کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6011248 | 1579844 | 2015 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Automatic seizure detection using Stockwell transform and boosting algorithm for long-term EEG
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Automatic detection of seizures has vital significance for epileptic diagnosis and can efficiently reduce the workload of the medical staff. In this study, a novel seizure detection method based on Stockwell transform is proposed for intracranial long-term EEG data. The Stockwell transform is employed to obtain the time-frequency representation of the EEG signals, and then the power spectral density is calculated in the time-frequency plane to characterize the behavior of EEG recordings. After that, a classifier based on gradient boosting algorithm is used to make the classification. Finally, the postprocessing is utilized on the outputs of the classifier to obtain more stable and accurate detection results, which includes Kalman filter, threshold judgment, and collar technique. The performance of this method is assessed on the publicly available EEG database which contains approximately 533Â h of intracranial EEG recordings. The experimental results indicate that the proposed method can achieve a satisfactory sensitivity of 94.26%, a specificity of 96.34%, as well as a very short delay time of 0.56Â s.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Epilepsy & Behavior - Volume 45, April 2015, Pages 8-14
Journal: Epilepsy & Behavior - Volume 45, April 2015, Pages 8-14
نویسندگان
Aiyu Yan, Weidong Zhou, Qi Yuan, Shasha Yuan, Qi Wu, Xiuhe Zhao, Jiwen Wang,