目的:评估为消费者可穿戴式(AppleWatch)设备上的强直阵挛性癫痫发作(TCS)监测而开发的自定义应用程序的性能。
方法:招募有惊厥性癫痫发作史的参与者进行癫痫监测单位(EMU)或门诊(AMB)监测;没有癫痫的参与者(正常对照[NC])也纳入AMB组。EMU和AMB参与者都戴着带有研究应用程序的AppleWatch,该应用程序连续记录了加速度计和光电体积描记术(PPG)信号,并在测试期间运行了固定和冷冻的强直阵挛性癫痫发作检测算法。该算法先前已经使用单独的训练数据集开发和验证。所有EMU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。通过灵敏度对设备性能进行了表征,并与以前的监测设备进行了比较,误报率(FAR;每24小时误报),精度,和检测延迟(延迟)。
结果:EMU组有85名参与者(4,279小时,来自15名参与者的19名TCS)在四个EMU中注册;AMB组有21名参与者(13名门诊患者,8NC,6,735小时,来自3名参与者的10个TCS)。除一名AMB参与者外,所有参与者都完成了研究。EMU组的设备性能包括灵敏度为100%[95%置信区间(CI)79-100%];每24小时的FAR为0.05[0.02,0.08];精度为68%[48%,83%];延迟为32.07s[标准偏差(std)10.22s]。AMB组的灵敏度为100%[66-100%];每24小时的FAR为0.13[0.08,0.24];精度为22%[11%,37%];延迟为37.38s[13.24s]。值得注意的是,1名AMB参与者对31例假警报中的8例负责.不包括该参与者的AMBFAR为每24小时0.10[0.07,0.14]。
结论:这项研究证明了在癫痫患者的日常使用中,在流行的消费者可穿戴设备(AppleWatch)上进行TCS监测的实用性。与之前在EMU和AMB环境中报告的相比,该监控应用程序具有高灵敏度和低得多的FAR。
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.
CONCLUSIONS: 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.