ECG Signal In-Band Noise De-Noising Base on EMD

Xiong, Hui; Zheng, Chun-Hou; Liu, Jinzhen; Song, Limei

doi:10.1142/s0218126619500178

Cited by 8 publications

(2 citation statements)

References 15 publications

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“…In recent years, the Empirical Mode Decomposition (EMD) method has attracted the attention of scholars because it completely got rid of the limitations of time-frequency analysis [ 23 , 24 ]. Based on the EMD method, Xiong filtered each of the decomposed IMF components and reconstructed the denoised signal [ 25 ]. In 2017, Giovanni proposed a method of extracting heartbeat and respiratory signals by using the EMD method in a certain range combined with Doppler information [ 26 ].…”

Section: Introductionmentioning

confidence: 99%

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

Liu

Cheng

et al. 2022

Sensors

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The identification of weak vital signs has always been one of the difficulties in the field of life detection. In this paper, a novel vital sign detection and extraction method with high efficiency, high precision, high sensitivity and high signal-to-noise ratio is proposed. Based on the NVA6100 pulse radar system, the radar matrix which contains several radar pulse detection signals is received. According to the characteristics of vital signs and radar matrices, the Singular Value Decomposition (SVD) is adopted to perform signal denoising and decomposition after preprocessing, and the temporal and spatial eigenvectors of each principal component are obtained. Through the energy proportion screening, the Wavelet Transform decomposition and linear trend suppression, relatively pure vital signs in each principal component, are obtained. The human location is detected by the Energy Entropy of spatial eigenvectors, and the respiratory signal and heartbeat signal are restored through a Butterworth Filter and an MTI harmonic canceller. Finally, through an analysis of the performance of the algorithm, it is proved to have the properties of efficiency and accuracy.

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Section: Introductionmentioning

confidence: 99%

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

Liu

Cheng

et al. 2022

Sensors

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“…However, the ECG signals are easy to be affected by instruments and human activities. There are several situations that interfere with ECG signals [12]- [18]. First, the baseline drift is usually caused by human respiration and myocardial excitation when the frequency is lower than 1 Hz.…”

Section: Introductionmentioning

confidence: 99%

Signal Analysis of Electrocardiogram and Statistical Evaluation of Myocardial Enzyme in the Diagnosis and Treatment of Patients With Pneumonia

Zhou

Zeng

et al. 2019

IEEE Access

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Pneumonia is a common disease in patients. This paper discusses the signal processing techniques of electrocardiogram (ECG) and the statistical analysis of myocardial enzymes in the diagnosis and treatment of patients with pneumonia and analyzes its significance. Detecting the activity of creatine kinase (CK), isoenzyme (CK-MB), and cardiac troponin T (CTnT) before and after treatment in patients with pneumonia and recording the changes of the electrocardiogram with non-invasive bedside conventional electrocardiogram can be useful for medical diagnosis. In addition, in order to eliminate the ECG signal noise to improve the accuracy of analysis and diagnosis, we have introduced a Butterworth filter to achieve the suppression of interference signals. Moreover, the Butterworth filter method is used to denoise the ECG signal, and the selection of wavelet function, the analysis of noise frequency band, and the threshold processing are solved accordingly. This method has the characteristics of simple calculation and fast processing speed. It can effectively suppress baseline drift noise and improve the overall operation speed. The experimental results show that the proposed method can well filter baseline drift, power frequency interference, EMG interference, and other high-frequency interference in ECG signals, and the real-time performance of the Butterworth filter method in the sampling process has good performance, which provides help for diagnosis. Via comparing and analyzing different ECG signal parameters between the groups, the serum levels of CK, CK-MB, and troponin are demonstrated to be significantly increased with the severity of the disease in patients with pneumonia. Abnormal changes in the ECG indicate that the myocardium may be affected after pneumonia in patients. The detection of CK-MB and troponin levels in the serum of patients with pneumonia has very high sensitivity and specificity. Recording electrocardiogram has good intuitive utility. ECG and myocardial enzyme monitoring are of great significance in the diagnosis and treatment of the development of the disease in patients with pneumonia. INDEX TERMS Electrocardiogram signal, Butterworth filter, interference signal, pneumonia, myocardial enzyme.

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Restraining EMI of Displacement Sensors Based on Wavelet Fuzzy Threshold Denoising

Zhang

Zhou

Dong

et al. 2020

Lecture Notes in Electrical Engineering

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ECG Signal In-Band Noise De-Noising Base on EMD

Cited by 8 publications

References 15 publications

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

A Vital Signs Fast Detection and Extraction Method of UWB Impulse Radar Based on SVD

Signal Analysis of Electrocardiogram and Statistical Evaluation of Myocardial Enzyme in the Diagnosis and Treatment of Patients With Pneumonia

Restraining EMI of Displacement Sensors Based on Wavelet Fuzzy Threshold Denoising

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