Nijsen Tamara M E, Arends Johan B A M, Griep Paul A M, Cluitmans Pierre J M
Epilepsy Centre Kempenhaeghe, Sterkselseweg 65, 5591 VE Heeze, The Netherlands.
Epilepsy Behav. 2005 Aug;7(1):74-84. doi: 10.1016/j.yebeh.2005.04.011.
Seizure detection results based on the visual analysis of three-dimensional (3D) accelerometry (ACM) and video/EEG recordings are reported for 18 patients with severe epilepsy. They were monitored for 36 hours during which 897 seizures were detected. This was seven times higher than the number of seizures reported by nurses during the registration period. The results in this article demonstrate that 3D ACM is a valuable sensing method for seizure detection in this population. Four hundred twenty-eight (48%) seizures were detected by ACM. With 3D ACM alone it was possible to detect all the seizures in 10 of the 18 patients. Three-dimensional ACM also was complementary to EEG in our population. ACM patterns during seizures were stereotypical in 95% of the motor seizures. These characteristic patterns are a starting point for automated seizure detection.
报告了对18例严重癫痫患者基于三维(3D)加速度测量法(ACM)以及视频/脑电图记录的视觉分析得出的癫痫发作检测结果。对他们进行了36小时的监测,在此期间检测到897次癫痫发作。这比登记期间护士报告的癫痫发作次数高出7倍。本文的结果表明,3D ACM是该人群癫痫发作检测的一种有价值的传感方法。通过ACM检测到428次(48%)癫痫发作。仅使用3D ACM就有可能在18例患者中的10例中检测到所有癫痫发作。在我们的研究人群中,三维ACM对脑电图也具有互补性。95%的运动性癫痫发作期间的ACM模式是刻板的。这些特征模式是自动癫痫发作检测的起点。