Classification of Hand Grasp Kinetics and Types Using Movement-Related Cortical Potentials and EEG Rhythms
المؤلفون المشاركون
Kamavuako, Ernest Nlandu
Jochumsen, Mads
Niazi, Imran Khan
Dremstrup, Kim
Rovsing, Cecilie
Rovsing, Helene
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-08-29
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Detection of single-trial movement intentions from EEG is paramount for brain-computer interfacing in neurorehabilitation.
These movement intentions contain task-related information and if this is decoded, the neurorehabilitation could potentially be optimized.
The aim of this study was to classify single-trial movement intentions associated with two levels of force and speed and three different grasp types using EEG rhythms and components of the movement-related cortical potential (MRCP) as features.
The feature importance was used to estimate encoding of discriminative information.
Two data sets were used.
29 healthy subjects executed and imagined different hand movements, while EEG was recorded over the contralateral sensorimotor cortex.
The following features were extracted: delta, theta, mu/alpha, beta, and gamma rhythms, readiness potential, negative slope, and motor potential of the MRCP.
Sequential forward selection was performed, and classification was performed using linear discriminant analysis and support vector machines.
Limited classification accuracies were obtained from the EEG rhythms and MRCP-components: 0.48±0.05 (grasp types), 0.41±0.07 (kinetic profiles, motor execution), and 0.39±0.08 (kinetic profiles, motor imagination).
Delta activity contributed the most but all features provided discriminative information.
These findings suggest that information from the entire EEG spectrum is needed to discriminate between task-related parameters from single-trial movement intentions.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jochumsen, Mads& Rovsing, Cecilie& Rovsing, Helene& Niazi, Imran Khan& Dremstrup, Kim& Kamavuako, Ernest Nlandu. 2017. Classification of Hand Grasp Kinetics and Types Using Movement-Related Cortical Potentials and EEG Rhythms. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141100
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jochumsen, Mads…[et al.]. Classification of Hand Grasp Kinetics and Types Using Movement-Related Cortical Potentials and EEG Rhythms. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1141100
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jochumsen, Mads& Rovsing, Cecilie& Rovsing, Helene& Niazi, Imran Khan& Dremstrup, Kim& Kamavuako, Ernest Nlandu. Classification of Hand Grasp Kinetics and Types Using Movement-Related Cortical Potentials and EEG Rhythms. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1141100
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1141100
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