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多模态可穿戴 EEG、EMG 和加速度计测量可提高强直阵挛性癫痫发作检测的准确性。

Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection.

机构信息

Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.

Laboratory for Epilepsy Research, KU Leuven, Leuven, Belgium.

出版信息

Physiol Meas. 2024 Jun 7;45(6). doi: 10.1088/1361-6579/ad4e94.

Abstract

. This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection.. We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2. The wearable Sensor Dot (Byteflies) was used to measure behind-the-ear EEG, electromyography (EMG), electrocardiography, accelerometry (ACC) and gyroscope. We evaluated automatic unimodal detection of TCSs, using sensitivity, precision, false positive rate (FPR) and F1-score. Subsequently, we fused the different modalities and again assessed performance. Algorithm-labeled segments were then provided to two experts, who annotated true positive TCSs, and discarded false positives.. Wearable EEG outperformed the other single modalities with a sensitivity of 100% and a FPR of 10.3/24 h. The combination of wearable EEG and EMG proved most clinically useful, delivering a sensitivity of 97.7%, an FPR of 0.4/24 h, a precision of 43%, and an F1-score of 59.7%. The highest overall performance was achieved through the fusion of wearable EEG, EMG, and ACC, yielding a sensitivity of 90.9%, an FPR of 0.1/24 h, a precision of 75.5%, and an F1-score of 82.5%.. In TCS detection with a wearable device, combining EEG with EMG, ACC or both resulted in a remarkable reduction of FPR, while retaining a high sensitivity.. Adding wearable EEG could further improve TCS detection, relative to extracerebral-based systems.

摘要

. 本文旨在探讨使用耳后双通道可穿戴脑电图(EEG)检测强直阵挛性发作(TCS)的可能性,并评估其在 TCS 检测中对非 EEG 模态的附加价值。. 我们纳入了来自欧洲多中心研究 SeizeIT2 的 27 名参与者,共 44 次 TCS。使用可穿戴 Sensor Dot(Byteflies)测量耳后 EEG、肌电图(EMG)、心电图、加速度计(ACC)和陀螺仪。我们评估了 TCS 的自动单模态检测,使用敏感性、准确性、假阳性率(FPR)和 F1 评分。随后,我们融合了不同的模态,并再次评估了性能。然后将算法标记的片段提供给两位专家,他们标记了真正的 TCS 阳性,并排除了假阳性。. 可穿戴 EEG 的性能优于其他单模态,敏感性为 100%,FPR 为 10.3/24 h。可穿戴 EEG 和 EMG 的组合在临床上最有用,敏感性为 97.7%,FPR 为 0.4/24 h,准确性为 43%,F1 得分为 59.7%。通过融合可穿戴 EEG、EMG 和 ACC,可实现最高的整体性能,敏感性为 90.9%,FPR 为 0.1/24 h,准确性为 75.5%,F1 得分为 82.5%。. 在使用可穿戴设备进行 TCS 检测中,将 EEG 与 EMG、ACC 或两者结合使用可显著降低 FPR,同时保持高敏感性。. 添加可穿戴 EEG 可以进一步提高 TCS 检测的性能,与基于脑外的系统相比。

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