Nguyen Minh Phuong, Schilling Christopher, Dossel Olaf
Institute of Biomedical Engineering, Universita t Karlsruhe (TH), Kaiserstrasse 12, 76131 Karlsruhe, Germany.
Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:368-71. doi: 10.1109/IEMBS.2009.5334668.
Atrial fibrillation (AFib) is the most common cardiac arrhythmia. Areas in atrial tissue with complex fractionated atrial electrograms (CFAEs) are among others responsible for the maintenance of AFib. Those areas are ideal target sites for ablation to eliminate AFib and restore sinus rhythm. As CFAEs are associated with high fibrillatory frequency, automated identification of CFAEs with spectral analysis helps developing objective strategies for AFib ablation. While the application of current techniques is restricted, this paper introduces a new approach to determine characteristic frequencies during AFib. By using Teager's energy operator we calculate the signal envelope and study its spectrum after Fast Fourier Transformation. Harmonic analysis of distinctive peaks in the power spectrum is carried out to assess characteristic frequencies of a CFAE. While the currently available methods only find one dominant frequency in the spectrum of the signal, our method is capable to find multiple characteristic frequencies, if present. Since it is believed that during AFib the atrium is activated by one or multiple wavelets, our method opens new opportunities for investigation of multiple wavelets propagation.
心房颤动（AFib）是最常见的心律失常。心房组织中具有复杂碎裂心房电图（CFAE）的区域是维持AFib的原因之一。这些区域是消除AFib并恢复窦性心律的理想消融靶点。由于CFAE与高颤动频率相关，通过频谱分析自动识别CFAE有助于制定AFib消融的客观策略。虽然当前技术的应用受到限制，但本文介绍了一种确定AFib期间特征频率的新方法。通过使用蒂格能量算子，我们计算信号包络并在快速傅里叶变换后研究其频谱。对功率谱中独特峰值进行谐波分析，以评估CFAE的特征频率。虽然目前可用的方法仅在信号频谱中找到一个主导频率，但我们的方法能够找到多个特征频率（如果存在）。由于人们认为在AFib期间心房由一个或多个小波激活，我们的方法为研究多个小波传播开辟了新机会。
