基于快速傅里叶卷积残差网络的自动心电图间期测量与波形描记
Automated ECG Interval Measurement and Wave Delineation Using Fast Fourier Convolution ResNet
浏览论文内容
中文总结 AI 辅助
本研究针对心电图间期测量的评估缺口，采用快速傅里叶卷积残差网络，在10646份临床心电图上完成大规模评估，明确了模型的精度、偏差及适用心律范围，为临床应用提供了可靠依据。
中文摘要 AI 辅助
准确测量心电图（ECG）间期，包括PR间期、QRS波群时限、QT/QTc间期，是心脏诊断的核心环节，但已发表的ECG描记相关文献几乎仅在小型精选数据库上以 fiducial 点的计时误差评估性能，而非在大型未筛选队列上以临床间期精度评估性能。本研究通过在10646份临床12导联ECG上评估完整端到端 pipeline 填补了这一空白，并报告了首个具备完整统计特征的大规模间期测量精度研究，统计特征包括偏差、95%一致性界限（Bland-Altman法）、自助法置信区间以及按心律分层的误差分析。底层描记由快速傅里叶卷积残差网络（FFCResNet）完成，该模型通过快速傅里叶变换（FFT）将局部时间卷积与全局频谱处理相结合，并添加寄存器令牌以实现上下文特征学习。针对P波、QRS波群、T波这三类波形，分别训练对应的模型，训练所用数据来自6个公开数据库，并采用ECG专用数据增强技术。在10646份ECG上，该系统的QT间期平均绝对误差（MAE）为17.5毫秒[95%置信区间（CI）：16.9-18.2]，Bland-Altman偏差为+8.5毫秒（一致性界限：-68.5至+85.5毫秒）；QRS波群时限MAE为14.8毫秒[95%CI：14.6-15.0]，偏差为+12.6毫秒（一致性界限：-12.3至+37.6毫秒）；心室率MAE为0.8次/分钟。所有偏差均通过Wilcoxon符号秩检验证实具有统计学显著性（p<0.001），但仍处于或接近已发表的窦性心律观察者间变异范围。按心律分层的分析显示，室上性心动过速（SVT）的QT间期误差显著高于窦性心动过缓（SB）和窦性心律（SR），其MAE分别为75.0毫秒、85.3毫秒、9.3毫秒、8.9毫秒，这一结果为该系统的适用范围提供了客观描述。波形分割任务中，P波、QRS波群、T波的内部Dice系数分别为95.5%、98.2%、96.1%，跨数据库Dice系数分别为78.1%、85.5%、74.2%。
英文摘要
Accurate measurement of ECG intervals, including PR, QRS duration, and QT/QTc, is central to cardiac diagnosis, yet the published ECG delineation literature evaluates performance almost exclusively as fiducial-point timing errors on small curated databases, rather than as clinical interval accuracy on large unselected cohorts. We bridge this gap by evaluating a complete end-to-end pipeline on 10,646 clinical 12-lead ECGs and reporting the first large-scale interval measurement accuracy study with full statistical characterisation, including bias, 95% limits of agreement (Bland-Altman), bootstrap confidence intervals, and rhythm-stratified error analysis. The underlying delineation is performed by a Fast Fourier Convolution ResNet (FFCResNet), adapting local temporal convolutions with global spectral processing via FFT and augmented with register tokens for contextual feature learning. Three per-wave models (P, QRS, and T) are trained on six public databases with ECG-specific augmentation. On 10,646 ECGs, the system achieves a QT MAE of 17.5 ms [95% CI: 16.9-18.2], with a Bland-Altman bias of +8.5 ms (LoA: -68.5 to +85.5 ms); a QRS duration MAE of 14.8 ms [95% CI: 14.6-15.0], with a bias of +12.6 ms (LoA: -12.3 to +37.6 ms); and a ventricular rate MAE of 0.8 beats/min. All biases are statistically significant by the Wilcoxon signed-rank test (p < 0.001) but remain within or near published inter-observer variability bounds for sinus rhythms. Rhythm-stratified analysis reveals substantially higher QT errors for supraventricular tachycardias (SVT MAE: 75.0 ms; AVRT MAE: 85.3 ms) than for sinus bradycardia (SB MAE: 9.3 ms) and sinus rhythm (SR MAE: 8.9 ms), providing an honest characterisation of the deployment scope. Wave segmentation achieves internal Dice scores of 95.5%, 98.2%, and 96.1% for P, QRS, and T waves, respectively, and cross-database Dice scores of 78.1%, 85.5%, and 74.2%.
发表机构
- Indian Institute of Science（印度科学学院）
- Gauze
- Waikato District Health Board（怀卡托地区卫生局）
- Christian Medical College（基督教医学院）
机构由 AI 辅助整理，请以论文原文为准。
