Identifying Patients with Poststroke Mild Cognitive Impairment by Pattern Recognition of Working Memory Load-Related ERP
المؤلفون المشاركون
Wei, Wenshi
Yan, Yuning
Li, Xiaoou
المصدر
Computational and Mathematical Methods in Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-10، 10ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-10-23
دولة النشر
مصر
عدد الصفحات
10
التخصصات الرئيسية
الملخص EN
The early detection of subjects with probable cognitive deficits is crucial for effective appliance of treatment strategies.
This paper explored a methodology used to discriminate between evoked related potential signals of stroke patients and their matched control subjects in a visual working memory paradigm.
The proposed algorithm, which combined independent component analysis and orthogonal empirical mode decomposition, was applied to extract independent sources.
Four types of target stimulus features including P300 peak latency, P300 peak amplitude, root mean square, and theta frequency band power were chosen.
Evolutionary multiple kernel support vector machine (EMK-SVM) based on genetic programming was investigated to classify stroke patients and healthy controls.
Based on 5-fold cross-validation runs, EMK-SVM provided better classification performance compared with other state-of-the-art algorithms.
Comparing stroke patients with healthy controls using the proposed algorithm, we achieved the maximum classification accuracies of 91.76% and 82.23% for 0-back and 1-back tasks, respectively.
Overall, the experimental results showed that the proposed method was effective.
The approach in this study may eventually lead to a reliable tool for identifying suitable brain impairment candidates and assessing cognitive function.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Li, Xiaoou& Yan, Yuning& Wei, Wenshi. 2013. Identifying Patients with Poststroke Mild Cognitive Impairment by Pattern Recognition of Working Memory Load-Related ERP. Computational and Mathematical Methods in Medicine،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-488905
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Li, Xiaoou…[et al.]. Identifying Patients with Poststroke Mild Cognitive Impairment by Pattern Recognition of Working Memory Load-Related ERP. Computational and Mathematical Methods in Medicine No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-488905
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Li, Xiaoou& Yan, Yuning& Wei, Wenshi. Identifying Patients with Poststroke Mild Cognitive Impairment by Pattern Recognition of Working Memory Load-Related ERP. Computational and Mathematical Methods in Medicine. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-488905
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-488905
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