Multimodal Imaging Laboratory, Department of Radiology, University of California at San Diego, La Jolla, CA 92093-0841, USA.
IEEE Trans Biomed Eng. 2009 Nov;56(11):2611-8. doi: 10.1109/TBME.2009.2020694. Epub 2009 Apr 24.
In this study, we perform a comparative study of independent component analysis (ICA) and conventional filtering (CF) for the purpose of artifact reduction from simultaneous gastric EMG and magnetogastrography (MGG). EMG/MGG data were acquired from ten anesthetized pigs by obtaining simultaneous recordings using serosal electrodes (EMG) as well as with a superconducting quantum interference device biomagnetometer (MGG). The analysis of MGG waveforms using ICA and CF indicates that ICA is superior to the CF method in its ability to extract respiration and cardiac artifacts from MGG recordings. A signal frequency analysis of ICA- and CF-processed data was also undertaken using waterfall plots, and it was determined that the two methods produce qualitatively comparable results. Through the use of simultaneous EMG/MGG, we were able to demonstrate the accuracy and trustworthiness of our results by comparison and cross-validation within the framework of a porcine model.
在这项研究中,我们对独立成分分析(ICA)和传统滤波(CF)进行了对比研究,目的是从胃电和胃磁图(MGG)的同步记录中去除伪迹。通过使用浆膜电极(EMG)和超导量子干涉器件生物磁强计(MGG)同时记录,从 10 头麻醉猪中获得了 EMG/MGG 数据。使用 ICA 和 CF 对 MGG 波形进行分析表明,ICA 在从 MGG 记录中提取呼吸和心脏伪迹的能力方面优于 CF 方法。还使用瀑布图对 ICA 和 CF 处理后的数据进行了信号频率分析,结果表明两种方法产生的结果在质量上具有可比性。通过使用同步 EMG/MGG,我们能够通过在猪模型框架内进行比较和交叉验证,证明我们结果的准确性和可靠性。