کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6891382 | 698080 | 2016 | 42 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new approach for automatic sleep scoring: Combining Taguchi based complex-valued neural network and complex wavelet transform
ترجمه فارسی عنوان
یک رویکرد جدید برای به ثمر رساندن خودکار خواب: ترکیبی از شبکه عصبی پیچیده ارزشمند مبتنی بر تاگوچی و تبدیل موجک پیچیده است
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
Automatic classification of sleep stages is one of the most important methods used for diagnostic procedures in psychiatry and neurology. This method, which has been developed by sleep specialists, is a time-consuming and difficult process. Generally, electroencephalogram (EEG) signals are used in sleep scoring. In this study, a new complex classifier-based approach is presented for automatic sleep scoring using EEG signals. In this context, complex-valued methods were utilized in the feature selection and classification stages. In the feature selection stage, features of EEG data were extracted with the help of a dual tree complex wavelet transform (DTCWT). In the next phase, five statistical features were obtained. These features are classified using complex-valued neural network (CVANN) algorithm. The Taguchi method was used in order to determine the effective parameter values in this CVANN. The aim was to develop a stable model involving parameter optimization. Different statistical parameters were utilized in the evaluation phase. Also, results were obtained in terms of two different sleep standards. In the study in which a 2nd level DTCWT and CVANN hybrid model was used, 93.84% accuracy rate was obtained according to the Rechtschaffen & Kales (R&K) standard, while a 95.42% accuracy rate was obtained according to the American Academy of Sleep Medicine (AASM) standard. Complex-valued classifiers were found to be promising in terms of the automatic sleep scoring and EEG data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods and Programs in Biomedicine - Volume 129, June 2016, Pages 203-216
Journal: Computer Methods and Programs in Biomedicine - Volume 129, June 2016, Pages 203-216
نویسندگان
Musa Peker,