Multimodal detection of typical absence seizures in home environment with wearable electrodes

IF 1.3 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Frontiers in signal processing Pub Date : 2022-10-17 DOI:10.3389/frsip.2022.1014700
C. Chatzichristos, Lauren Swinnen, Jaiver Macea, Miguel M. C. Bhagubai, W. van Paesschen, M. de Vos
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引用次数: 6

Abstract

Patients with absence epilepsy fail to report almost 90% of their seizures. The clinical gold standard to assess absence seizures is video-electroencephalography (vEEG) recorded in the hospital, an expensive and obtrusive procedure which requires also extended reviewing time. Wearable sensors, which allow the recording of electroencephalography (EEG), accelerometer and gyroscope have been used to monitor epileptic patients in their home environment for the first time. We developed a pipeline for accurate and robust absence seizure detection while reducing the review time of the long recordings. Our results show that multimodal analysis of absence seizures can improve the robustness to false alarms, while retaining a high sensitivity in seizure detection.
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基于可穿戴电极的家庭环境中典型失神发作的多模态检测
缺乏性癫痫患者几乎90%的癫痫发作没有报告。评估失神发作的临床黄金标准是在医院记录的视频脑电图(vEEG),这是一项昂贵且突发性的程序,也需要延长检查时间。可以记录脑电图(EEG)的可穿戴传感器、加速度计和陀螺仪首次被用于监测癫痫患者的家庭环境。我们开发了一种准确而稳健的缺失发作检测管道,同时减少了长记录的审查时间。我们的研究结果表明,多模态分析可以提高对假警报的鲁棒性,同时在癫痫检测中保持较高的灵敏度。
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