Key result
A noise reduction approach using a universal modified threshold level-dependent threshold with non-negative garrote threshold function delivered 80.72dB SNR compared with other standard techniques.
Why the study?
Recovering ECG signals from noise is critical for telecardiology health monitoring systems and accurate cardiac disease detection.
A novel DTCWT-based optimal threshold tuning system effectively denoises ECG signals, achieving a high signal-to-noise ratio for potential telecardiology applications.
May enhance ECG quality for telecardiology; leaves open prospective clinical validation before adoption.
The primary output for any health monitoring system that offers telecardiology services is the recovery of the electrocardiographic (ECG) signal from the noised signal. The mechanized investigation of the ECG signal is the most inspiring challenge for accurate detection of cardiac disease. This could be accomplished by eliminating the various noises from the acquired signal. In this paper, a noise reduction approach employing DTCWT is executed on an ECG signal by proposing a noise estimator along with a detailed assessment of the effect of the choice of the threshold value, threshold algorithm and distribution function. The thresholding technique is executed by varying the threshold value ( γ) and its function ( f n ) applied to the proposed estimator (α*). The proposed estimator is scaled by 2 n factor to study its impact on performance metrics and the nature of the reconstructed signal utilizing different distribution functions. The best combination of threshold function with threshold value selection has been chosen in this work from eight different sets of threshold value selection rules along with six distinct threshold functions. The experimental results show that the proposed noise reduction approach using a universal modified threshold level-dependent threshold with non-negative garrote threshold function for normal distribution with n = 3 delivers 80.72dB SNR with a subsequent reduction in MSE and PRD as compared with other standard techniques. An elaborate empirical analysis for selecting the distribution function for obtaining the best possible threshold function and technique is the prime objective and novelty of this research work.
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Prashar et al. (2020) studied cardiac disease. DTCWT-based noise reduction approach vs. other standard techniques was evaluated on Signal-to-noise ratio (SNR). A noise reduction approach using a universal modified threshold level-dependent threshold with non-negative garrote threshold function delivered 80.72dB SNR compared with other standard techniques.
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