Stridh M, Sörnmo L, Meurling C J, Olsson S B
Signal Processing Group, Department Applied Electronics, Lund University, S-221 00 Lund, Sweden.
IEEE Trans Biomed Eng. 2001 Jan;48(1):19-27. doi: 10.1109/10.900245.
Time-frequency analysis is considered for characterizing atrial fibrillation in the surface electrocardiogram (ECG). Variations in fundamental frequency of the fibrillatory waves are tracked by using different time-frequency distributions which are appropriate to short- and long-term variations. The cross Wigner-Ville distribution is found to be particularly useful for short-term analysis due to its ability to handle poor signal-to-noise ratios. In patients with chronic atrial fibrillation, substantial short-term variations exist in fibrillation frequency and variations up to 2.5 Hz can be observed within a few seconds. Although time-frequency analysis is performed independently in each lead, short-term variations in fibrillation frequency often exhibit a similar pattern in the leads V1, V2 and V3. Using different techniques for short- and long-term analysis, it is possible to reliably detect subtle long-term changes in fibrillation frequency, e.g., related to an intervention, which otherwise would have been obscured by spontaneous variations in fibrillation frequency.
时频分析被用于表征体表心电图（ECG）中的房颤。通过使用适用于短期和长期变化的不同时频分布来追踪颤动波基频的变化。交叉维格纳-威利分布因其处理低信噪比的能力而被发现对短期分析特别有用。在慢性房颤患者中，颤动频率存在显著的短期变化，并且在几秒钟内可观察到高达2.5Hz的变化。尽管时频分析是在每个导联中独立进行的，但颤动频率的短期变化在V1、V2和V3导联中通常呈现相似的模式。使用不同的短期和长期分析技术，可以可靠地检测颤动频率的细微长期变化，例如与干预相关的变化，否则这些变化会被颤动频率的自发变化所掩盖。
