Abdollahpur Mostafa, Holmqvist Fredrik, Platonov Pyotr G, Sandberg Frida
Department of Biomedical Engineering, Lund University, Lund, Sweden.
Department of Cardiology, Clinical Sciences, Lund University, Lund, Sweden.
Front Physiol. 2021 Apr 8;12:653492. doi: 10.3389/fphys.2021.653492. eCollection 2021.
The autonomic nervous system (ANS) is an important factor in cardiac arrhythmia, and information about ANS activity during atrial fibrillation (AF) may contribute to personalized treatment. In this study we aim to quantify respiratory modulation in the f-wave frequency trend from resting ECG. First, an f-wave signal is extracted from the ECG by QRST cancelation. Second, an f-wave model is fitted to the f-wave signal to obtain a high resolution f-wave frequency trend and an index for signal quality control ( ). Third, respiratory modulation in the f-wave frequency trend is extracted by applying a narrow band-pass filter. The center frequency of the band-pass filter is determined by the respiration rate. Respiration rate is estimated from a surrogate respiration signal, obtained from the ECG using homomorphic filtering. Peak conditioned spectral averaging, where spectra of sufficient quality from different leads are averaged, is employed to obtain a robust estimate of the respiration rate. The envelope of the filtered f-wave frequency trend is used to quantify the magnitude of respiratory induced f-wave frequency modulation. The proposed methodology is evaluated using simulated f-wave signals obtained using a sinusoidal harmonic model. Results from simulated signals show that the magnitude of the respiratory modulation is accurately estimated, quantified by an error below 0.01 Hz, if the signal quality is sufficient ( ). The proposed method was applied to analyze ECG data from eight pacemaker patients with permanent AF recorded at baseline, during controlled respiration, and during controlled respiration after injection of atropine, respectively. The magnitude of the respiratory induce f-wave frequency modulation was 0.15 ± 0.01, 0.18 ± 0.02, and 0.17 ± 0.03 Hz during baseline, controlled respiration, and post-atropine, respectively. Our results suggest that parasympathetic regulation affects the magnitude of respiratory induced f-wave frequency modulation.
自主神经系统（ANS）是心律失常的一个重要因素，而房颤（AF）期间有关ANS活动的信息可能有助于个性化治疗。在本研究中，我们旨在从静息心电图中量化f波频率趋势中的呼吸调制。首先，通过QRST消除从心电图中提取f波信号。其次，将f波模型拟合到f波信号上，以获得高分辨率的f波频率趋势和信号质量控制指标（ ）。第三，通过应用窄带通滤波器提取f波频率趋势中的呼吸调制。带通滤波器的中心频率由呼吸频率确定。呼吸频率从使用同态滤波从心电图获得的替代呼吸信号中估计。采用峰值条件频谱平均法，对来自不同导联的足够质量的频谱进行平均，以获得呼吸频率的稳健估计。滤波后的f波频率趋势的包络用于量化呼吸诱发的f波频率调制的幅度。使用正弦谐波模型获得的模拟f波信号对所提出的方法进行评估。模拟信号的结果表明，如果信号质量足够，呼吸调制的幅度可以准确估计，量化误差低于0.01Hz（ ）。所提出的方法分别应用于分析八名永久性房颤起搏器患者在基线、控制呼吸期间以及注射阿托品后控制呼吸期间记录的心电图数据。在基线、控制呼吸和阿托品注射后，呼吸诱发的f波频率调制幅度分别为0.15±0.01、0.18±0.02和0.17±0.03Hz。我们的结果表明，副交感神经调节会影响呼吸诱发的f波频率调制的幅度。
