混合时频方法及体表ECG房颤特征研究

Study of Hybrid Time-Frequency Method and Characterization of Atrial Fibrillation from Surface ECG

从体表心电图对房颤信号的时频相关特征进行分析,能及时提供反映患者心房活动动态行为的信息。本文结合Gabor展开和二次Wigner分布各自的优点,把房颤信号的时频分布表示成由自相关和交叉相关项组成的时频原子级数展开,通过Manhattan距离阈值来控制分辨率和干扰项间的平衡,并把该方法与基于矩的瞬时频率(Instantaneous frequency,IFs)估计法结合,进行IFs的鲁棒计算。通过比较10对自发终止与非自发终止型房颤,表明该方法能检测出大多数自发终止型房颤在即将终止时IF呈下降趋势,且比基于峰值检测和谱图分析的方法更稳定,计算更简单。因此,本文的方法为刻画房颤的非平稳特征提供了一种稳健的、计算代价低的无创技术,具有好的临床应用前景。

With the non-invasive analysis of time-frequency features and instantaneous frequency （IFs） of atrial fibrillation （AF） from surface ECG signals, some important information reflecting the dynamic behavior of atria with AF can be extracted. In this paper is proposed a hybrid time-frequency analysis method, which uses the respective advantages of Gahor expansion and quadratic Wigner distribution. Our study showed that the time-frequency representation of atrial fibrillation signals was formulated into the combinations of time-frequency atoms series. By controlling the trade-off of resolution and interference terms via Manhattan distance threshold, this method in combination with moment-based computation obtained more robust estimation of IFs. The comparative analysis of 10 pairs of non-terminating and terminating types of AF signals suggested that hybrid estimation of IFs can detect the reduction of a majority of the fibrillatory rate when AF will end. Meanwhile, this method decreases compute burden and is a more robust way relative to peak-based or spectro- gram method. So, the proposed method would have prospective applications in clinical management of atrial fibrillation.