کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6268687 1614637 2014 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An efficient seizure prediction method using KNN-based undersampling and linear frequency measures
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب (عمومی)
پیش نمایش صفحه اول مقاله
An efficient seizure prediction method using KNN-based undersampling and linear frequency measures
چکیده انگلیسی
The proposed algorithm was evaluated on seizures and 434.9 h of interictal data from 18 patients of Freiburg database. It predicted 100% of seizures with average false alarm rate of 0.13 per hour ranging between 0 and 0.39. Furthermore, G-Mean and F-measure were used for validation which were 0.97 and 0.90, respectively. These results confirmed the discriminative ability of the algorithm. In comparison with other studies, the proposed method improves trade-off between sensitivity and false prediction rate with linear features and low computational requirements and it can potentially be employed in implantable devices. Achieving high performance by linear features, PCA, KNN-based undersampling, and SVM demonstrates that this method can potentially be used in implantable devices.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Neuroscience Methods - Volume 232, 30 July 2014, Pages 134-142
نویسندگان
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