Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks
المؤلفون المشاركون
Deng, Hai
Islam, Mohammad S.
Mamun, Khondaker A.
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-16، 16ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-10-19
دولة النشر
مصر
عدد الصفحات
16
التخصصات الرئيسية
الملخص EN
Decoding neural activities related to voluntary and involuntary movements is fundamental to understanding human brain motor circuits and neuromotor disorders and can lead to the development of neuromotor prosthetic devices for neurorehabilitation.
This study explores using recorded deep brain local field potentials (LFPs) for robust movement decoding of Parkinson’s disease (PD) and Dystonia patients.
The LFP data from voluntary movement activities such as left and right hand index finger clicking were recorded from patients who underwent surgeries for implantation of deep brain stimulation electrodes.
Movement-related LFP signal features were extracted by computing instantaneous power related to motor response in different neural frequency bands.
An innovative neural network ensemble classifier has been proposed and developed for accurate prediction of finger movement and its forthcoming laterality.
The ensemble classifier contains three base neural network classifiers, namely, feedforward, radial basis, and probabilistic neural networks.
The majority voting rule is used to fuse the decisions of the three base classifiers to generate the final decision of the ensemble classifier.
The overall decoding performance reaches a level of agreement (kappa value) at about 0.729±0.16 for decoding movement from the resting state and about 0.671±0.14 for decoding left and right visually cued movements.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Islam, Mohammad S.& Mamun, Khondaker A.& Deng, Hai. 2017. Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1140981
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Islam, Mohammad S.…[et al.]. Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-16.
https://search.emarefa.net/detail/BIM-1140981
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Islam, Mohammad S.& Mamun, Khondaker A.& Deng, Hai. Decoding of Human Movements Based on Deep Brain Local Field Potentials Using Ensemble Neural Networks. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-16.
https://search.emarefa.net/detail/BIM-1140981
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1140981
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