ECG signal performance de-noising assessment based on threshold tuning of dual-tree wavelet transform

Autor: Rachid Latif, Abdenbi Abenaou, Wissam Jenkal, Khalifa Elmansouri, Oussama El B’charri
Rok vydání: 2016
Předmět:
Discrete wavelet transform
0209 industrial biotechnology
Engineering
Threshold limit value
Speech recognition
0206 medical engineering
Physics::Medical Physics
Biomedical Engineering
Wavelet Analysis
02 engineering and technology
Data_CODINGANDINFORMATIONTHEORY
Signal
Sensitivity and Specificity
Biomaterials
Set (abstract data type)
Electrocardiography
020901 industrial engineering & automation
Wavelet
Quality (physics)
De-noising
Dual tree wavelet transform
Humans
Radiology
Nuclear Medicine and imaging
Diagnosis
Computer-Assisted
Radiological and Ultrasound Technology
business.industry
Noise (signal processing)
ECG
Research
Wavelet transform
Reproducibility of Results
Pattern recognition
Signal Processing
Computer-Assisted
Realistic noise
General Medicine
020601 biomedical engineering
Threshold tuning
Artificial intelligence
business
Artifacts
Algorithms
Zdroj: BioMedical Engineering
ISSN: 1475-925X
Popis: Background Since the electrocardiogram (ECG) signal has a low frequency and a weak amplitude, it is sensitive to miscellaneous mixed noises, which may reduce the diagnostic accuracy and hinder the physician’s correct decision on patients. Methods The dual tree wavelet transform (DT-WT) is one of the most recent enhanced versions of discrete wavelet transform. However, threshold tuning on this method for noise removal from ECG signal has not been investigated yet. In this work, we shall provide a comprehensive study on the impact of the choice of threshold algorithm, threshold value, and the appropriate wavelet decomposition level to evaluate the ECG signal de-noising performance. Results A set of simulations is performed on both synthetic and real ECG signals to achieve the promised results. First, the synthetic ECG signal is used to observe the algorithm response. The evaluation results of synthetic ECG signal corrupted by various types of noise has showed that the modified unified threshold and wavelet hyperbolic threshold de-noising method is better in realistic and colored noises. The tuned threshold is then used on real ECG signals from the MIT-BIH database. The results has shown that the proposed method achieves higher performance than the ordinary dual tree wavelet transform into all kinds of noise removal from ECG signal. Conclusion The simulation results indicate that the algorithm is robust for all kinds of noises with varying degrees of input noise, providing a high quality clean signal. Moreover, the algorithm is quite simple and can be used in real time ECG monitoring.
Databáze: OpenAIRE
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