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Application of Adaptive Filters in Denoising Magnetocardiogram Signals

机译:自适应滤波器在去噪磁心电图信号中的应用

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Magnetocardiography (MCG) is the measurement of weak magnetic fields from the heart using Superconducting QUantum Interference Devices (SQUID). Though the measurements are performed inside magnetically shielded rooms (MSR) to reduce external electromagnetic disturbances, interferences which are caused by sources inside the shielded room could not be attenuated. The work presented here reports the application of adaptive filters to denoise MCG signals. Two adaptive noise cancellation approaches namely least mean squared (LMS) algorithm and recursive least squared (RLS) algorithm are applied to denoise MCG signals and the results are compared. It is found that both the algorithms effectively remove noisy wiggles from MCG traces; significantly improving the quality of the cardiac features in MCG traces. The calculated signal-to-noise ratio (SNR) for the denoised MCG traces is found to be slightly higher in the LMS algorithm as compared to the RLS algorithm. The results encourage the use of adaptive techniques to suppress noise due to power line frequency and its harmonics which occur frequently in biomedical measurements.
机译:磁插片造影(MCG)是使用超导量子干涉装置(鱿鱼)从心脏的弱磁场的测量。尽管在磁屏蔽室(MSR)内进行测量以减少外部电磁干扰,但是由屏蔽室内的源引起的干扰不能衰减。此处提出的工作报告了自适应滤波器的应用到Denoise MCG信号。两个自适应噪声消除方法接近即最小值平方(LMS)算法,并且递归最小二乘(RLS)算法应用于去噪MCG信号并且比较结果。发现算法两者都有效地从MCG迹线中删除嘈杂的摇摆;显着提高MCG痕迹中的心脏功能的质量。与RLS算法相比,LMS算法中的计算的信噪比(SNR)被发现在LMS算法中略高。结果鼓励使用自适应技术来抑制由于电力线频率和谐波引起的噪声,这些谐波在生物医学测量中经常发生。

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