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Abstract Introduction The analysis of electrocardiogram (ECG) signals allows the experts to diagnosis several cardiac disorders. However, the accuracy of such diagnostic depends on the signals quality. In this paper it is proposed a simple method for power-line interference (PLI) removal based on the wavelet decomposition, without the use of thresholding techniques. Methods This method consists in identifying the ECG and noise frequency range for further zeroing wavelet detail coefficients in the subbands with no ECG coefficients in the frequency content. Afterward, the enhanced ECG signal is obtained by the inverse discrete wavelet transform (IDWT). In order to choose the wavelet function, several experiments were performed with synthetic signals with worse Signal-to-Noise Ratio (SNR). Results Considering the relative error metrics and runtime, the best wavelet function for denoising was Symlet 8. Twenty synthetic ECG signals with different features and eight real ECG signals, obtained in the Physionet Challenge 2011, were used in the experiments. Results show the advantage of the proposed method against thresholding and notch filter techniques, considering classical metrics of assessment. The proposed method performed better for 75% of the synthetic signals and for 100% of the real signals considering most of the evaluation measures, when compared with a thresholding technique. In comparison with the notch filter, the proposed method is better for all signals. Conclusion The proposed method can be used for PLI removal in ECG signals with superior performance than thresholding and notch filter techniques. Also, it can be applied for high frequencies denoising even without a priori frequencies knowledge.
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Objective To definite the status of tone of autonomic nervous system during water immersion process by analyzing the nonlinear characteristic of ECG signals;To explore the relation of approximate entropy(ApEn),scaling exponent(?) changes and modulation function status of autonomic nervous system.Methods The ECG signals of rats during the process of restraint stress(RS),water-immersion restraint stress(WRS) and Vagotomy and Water-immersion restraint stress(vagotomy-WRS) were recorded.The ApEn and ? of RR intervals were calculated.Results After the stress,the differences of the value of ApEn and ? of RR intervals between RS and vagotomy-WRS groups and between different periods in vagotomy-WRS group were not significant.The value of ApEn increased in WRS group and decreased in RS group significantly.Compared with pre-stress,? showed decreased trend,all of the values smaller than 0.5 in WRS group and increased obviously,most values larger than 0.5 in RS group.Conclusion The increased ApEn and decreased ? indicates a higher intensity of parasympathetic activity.The parasympathetic activity is the predominant response of autonomic nervous system during water immersion process.
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Objective To find a method for denoising of ECG signals during spaceflight.Method According to noise character of ECG during spaceflight,a new denoising method that combines wavelet transform and shape filter was put forward.Result By practical application and simulation test,it was proved that this method could eliminate efficiently noise from ECG during spaceflight.Conclusion The method that combines wavelet transform and shape filter can be used for ECG denoising during spaceflight.
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Objective To investigate the methods for EGG data compression and accurate QRS detection. Methods The quick fitting of LADT was improved and the combination of the improved quick fitting of LADT and neural network was used for the detection of the location of the QRS complex. Results Test by the MIT/BIH arrhythmia database revealed high accuracy rate of QRS detection and easy real time application. Conclusion The purposes of accurate detection of QRS with a little time are realized.