skip to main content
10.1145/3290420.3290445acmotherconferencesArticle/Chapter ViewAbstractPublication PagesiccipConference Proceedingsconference-collections
research-article

Hardware implementation of real-time ECG R-wave detection with wavelet transform algorithm

Published: 02 November 2018 Publication History

Abstract

This paper introduces the hardware implementation architecture of real-time ECG R-wave detection with wavelet transform algorithm. According to the principle of mutation point detection based on wavelet transform, we determine the position of R-wave by the modulus maximum of the wavelet coefficients. Moreover, the proposed hardware implementation architecture is optimized based on the characteristics of the wavelet transform algorithm. The clinical data of MIT-BIH arrhythmia database is used to verify the proposed algorithm and hardware implementation architecture.

References

[1]
D. Pandit, L. Zhang, C. Liu, S. Chattopadhyay, N. Aslam, and C. P. Lim. 2017. A lightweight QRS detector for single lead ECG signals using a max-min difference algorithm. Computer methods and programs in biomedicine. 144 (Jun.2017), 61--75.
[2]
M. Rakshit, D. Panigrahy and P. K. Sahu. 2016. An improved method for R-peak detection by using Shannon energy envelope. Sādhanā. 41.5 (May. 2016), 469--477.
[3]
M. Rakshit and S. Das. 2017. An efficient wavelet-based automated R-peaks detection method using Hilbert transform. Biocybernetics and Biomedical Engineering. 37.3(2017), 566--577.
[4]
B. Purahong, S. Thongkrairat, T. Anuwongpinit, V. Chutchavong and H. Aoyama. 2017. Implementation of ECG portable device for real-time signal monitoring. In Proceedings of the 3rd International Conference on Communication and Information Processing (ICCIP). ACM. (Nov.2017), 257--260.
[5]
T. Yamakawa, R. Kinoshita, K. Fujiwara, M. Kano, M. Miyajima, T. Sakata and Y. Ueda. 2015. Accuracy comparison between two microcontroller-embedded R-wave detection methods for heart-rate variability analysis. In Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2015 Asia-Pacific. IEEE. (Dec.2015), 1010--1013.
[6]
K. Meddah, H. Zairi and M. K. Talha. 2015. New system cardiac arrhythmia detection on FPGA. In Modelling, Identification and Control (ICMIC), 2015 7th International Conference on IEEE. 7(Dec. 2015), 1--5.
[7]
B. Zhang, L. Sieler, Y. Morère, B. Bolmont and G. Bourhis. 2017. Dedicated wavelet QRS complex detection for FPGA implementation. In Advanced Technologies for Signal and Image Processing (ATSIP). 2017 International Conference on. IEEE, (May.2017), 1--6.
[8]
Y. Ma, T. Li, Y. Ma and K. Zhan. 2016. Novel real-time FPGA-based R-wave detection using lifting wavelet. Circuits, Systems, and Signal Processing. 35.1(Jan. 2016), 281--299.
[9]
C. I. Ieong, P. I. Mak, C. P. Lam, C. Dong, M. I. Vai, P. U. Mak and R. P. Martins. 2012. A 0.83-QRS detection processor using quadratic spline wavelet transform for wireless ECG acquisition in 0.35-CMOS. IEEE Trans. Biomed. Circuits Syst. 6.6(Apr. 2012), 586--595.
[10]
H. Chereda, S. Nikolaiev and Y. Tymoshenko. 2016. Sampling Rate Independent Filtration Approach for Automatic ECG Delineation. arXiv preprint arXiv. 1611.08537(Nov. 2016).

Cited By

View all
  • (2023)Research and Design of Human Motion MonitoringProceedings of the 6th International Conference on Information Technologies and Electrical Engineering10.1145/3640115.3640163(298-304)Online publication date: 3-Nov-2023
  • (2022)Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia ClassificationIEEE Access10.1109/ACCESS.2022.316989310(44046-44061)Online publication date: 2022

Index Terms

  1. Hardware implementation of real-time ECG R-wave detection with wavelet transform algorithm

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Other conferences
    ICCIP '18: Proceedings of the 4th International Conference on Communication and Information Processing
    November 2018
    326 pages
    ISBN:9781450365345
    DOI:10.1145/3290420
    • Conference Chairs:
    • Jalel Ben-Othman,
    • Hui Yu,
    • Program Chairs:
    • Herwig Unger,
    • Masayuki Arai
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 02 November 2018

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. ECG
    2. R-wave detection
    3. hardware implementation
    4. mutation detection
    5. wavelet transform

    Qualifiers

    • Research-article

    Conference

    ICCIP 2018

    Acceptance Rates

    Overall Acceptance Rate 61 of 301 submissions, 20%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)1
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 19 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2023)Research and Design of Human Motion MonitoringProceedings of the 6th International Conference on Information Technologies and Electrical Engineering10.1145/3640115.3640163(298-304)Online publication date: 3-Nov-2023
    • (2022)Three-Heartbeat Multilead ECG Recognition Method for Arrhythmia ClassificationIEEE Access10.1109/ACCESS.2022.316989310(44046-44061)Online publication date: 2022

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media