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Catalog Publications

Year 2022
  • Stress Detection of Children With ASD Using Physiological Signals
    Publication
    • S. N. B. Aktas
    • P. Uluer
    • B. Coskun
    • E. Toprak
    • D. E. Barkana
    • H. Kose
    • T. Zorcec
    • B. Robins
    • A. Landowska

    - Year 2022

    This paper proposes a physiological signal-based stress detection approach for children with autism spectrum disorder (ASD) to be used in social and assistive robot inter- vention. Electrodermal activity (EDA) and blood volume pulse (BVP) signals are collected with an E4 smart wristband from children with ASD in different countries. The peak count and signal amplitude features are derived from EDA signal and used in order to detect...

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  • Stress Detection of Children with Autism using Physiological Signals in Kaspar Robot-Based Intervention Studies
    Publication
    • B. Coskun
    • P. Uluer
    • E. Toprak
    • D. E. Barkana
    • H. Kose
    • T. Zorcec
    • B. Robins
    • A. Landowska

    - Year 2022

    This study aims to develop a stress detection system using the blood volume pulse (BVP) signals of children with Autism Spectrum Disorder (ASD) during robot-based interven- tion. This study presents the heart rate variability (HRV) analysis method to detect the stress, where HRV features are extracted from raw BVP signals recorded from an E4 wristband during interaction studies with the social robot Kaspar. Low frequency power...

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  • Systematic Literature Review for Emotion Recognition from EEG Signals

    Researchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...

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  • Systematic Literature Review for Emotion Recognition from EEG Signals

    Researchers have recently become increasingly interested in recognizing emotions from electroencephalogram (EEG) signals and many studies utilizing different approaches have been conducted in this field. For the purposes of this work, we performed a systematic literature review including over 40 articles in order to identify the best set of methods for the emotion recognition problem. Our work collects information about the most...

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  • Toward a unified model of mobile Business Intelligence (m-BI) acceptance and use
    Publication

    - Year 2022

    Factors affecting mobile business intelligence (m-BI) acceptance and use have become an increasingly important topic in practice due to the growing complexity of organizations, and their underlying information systems (IS). Since, one can notice considerable interest in m-BI, however, to the best of our knowledge few studies (if any) aim to synthesize the existing body of knowledge with regards to the factors affecting m-BI acceptance...

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Year 2021