Tyler J Newton, Mitchell A Frankel, Zoë Tosi, Avidor B Kazen, Vamshi K Muvvala, Tobias Loddenkemper, Mark C Spitz, Laura Strom, Daniel Friedman, Mark J Lehmkuhle
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Automated algorithms are necessary for review of extended-duration reduced-channel EEG, yet current clinical support software is designed only for full-montage recordings.</p><p><strong>Methods: </strong>The performance of a novel automated seizure detection algorithm for reduced-channel EEG (Epitel) was evaluated in a clinical validation study involving 50 participants (31 with seizures) with diverse demographic and seizure representation.</p><p><strong>Results: </strong>The algorithm demonstrated an event-level sensitivity of 86.2% (95% confidence interval [CI] = 79.5%-93.2%) and a false detection rate of .162 per hour (95% CI = .116-.221), which is comparable to the performance of current clinical software for full-montage EEG. Performance varied by electrographic seizure type, with 91.4% sensitivity for focal evolving to generalized seizures, 86.7% for generalized seizures, and 77.3% for focal seizures. 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引用次数: 0
摘要
目的:减少通道可穿戴脑电图(EEG)可克服传统的动态电图癫痫发作监测在长时间使用过程中的可及性和患者舒适度限制。自动算法是必要的审查延长持续时间减少通道脑电图,但目前的临床支持软件是专为全蒙太奇录音。方法:在一项涉及50名不同人口统计学和癫痫发作代表的参与者(31名有癫痫发作)的临床验证研究中,评估了一种新型的减少通道脑电图(Epitel)自动癫痫发作检测算法的性能。结果:该算法的事件级灵敏度为86.2%(95%置信区间[CI] = 79.5% ~ 93.2%),误检率为每小时0.162次(95% CI = 0.116 ~ 0.221),与目前全蒙太奇脑电图临床软件的性能相当。不同电图发作类型的表现不同,局灶性发作演变为全局性发作的敏感性为91.4%,全局性发作的敏感性为86.7%,局灶性发作的敏感性为77.3%。该算法在6-21岁的儿童参与者(83%的敏感性)和22岁以上的成年人(90%的敏感性)以及门诊(80%)和癫痫监测单元(EMU)监测环境(87.5%)中都保持了稳健的表现。动态监测环境下的误检率(。290例假阳性[FP]检测/小时),所有涉及儿科参与者,明显高于欧洲经济联盟(0.136)FP/h),表明有明显需要改进的区域,以进行不受限制的家庭监测。该算法的补充Confidence度量,旨在产生对算法的信任,显示出与检测精度的强相关性。意义:这些结果表明,该算法可以为长时间减少通道可穿戴脑电图的审查提供重要支持,实现不受日常生活限制的电图癫痫监测。
Validation of a discrete electrographic seizure detection algorithm for extended-duration, reduced-channel wearable EEG.
Objective: Reduced-channel wearable electroencephalography (EEG) may overcome the accessibility and patient comfort limitations of traditional ambulatory electrographic seizure monitoring during extended-duration use. Automated algorithms are necessary for review of extended-duration reduced-channel EEG, yet current clinical support software is designed only for full-montage recordings.
Methods: The performance of a novel automated seizure detection algorithm for reduced-channel EEG (Epitel) was evaluated in a clinical validation study involving 50 participants (31 with seizures) with diverse demographic and seizure representation.
Results: The algorithm demonstrated an event-level sensitivity of 86.2% (95% confidence interval [CI] = 79.5%-93.2%) and a false detection rate of .162 per hour (95% CI = .116-.221), which is comparable to the performance of current clinical software for full-montage EEG. Performance varied by electrographic seizure type, with 91.4% sensitivity for focal evolving to generalized seizures, 86.7% for generalized seizures, and 77.3% for focal seizures. The algorithm maintained robust performance in both pediatric participants aged 6-21 years (83% sensitivity) and adults aged 22+ years (90% sensitivity), as well as in ambulatory (80%) and epilepsy monitoring unit (EMU) monitoring environments (87.5%). The false detection rate in ambulatory monitoring environments (.290 false positive [FP] detections/h), all of which involved pediatric participants, was notably higher than in the EMU (.136 FP/h), indicating an area with clear need for improvement for unrestricted at-home monitoring. The algorithm's supplemental Confidence metric, designed to engender trust in the algorithm, showed a strong correlation with detection precision.
Significance: These results suggest that this algorithm can provide crucial support for review of extended-duration reduced-channel wearable EEG, enabling electrographic seizure monitoring with no restrictions on a person's daily life.
期刊介绍:
Epilepsia is the leading, authoritative source for innovative clinical and basic science research for all aspects of epilepsy and seizures. In addition, Epilepsia publishes critical reviews, opinion pieces, and guidelines that foster understanding and aim to improve the diagnosis and treatment of people with seizures and epilepsy.