Spectral trimming technique: a new approach for suppressing motion artefacts in stress electrocardiography

Abstract

Motion artefacts in electrocardiographic (ECG) signal are suppressed mainly by adaptive noise cancellation and wavelet denoising. While the former requires a motion sensor in addition to ECG electrodes, the latter removes some of the desired low-frequency components in the signal. In this paper spectral trimming technique is being introduced for suppressing the motion artefacts in stress electrocardiography. In this method, Fourier spectral coefficients up to 1.221 Hz of noisy signal are trimmed on the basis of template derived from resting ECG signal in the same subject. The proposed spectral trimming technique has yielded the lowest value of mean ± standard deviation for root mean square error (18.92 ± 8.71) and highest value of the signal to noise ratio (6.439 ± 4.266) as compared to other three methods, namely adaptive noise cancellation, wavelet decomposition and adaptive line enhancement with compatible value of correlation coefficient. Subsequently, spectral trimming technique has been implemented in real-time (deferred by 8.2 s) application for stress electrocardiography. Spectral trimming technique thus offers a method of choice for motion artefact suppression in offline as well as deferred online applications. This method takes care of the limitations of conventional methods such as adaptive noise cancellation or wavelet denoising for suppressing motion artefacts in stress electrocardiography.

Keywords:

• Adaptive noise cancellation
• spectral trimming
• stress electrocardiography
• motion artefact
• wavelet de-noising

Acknowledgment

The authors are grateful to Board of Research in Nuclear Sciences (BRNS), Department of Atomic Energy, Government of India for supporting this research work. The authors are also thankful to Mrs. Anita Behere, Head, Electronics Division, Bhabha Atomic Research Centre, Mumbai (BARC); Dr. Geeta Lathkar, Director, MGMCET for her valuable contribution and support. The authors take this opportunity to acknowledge help from Ms. Jyoti Jethe, Ms. Paridhi Jain and Ms. Sushma Bhat throughout this work. The authors are also thankful to Mr. Nazim Momin, Mr. Suryapal and Mr. B. V. Gaikwad for being a helping hand throughout.

Disclosure statement

No potential conflict of interest was reported by the author(s).