JOURNAL ARTICLE

Denoising in Biomedical signals using Ensemble Empirical Mode Decomposition

Megha AgarwalRicha Priyadarshani

Year: 2014 Journal:   IOSR Journal of Electronics and Communication Engineering Vol: 9 (6)Pages: 80-86   Publisher: International organization of Scientific Research (IOSR)

Abstract

In this paper a novel Ensemble Empirical Mode decomposition (EEMD) and adaptive filtering is proposed to filter out Gaussian noise and contact noise contained in raw biomedical signals.Real Biomedical signals from the MIT-BIH database are used to validate the performance of the proposed method.It has been observed that original signals can be significantly enhanced by using the proposed method where the contact noise is eliminated while useful features of original signals are kept.The results also show that the proposed method is quite effective to reduce noise from ECG signals and many other biomedical signals with a very small mean square error.

Keywords:
Hilbert–Huang transform Computer science Noise reduction Decomposition Mode (computer interface) Artificial intelligence Pattern recognition (psychology) Telecommunications Chemistry White noise

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0.59
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Citation History

Topics

ECG Monitoring and Analysis
Health Sciences →  Medicine →  Cardiology and Cardiovascular Medicine
Machine Fault Diagnosis Techniques
Physical Sciences →  Engineering →  Control and Systems Engineering
Phonocardiography and Auscultation Techniques
Health Sciences →  Medicine →  Pulmonary and Respiratory Medicine

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