (2016)Google Scholar
  14. 14.
    J.M. Belmont, L.F. Mattioli et al., Evaluation of stethoscopy remote for Pédiatrie telecardiology. Telemed. J. 1(2), (1995)Google Scholar
  15. 15.
    J.M. Belmont, L.F. Mattioli et al., Accuracy of analog telephonic stethoscopy for pediatric telecardiology. Pediatrics 112(4), (2003)CrossRefGoogle Scholar
  16. 16.
    F. Hu, D.-C. Dong, Privacy-preserving telecardiology sensor networks: toward a low-cost portable wireless hardware/software codesign. IEEE Trans. Inf. Technol. Biomed. 11(6), (2007)CrossRefGoogle Scholar
  17. 17.
    C.-T. Lin, K.-C. Chang, An intelligent telecardiology system using a wearable and wireless ECG to detect atrial fibrillation. IEEE Trans. Inf. Technol. Biomed. 14(3), (2010)Google Scholar
  18. 18.
    A. Alesanco, J. Garcıa, Clinical assessment of wireless ECG transmission in real-time cardiac tele-monitoring. IEEE Trans. Inf. Technol. Biomed. 14(5), 1144–1152 (2010)CrossRefGoogle Scholar
  19. 19.
    A.K. Manocha, M. Singh, An overview of ischemia detection techniques. Int. J. Sci. Eng. Res. 2(11), (2011)Google Scholar
  20. 20.
    S.G. Al-Kindi, R. Tafreshi, Real-time detection of myocardial infarction by evaluation of ST-segment in digital ECG. J. Med. Imaging Health Inf. 1, 1–6 (2011)CrossRefGoogle Scholar
  21. 21.
    H. Xia, I. Asif et al., Cloud-ECG for real time ECG monitoring and analysis. Comput. Method Program Biomed. 1(10), 253–259 (2013)CrossRefGoogle Scholar
  22. 22.
    A. Huang, C. Chen et al, WE-CARE: an intelligent mobile telecardiology system to enable mHealth applications. IEEE J. Biomed. Health Inf. 18(2), (2014)CrossRefGoogle Scholar
  23. 23.
    X. Wang et al., Enabling smart personalized healthcare: a hybrid mobile-cloud approach for ECG tele monitoring. IEEE J. Biomed. Health Inf. 18(3), 739–745 (2014)CrossRefGoogle Scholar
  24. 24.
    D. Sadhukhan, S. Pal et al., Electrocardiogram data compression using Adaptive bit encoding of the discrete Fourier transforms coefficients. IET Sci. Meas. Technol. 9(7), 866–874 (2015)CrossRefGoogle Scholar
  25. 25.
    N.V. Panicker, A. S. Kumar, Tablet PC enabled body sensor system for rural telehealth applications. Int. J. Telemed. Appl. (2016)Google Scholar
  26. 26.
    R. Huang, Y. Zhou, Disease classification and biomarker discovery using ECG data. Int. J. Biomed. Res. (2015)Google Scholar
  27. 27.
    K. Sailunaz, M. Alhussein et al., Cloud based medical system framework for rural health monitoring in developing countries. Comput. Elect. Eng. 1–13, (2016)Google Scholar
  28. 28.
    A. Kumar, M. Singh, Statistical analysis of ST segments in ECG signal for detection of ischaemic episodes. Trans. Inst. Meas. Control 1–12 (2016)Google Scholar
  29. 29.
    E. Spanò et al., Low-power wearable ECG monitoring system for multiple-patient remote monitoring. IEEE Sens. J. 16(13), 5452–5462 (2016)CrossRefGoogle Scholar
  30. 30.
    L. Marsanoval, M. Ronzhina et al., ECG features and methods for automatic classification of ventricular premature and ischemic heartbeats: a comprehensive experimental study. Scientific Report (2017)Google Scholar
  31. 31.
    G. Molinari, M. Molinari et al., Telecardiology and its settings of application: an update. J. Telemed. Telecare 24(5), 373–381 (2017)CrossRefGoogle Scholar
  32. 32.
    I. de la Torre Díez, B. Garcia-Zapirain et al., Proposing telecardiology services on cloud for different medical institutions. Telemed. e-Health 23(8), (2017)Google Scholar
  33. 33.
    B.S. Chandraa, C.S. Sastry et al., Dictionary-based monitoring of premature ventricular contractions: an ultra-low-cost point-of-care service. Artif. Intell. Med. (2017)Google Scholar
  34. 34.
    M. Kumar, R.B. Pachori et al., Automated diagnosis of myocardial infarction ECG signals using sample entropy in flexible analytic wavelet transform framework. Entropy (2017)Google Scholar
  35. 35.
    C.K. Roopa, B.S. Harish, A survey on various machine learning approaches for ECG analysis. Int. J. Comput. Appl. (2017)Google Scholar
  36. 36.
    F. Gaol, S. Thiebes et al., Rethinking the meaning of cloud computing for health care: a taxonomic perspective and future research directions. J. Med. Internet Res. (2018)Google Scholar
  37. 37.
    E. Andrès, S. Talha et al., Current research and new perspectives of telemedicine in chronic heart failure: narrative review and points of interest for the clinician. J. Clin. Med. (2018)Google Scholar
  38. 38.
    A. Sultan, Z. Ur Rahman et al., An efficient Kalman noise canceller for cardiac signal analysis in modern telecardiology systems. IEEE 6 (2018)Google Scholar
  39. 39.
    T. Tariq, A. Abbas et al., A smart heart beat analytics system using wearable device, in International Conference on Communication, Computing and Digital Systems (2019)Google Scholar
  40. 40.
    M.A.G. Santos, R. Munoz et al., Online heart monitoring systems on the internet of health things environments: a survey, a reference model and an outlook. Science Direct (2019)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Department of Electronics & Communication EngineeringMRSPTUBathindaIndia
  2. 2.Department of Electrical EngineeringPIT, GTB GarhMogaIndia

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