Denoising and Baseline Correction of ECG Signals using Sparse Representation
文献类型：会议论文
| ; | |
| 作者 | Zhou, Yichao1; Hu, Xiyuan2 ; Tang, Zhenmin1; Ahn, Andrew C.3
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| 出版日期 | 2015-10 ; 2015-10 |
| 会议日期 | 2015-10 ; 2015-10 |
| 会议地点 | Hangzhou, China ; Hangzhou, China |
| 关键词 | Sparse Representation Sparse Representation Adaptive Signal Separation Adaptive Signal Separation Ecg Denoising Ecg Denoising Baseline Wandering Correction Baseline Wandering Correction |
| 英文摘要 | Removing noise and other artifacts in the electrocardiogram (ECG) is a critical preprocessing step for further heart disease analysis and diagnosis. In this paper, we propose a sparse representation based ECG signal denoising and baseline wandering (BW) correction algorithm. Unlike the traditional filtering-based methods, like Fourier orWavelet transform, which use fixed basis, the proposed algorithm models the ECG signal as superposition of few inner structures plus additive random noise, while those structures can be learned from the input signal or a training set. Using those learned inner structures and their properties, we can accurately approximate the original ECG signal and remove noise and other artifacts like baseline wandering. To demonstrate the robustness and efficacy of the proposed algorithm, we compare it to several state-of-the-art algorithms through both simulated and real-life ECG recordings.; Removing noise and other artifacts in the electrocardiogram (ECG) is a critical preprocessing step for further heart disease analysis and diagnosis. In this paper, we propose a sparse representation based ECG signal denoising and baseline wandering (BW) correction algorithm. Unlike the traditional filtering-based methods, like Fourier orWavelet transform, which use fixed basis, the proposed algorithm models the ECG signal as superposition of few inner structures plus additive random noise, while those structures can be learned from the input signal or a training set. Using those learned inner structures and their properties, we can accurately approximate the original ECG signal and remove noise and other artifacts like baseline wandering. To demonstrate the robustness and efficacy of the proposed algorithm, we compare it to several state-of-the-art algorithms through both simulated and real-life ECG recordings. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/19684]  |
| 专题 | 自动化研究所_智能制造技术与系统研究中心_多维数据分析团队 |
| 通讯作者 | Ahn, Andrew C. |
| 作者单位 | 1.School of Computer Science, Nanjing University of Science and Technology 2.Institute of Automation, Chinese Academy of Sciences 3.BIDMC, MGH, Harvard Medical School |
| 推荐引用方式 GB/T 7714 | Zhou, Yichao,Hu, Xiyuan,Tang, Zhenmin,et al. Denoising and Baseline Correction of ECG Signals using Sparse Representation, Denoising and Baseline Correction of ECG Signals using Sparse Representation[C]. 见:. Hangzhou, China, Hangzhou, China. 2015-10, 2015-10. |
入库方式： OAI收割
来源：自动化研究所
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