DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography
المؤلفون المشاركون
Wang, Yingdong
Wu, Qingfeng
Wang, Chen
Ruan, Qunsheng
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-08
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
In the past few decades, identification recognition based on electroencephalography (EEG) has received extensive attention to resolve the security problems of conventional biometric systems.
In the present study, a novel EEG-based identification system with different entropy and a continuous convolution neural network (CNN) classifier is proposed.
The performance of the proposed method is experimentally evaluated through the emotional EEG data.
The conducted experiment shows that the proposed method approaches the stunning accuracy (ACC) of 99.7% on average and can rapidly train and update the DE-CNN model.
Then, the effects of different emotions and the impact of different time intervals on the identification performance are investigated.
Obtained results show that different emotions affect the identification accuracy, where the negative and neutral mood EEG has a better robustness than positive emotions.
For a video signal as the EEG stimulant, it is found that the proposed method with 0–75 Hz is more robust than a single band, while the 15–32 Hz band presents overfitting and reduces the accuracy of the cross-emotion test.
It is concluded that time interval reduces the accuracy and the 15–32 Hz band has the best compatibility in terms of the attenuation.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Yingdong& Wu, Qingfeng& Wang, Chen& Ruan, Qunsheng. 2020. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Yingdong…[et al.]. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Yingdong& Wu, Qingfeng& Wang, Chen& Ruan, Qunsheng. DE-CNN: An Improved Identity Recognition Algorithm Based on the Emotional Electroencephalography. Computational and Mathematical Methods in Medicine. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1139573
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1139573
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر