access icon openaccess Motion artefact removals for wearable ECG using stationary wavelet transform

Wearable Electrocardiogram (ECG) is attracting much attention in daily healthcare applications. From the viewpoint of long-term use, it is desired that the electrodes are non-contact with the human body. In this study, the authors propose an algorithm using the stationary wavelet transform (SWT) to remove motion artefact superimposed on ECG signal when using non-contact capacitively coupling electrodes. The authors evaluate the effect on motion artefact removal of this algorithm by applying it to various ECG signals with motion artefacts superimposed. As a result, the correlation coefficients of ECG signals with respect to the clean ones have been improved from 0.71 to 0.88 on median before and after motion artefact removal, which demonstrates the validity of the proposed SWT-based algorithm.

Inspec keywords: wavelet transforms; medical signal processing; health care; electrocardiography

Other keywords: stationary wavelet transform; motion artefact removals; wearable electrocardiogram; wearable ECG; SWT

Subjects: Electrical activity in neurophysiological processes; Bioelectric signals; Function theory, analysis; Biomedical engineering; Integral transforms; Biology and medical computing; Digital signal processing; Integral transforms

References

    1. 1)
      • 2. Wang, J., Wang, Q.: ‘Body area communications’ (Wiley-IEEE, 2012).
    2. 2)
    3. 3)
    4. 4)
      • 5. Kishimoto, Y., Kutsuna, Y., Oguri, K.: ‘Detecting motion artifact ECG noise during sleeping by means of a tri-axis accelerometer’. Proc. IEEE EMBS, 2007.
    5. 5)
    6. 6)
      • 1. IEEE Std 802.15.6-2012: ‘IEEE Standard for local and metropolitan area networks – Part 15.6: Wireless Body Area Networks’, 2012.
    7. 7)
    8. 8)
      • 6. Strasser, F., Muma, M., Zoubir, A.M.: ‘Motion artifact removal in ECG signals using multi-resolution thresholding’. Proc. European Signal Processing Conf. (EUSIPCO), 2012, pp. 899903.
    9. 9)
    10. 10)
    11. 11)
      • 9. Lugovaya, T.S.: ‘Biometric human identification based on electrocardiogram’. Master's thesis, Faculty of Computing Technologies and Informatics, Electrotechnical University ‘LETI’, Saint-Petersburg, Russian Federation, 2005.
http://iet.metastore.ingenta.com/content/journals/10.1049/htl.2016.0100
Loading

Related content

content/journals/10.1049/htl.2016.0100
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading