کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10435049 | 910806 | 2015 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Denoising preterm EEG by signal decomposition and adaptive filtering: A comparative study
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مهندسی پزشکی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Denoising preterm EEG by signal decomposition and adaptive filtering: A comparative study Denoising preterm EEG by signal decomposition and adaptive filtering: A comparative study](/preview/png/10435049.png)
چکیده انگلیسی
Electroencephalography (EEG) from preterm infant monitoring systems is usually contaminated by several sources of noise that have to be removed in order to correctly interpret signals and perform automated analysis reliably. Band-pass and adaptive filters (AF) continue to be systematically applied, but their efficacy may be decreased facing preterm EEG patterns such as the tracé alternant and slow delta-waves. In this paper, we propose the combination of EEG decomposition with AF to improve the overall denoising process. Using artificially contaminated signals from real EEGs, we compared the quality of filtered signals applying different decomposition techniques: the discrete wavelet transform, the empirical mode decomposition (EMD) and a recent improved version, the complete ensemble EMD with adaptive noise. Simulations demonstrate that introducing EMD-based techniques prior to AF can reduce up to 30% the root mean squared errors in denoised EEGs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Medical Engineering & Physics - Volume 37, Issue 3, March 2015, Pages 315-320
Journal: Medical Engineering & Physics - Volume 37, Issue 3, March 2015, Pages 315-320
نویسندگان
X. Navarro, F. Porée, A. Beuchée, G. Carrault,