کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6010391 | 1185876 | 2015 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Seizure detection approach using S-transform and singular value decomposition
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
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چکیده انگلیسی
Automatic seizure detection plays a significant role in the diagnosis of epilepsy. This paper presents a novel method based on S-transform and singular value decomposition (SVD) for seizure detection. Primarily, S-transform is performed on EEG signals, and the obtained time-frequency matrix is divided into submatrices. Then, the singular values of each submatrix are extracted using singular value decomposition (SVD). Effective features are constructed by adding the largest singular values in the same frequency band together and fed into Bayesian linear discriminant analysis (BLDA) classifier for decision. Finally, postprocessing is applied to obtain higher sensitivity and lower false detection rate. A total of 183.07Â hours of intracranial EEG recordings containing 82 seizure events from 20 patients were used to evaluate the system. The proposed method had a sensitivity of 96.40% and a specificity of 99.01%, with a false detection rate of 0.16/h.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Epilepsy & Behavior - Volume 52, Part A, November 2015, Pages 187-193
Journal: Epilepsy & Behavior - Volume 52, Part A, November 2015, Pages 187-193
نویسندگان
Yudan Xia, Weidong Zhou, Chengcheng Li, Qi Yuan, Shujuan Geng,