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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Exploring cognitive load and emotional states for the visually impaired

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    15101041, 14301057, 14101123_CSE.pdf (1.104Mb)
    Date
    2019-04
    Publisher
    Brac University
    Author
    Afroz, Sharmin
    Shimanto, Zubaed Hassan
    Jahan, Ra qua Sifat
    Metadata
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    URI
    http://hdl.handle.net/10361/12352
    Abstract
    Cognitive load and emotional states may impact for designing an assistive navigation aid for the Visually Impaired Peoples (VIPs). In this study, electroencephalogram (EEG) signals were captured from participants with di erent degree sight loss peoples (DDSLPs). EEG signals were then used to measure various cognitive loads and emotions to test the usability of an intelligent navigation aids. To support the argument of testing the usability of a navigation aids, the complexity of the tasks in terms of cognitive load and emotions were quanti ed considering diverse factors by extracting features from various well established entropies when DDSLPs will navigate unfamiliar indoor environments with di erent obstacles. Experimental results show that classi cation accuracy for narrow space is 97.61% for cognitive load. Moreover, the experiment achieves that 90.40% and 50.60% classi cation accuracy for arousal and valence in the open space and stairs, respectively.
    Keywords
    Cognitive load; Emotional states; EEG; Human brain; Entropy; SVM
     
    LC Subject Headings
    Machine learning
     
    Description
    This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2019.
     
    Cataloged from PDF version of thesis.
     
    Includes bibliographical references (pages 34-39).
    Department
    Department of Computer Science and Engineering, Brac University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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