Analyzing high-density ECG signals using ICA

Yi Zhu, Amirali Shayan, Wanping Zhang, Tong Lee Chen, Tzyy Ping Jung, Jeng Ren Duann, Scott Makeig, Chung Kuan Cheng

研究成果: 雜誌貢獻期刊論文同行評審

14 引文 斯高帕斯(Scopus)


The analysis of ECG signals is of fundamental importance for cardiac diagnosis. Conventional ECG recordings, however, use a limited number of channels (12) and each records a mixture of activities generated in different parts of the heart. Therefore, direct observation of the ECG signals collected on the body surface is likely an inefficient way to study and diagnose cardiac abnormalities. This study describes new experimental and analytical methods to capture more meaningful ECG component signals, each representing more directly a physical cardiac source. This study first describes a simply applied method for collecting high-density ECG signals. The recorded signals are then separated by independent component analysis (ICA) to obtain spatially fixed and temporally independent component activations. Results from five subjects show that P-, QRS-, and T-waves can be clearly separated from the recordings, suggesting ICA might be an effective and useful tool for high-density ECG analysis, interpretation, and diagnosis.

頁(從 - 到)2528-2537
期刊IEEE Transactions on Biomedical Engineering
出版狀態已出版 - 11月 2008


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