Facultad de Ingeniería, Universidad Anáhuac México, Huixquilucan 52786, Estado de Mexico, Mexico.
Departamento de Estudios en Ingeniería para la Innovación, Universidad Iberoamericana Ciudad de México, Ciudad de México 01219, Mexico.
Sensors (Basel). 2020 Sep 25;20(19):5483. doi: 10.3390/s20195483.
Most methods for sudden cardiac death (SCD) prediction require long-term (24 h) electrocardiogram recordings to measure heart rate variability (HRV) indices or premature ventricular complex indices (with the heartprint method). This work aimed to identify the best combinations of HRV and heartprint indices for predicting SCD based on short-term recordings (1000 heartbeats) through a support vector machine (SVM). Eleven HRV indices and five heartprint indices were measured in 135 pairs of recordings (one before an SCD episode and another without SCD as control). SVMs (defined with a radial basis function kernel with hyperparameter optimization) were trained with this dataset to identify the 13 best combinations of indices systematically. Through 10-fold cross-validation, the best area under the curve (AUC) value as a function of γ (gamma) and cost was identified. The predictive value of the identified combinations had AUCs between 0.80 and 0.86 and accuracies between 80 and 86%. Further SVM performance tests on a different dataset of 68 recordings (33 before SCD and 35 as control) showed AUC = 0.68 and accuracy = 67% for the best combination. The developed SVM may be useful for preventing imminent SCD through early warning based on electrocardiogram (ECG) or heart rate monitoring.
大多数用于预测心源性猝死（SCD）的方法都需要进行长期（24 小时）心电图记录，以测量心率变异性（HRV）指数或室性早搏指数（使用心印法）。本研究旨在通过支持向量机（SVM），基于短期记录（1000 次心跳），确定用于预测 SCD 的最佳 HRV 和心印指数组合。在 135 对记录（一次在 SCD 发作前，另一次无 SCD 作为对照）中测量了 11 个 HRV 指数和 5 个心印指数。使用该数据集通过 SVM（定义为具有超参数优化的径向基函数核）进行训练，以系统地识别 13 个最佳指数组合。通过 10 倍交叉验证，确定了作为γ（gamma）和成本函数的最佳曲线下面积（AUC）值。确定组合的预测值的 AUC 在 0.80 到 0.86 之间，准确性在 80 到 86%之间。对 68 次记录的另一数据集（33 次在 SCD 之前，35 次作为对照）进行的进一步 SVM 性能测试显示，最佳组合的 AUC 为 0.68，准确性为 67%。开发的 SVM 可能有助于通过基于心电图（ECG）或心率监测的预警来预防即将发生的 SCD。
