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前瞻性多中心研究:在癫痫监测单元和动态环境中使用 Apple Watch 进行持续强直阵挛性癫痫发作监测。

Prospective multicenter study of continuous tonic-clonic seizure monitoring on Apple Watch in epilepsy monitoring units and ambulatory environments.

机构信息

Johns Hopkins University, Department of Neurology, United States.

University of Maryland Medical Center, United States.

出版信息

Epilepsy Behav. 2024 Sep;158:109908. doi: 10.1016/j.yebeh.2024.109908. Epub 2024 Jul 3.

Abstract

OBJECTIVE

Evaluate the performance of a custom application developed for tonic-clonic seizure (TCS) monitoring on a consumer-wearable (Apple Watch) device.

METHODS

Participants with a history of convulsive epileptic seizures were recruited for either Epilepsy Monitoring Unit (EMU) or ambulatory (AMB) monitoring; participants without epilepsy (normal controls [NC]) were also enrolled in the AMB group. Both EMU and AMB participants wore an Apple Watch with a research app that continuously recorded accelerometer and photoplethysmography (PPG) signals, and ran a fixed-and-frozen tonic-clonic seizure detection algorithm during the testing period. This algorithm had been previously developed and validated using a separate training dataset. All EMU convulsive events were validated by video-electroencephalography (video-EEG); AMB events were validated by caregiver reporting and follow-ups. Device performance was characterized and compared to prior monitoring devices through sensitivity, false alarm rate (FAR; false-alarms per 24 h), precision, and detection delay (latency).

RESULTS

The EMU group had 85 participants (4,279 h, 19 TCS from 15 participants) enrolled across four EMUs; the AMB group had 21 participants (13 outpatient, 8 NC, 6,735 h, 10 TCS from 3 participants). All but one AMB participant completed the study. Device performance in the EMU group included a sensitivity of 100 % [95 % confidence interval (CI) 79-100 %]; an FAR of 0.05 [0.02, 0.08] per 24 h; a precision of 68 % [48 %, 83 %]; and a latency of 32.07 s [standard deviation (std) 10.22 s]. The AMB group had a sensitivity of 100 % [66-100 %]; an FAR of 0.13 [0.08, 0.24] per 24 h; a precision of 22 % [11 %, 37 %]; and a latency of 37.38 s [13.24 s]. Notably, a single AMB participant was responsible for 8 of 31 false alarms. The AMB FAR excluding this participant was 0.10 [0.07, 0.14] per 24 h.

DISCUSSION

This study demonstrates the practicability of TCS monitoring on a popular consumer wearable (Apple Watch) in daily use for people with epilepsy. The monitoring app had a high sensitivity and a substantially lower FAR than previously reported in both EMU and AMB environments.

摘要

目的

评估一款针对强直阵挛性癫痫发作(TCS)监测而开发的定制应用在消费级可穿戴设备(Apple Watch)上的性能。

方法

招募了有癫痫性抽搐病史的参与者,他们分别接受癫痫监测单元(EMU)或门诊(AMB)监测;无癫痫(正常对照[NC])的参与者也被纳入 AMB 组。EMU 和 AMB 组参与者均佩戴配备研究应用的 Apple Watch,该应用可连续记录加速度计和光容积描记图(PPG)信号,并在测试期间运行固定和冻结的强直阵挛性癫痫发作检测算法。该算法之前是使用单独的训练数据集开发和验证的。所有 EMU 的惊厥事件均通过视频脑电图(video-EEG)进行验证;AMB 事件通过护理人员报告和随访进行验证。通过敏感性、误报率(FAR;每 24 小时的误报数)、精确度和检测延迟(潜伏期),对设备性能进行了特征描述并与之前的监测设备进行了比较。

结果

EMU 组有 85 名参与者(4279 小时,15 名参与者中的 19 次 TCS)在四个 EMU 中接受监测;AMB 组有 21 名参与者(13 名门诊患者,8 名 NC,6735 小时,3 名参与者中的 10 次 TCS)。除了一名 AMB 参与者外,所有参与者均完成了研究。EMU 组的设备性能包括敏感性为 100%[95%置信区间(CI)79-100%];误报率为 0.05[0.02,0.08]每 24 小时;精确度为 68%[48%,83%];潜伏期为 32.07 秒[标准差(std)为 10.22 秒]。AMB 组的敏感性为 100%[66-100%];误报率为 0.13[0.08,0.24]每 24 小时;精确度为 22%[11%,37%];潜伏期为 37.38 秒[13.24 秒]。值得注意的是,一名 AMB 参与者的 31 次误报中有 8 次是单独造成的。排除该参与者后,AMB 的误报率为 0.10[0.07,0.14]每 24 小时。

讨论

这项研究证明了在日常使用中,TCS 监测在流行的消费级可穿戴设备(Apple Watch)上的实用性。与 EMU 和 AMB 环境中的先前报告相比,该监测应用的敏感性高,误报率显著降低。

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