Key result
Spectral trimming technique yielded the lowest root mean square error and highest signal to noise ratio compared to other methods for stress ECG artefact suppression.
Why the study?
Existing methods to suppress motion artefacts in ECG signals either require an additional motion sensor or remove desired low-frequency signal components.
Does the spectral trimming technique improve motion artefact suppression in stress electrocardiography compared to conventional methods?
Does the spectral trimming technique improve motion artefact suppression in stress electrocardiography compared to conventional methods?
The spectral trimming technique offers an effective new approach for suppressing motion artefacts in stress electrocardiography, outperforming conventional methods in signal-to-noise ratio and error reduction.
Answers are grounded in this paper and cite their sources.
Hypothesis-generating for sensor-free artefact suppression in stress ECG; prospective validation required before clinical adoption.
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.
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Lakhe et al. (2020) studied Motion artefacts in stress electrocardiography. Spectral trimming technique vs. Adaptive noise cancellation, wavelet decomposition, and adaptive line enhancement was evaluated on Root mean square error and signal to noise ratio. Spectral trimming technique yielded the lowest root mean square error and highest signal to noise ratio compared to other methods for stress ECG artefact suppression.
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