首页> 外文会议>Computing in Cardiology 2012.;vol. 39. >Evaluation of Blind Source Separation methods for noise reduction in BSPM recorded during exercise
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Evaluation of Blind Source Separation methods for noise reduction in BSPM recorded during exercise

机译:运动中记录的BSPM降噪的盲源分离方法评估

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摘要

The application of Blind Source Separation (BSS) is now an accepted technique in the feld of biosignal processing. The reduction of noise (biological and technical artifacts) in body surface potential mapping recorded during exercise is a frequent goal. Two BSS methods (FastICA and temporal decorrelation) for removing noise are compared with respect to the ability to isolate artifacts. Datasets from 13 subjects were studied. For quantification of the results the changes of the root-mean-square (RMS) before and after denoising were analyzed. The use of both BSS methods improved the signal-to-noise-ratios (SNR) in a range of −4 to −10 dB.
机译:盲源分离(BSS)的应用现已成为生物信号处理领域公认的技术。减少运动过程中记录的体表电位图中的噪声(生物和技术伪迹)是一个常见的目标。针对隔离伪像的能力,比较了两种用于去除噪声的BSS方法(FastICA和时间去相关)。研究了来自13个受试者的数据集。为了量化结果,分析了去噪前后的均方根(RMS)变化。两种BSS方法的使用都将信噪比(SNR)改善了-4至-10 dB。

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