EEG BASED COGNITIVE WORKLOAD CLASSIFICATION DURING NASA MATB-II MULTITASKING
| العنوان: | EEG BASED COGNITIVE WORKLOAD CLASSIFICATION DURING NASA MATB-II MULTITASKING |
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| المؤلفون: | Alok Mittal, Greeshma Sharma, Sushil Chandra, Kundan Lal Verma, Devendra Jha |
| المصدر: | International Journal of Cognitive Research in Science, Engineering and Education, Vol 3, Iss 1 (2015) International Journal of Cognitive Research in Science, Engineering and Education, Vol 3, Iss 1, Pp 35-41 (2015) |
| بيانات النشر: | Association for the Development of Science, Engineering and Education, 2015. |
| سنة النشر: | 2015 |
| مصطلحات موضوعية: | Computer science, Cognitive Neuroscience, EEG spectral feature, Neural Network, Experimental and Cognitive Psychology, Electroencephalography, Education, medicine, Human multitasking, EEG feature, L7-991, Neural network classification, Cognitive Workload, Artificial neural network, medicine.diagnostic_test, business.industry, Workload, Pattern recognition, Education (General), Engineering (General). Civil engineering (General), ComputingMethodologies_PATTERNRECOGNITION, Feature (computer vision), Discrete wavelet transform, Artificial intelligence, Cognitive workload, TA1-2040, business |
| الوصف: | The objective of this experiment was to determine the best possible input EEG feature for classification of the workload while designing load balancing logic for an automated operator. The input features compared in this study consisted of spectral features of Electroencephalography, objective scoring and subjective scoring. Method utilizes to identify best EEG feature as an input in Neural Network Classifiers for workload classification, to identify channels which could provide classification with the highest accuracy and for identification of EEG feature which could give discrimination among workload level without adding any classifiers. The result had shown Engagement Index is the best feature for neural network classification. |
| اللغة: | English |
| تدمد: | 2334-8496 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b68f64ddd1d3d5a86dba779d0f080bfc https://ijcrsee.com/index.php/ijcrsee/article/view/67 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....b68f64ddd1d3d5a86dba779d0f080bfc |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 23348496 |
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