Although several validated seizure detection algorithms are available for convulsive seizures, detection of nonconvulsive seizures remains challenging. In this phase 2 study, we have validated a predefined seizure detection algorithm based on heart rate variability (HRV) using patient‐specific cutoff values. The validation data set was independent from the previously published data set. Electrocardiography (ECG) was recorded using a wearable device (ePatch) in prospectively recruited patients. The diagnostic gold standard was inferred from video–EEG monitoring. Because HRV‐based seizure detection is suitable only for patients with marked ictal autonomic changes, we defined responders as the patients who had a>50 beats/min ictal change in heart rate. Eleven of the 19 included patients with seizures (57.9%) fulfilled this criterion. In this group, the algorithm detected 20 of the 23 seizures (sensitivity: 87.0%). The algorithm detected all but one of the 10 recorded convulsive seizures and all of the 8 focal impaired awareness seizures, and it missed 2 of the 4 focal aware seizures. The median sensitivity per patient was 100% (in nine patients all seizures were detected). The false alarm rate was 0.9/24 h (0.22/night). Our results suggest that HRV‐based seizure detection has high performance in patients with marked autonomic changes.

中文翻译：

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使用心率变异性检测癫痫发作：一项前瞻性验证研究

尽管有几种经过验证的癫痫检测算法可用于惊厥性癫痫发作，但非惊厥性癫痫发作的检测仍然具有挑战性。在这项第 2 阶段研究中，我们使用患者特定的临界值验证了基于心率变异性 (HRV) 的预定义癫痫检测算法。验证数据集独立于先前发布的数据集。使用可穿戴设备 (ePatch) 在前瞻性招募的患者中记录心电图 (ECG)。诊断金标准是从视频脑电图监测中推断出来的。因为基于 HRV 的癫痫检测仅适用于发作期自主神经变化显着的患者，我们将反应者定义为发作期心率变化 >50 次/分钟的患者。19 名癫痫患者中有 11 名 (57.9%) 符合该标准。在这个群体中，该算法检测到 23 次癫痫发作中的 20 次（灵敏度：87.0%）。该算法检测到 10 次记录的惊厥性癫痫发作和所有 8 次局灶性意识障碍癫痫发作中除 1 次以外的所有癫痫发作，并漏掉了 4 次局灶性意识发作中的 2 次。每名患者的中位敏感性为 100%（在 9 名患者中检测到所有癫痫发作）。误报率为 0.9/24 小时（0.22/夜）。我们的结果表明，基于 HRV 的癫痫检测在具有显着自主神经变化的患者中具有很高的性能。9/24 小时（0.22/晚）。我们的结果表明，基于 HRV 的癫痫检测在具有显着自主神经变化的患者中具有很高的性能。9/24 小时（0.22/晚）。我们的结果表明，基于 HRV 的癫痫检测在具有显着自主神经变化的患者中具有很高的性能。