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Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience
المؤلفون المشاركون
Shieh, Jiann-Shing
Jiang, George J. A.
Huang, Hui-Hsun
Lan, Jheng-Yan
Tsai, Feng-Fang
Chang, Hung-Chi
Yang, Yea-Wen
Chuang, Fu-Lan
Chiu, Yi-Fang
Jen, Kuo-Kuang
Wu, Jeng-Fu
Abbod, Maysam F.
Fan, Shou-Zen
المصدر
العدد
المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-02-08
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Electroencephalogram (EEG) signals, as it can express the human brain’s activities and reflect awareness, have been widely used in many research and medical equipment to build a noninvasive monitoring index to the depth of anesthesia (DOA).
Bispectral (BIS) index monitor is one of the famous and important indicators for anesthesiologists primarily using EEG signals when assessing the DOA.
In this study, an attempt is made to build a new indicator using EEG signals to provide a more valuable reference to the DOA for clinical researchers.
The EEG signals are collected from patients under anesthetic surgery which are filtered using multivariate empirical mode decomposition (MEMD) method and analyzed using sample entropy (SampEn) analysis.
The calculated signals from SampEn are utilized to train an artificial neural network (ANN) model through using expert assessment of consciousness level (EACL) which is assessed by experienced anesthesiologists as the target to train, validate, and test the ANN.
The results that are achieved using the proposed system are compared to BIS index.
The proposed system results show that it is not only having similar characteristic to BIS index but also more close to experienced anesthesiologists which illustrates the consciousness level and reflects the DOA successfully.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, George J. A.& Fan, Shou-Zen& Abbod, Maysam F.& Huang, Hui-Hsun& Lan, Jheng-Yan& Tsai, Feng-Fang…[et al.]. 2015. Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience. BioMed Research International،Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1055122
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, George J. A.…[et al.]. Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience. BioMed Research International No. 2015 (2015), pp.1-8.
https://search.emarefa.net/detail/BIM-1055122
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, George J. A.& Fan, Shou-Zen& Abbod, Maysam F.& Huang, Hui-Hsun& Lan, Jheng-Yan& Tsai, Feng-Fang…[et al.]. Sample Entropy Analysis of EEG Signals via Artificial Neural Networks to Model Patients’ Consciousness Level Based on Anesthesiologists Experience. BioMed Research International. 2015. Vol. 2015, no. 2015, pp.1-8.
https://search.emarefa.net/detail/BIM-1055122
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1055122
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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