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Robust Multimodal Cognitive Load Measurement

  • Book
  • © 2016

Overview

Authors:
  1. Fang Chen

    1. (NICTA), National ICT Australia, Sydney, Australia

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  2. Jianlong Zhou

    1. (NICTA), National ICT Australia, Sydney, Australia

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  3. Yang Wang

    1. (NICTA), National ICT Australia, Sydney, Australia

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  4. Kun Yu

    1. (NICTA), National ICT Australia, Sydney, Australia

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  5. Syed Z. Arshad

    1. (NICTA), National ICT Australia, Sydney, Australia

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  6. Ahmad Khawaji

    1. (NICTA), National ICT Australia, Sydney, Australia

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  7. Dan Conway

    1. (NICTA), National ICT Australia, Sydney, Australia

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  • Explores multimodal cognitive load measurement using physiological and behavioral modalities
  • Introduces various computational methods for automatic and real-time cognitive load measurement
  • Provides models for dynamic workload adjustment and real-time cognitive load measurement via data streaming

Part of the book series: Human–Computer Interaction Series (HCIS)

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Table of contents (17 chapters)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Preliminaries

    1. Front Matter

      Pages 1-1
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    2. Introduction

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 3-12

    3. The State-of-The-Art

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 13-32

    4. Theoretical Aspects of Multimodal Cognitive Load Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 33-71

  3. Physiological Measurement

    1. Front Matter

      Pages 73-73
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    2. Eye-Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 75-85

    3. Galvanic Skin Response-Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 87-99

  4. Behavioural Measurement

    1. Front Matter

      Pages 101-101
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    2. Linguistic Feature-Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 103-114

    3. Speech Signal Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 115-131

    4. Pen Input Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 133-145

    5. Mouse Based Measures

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 147-157

  5. Multimodal Measures and Affecting Factors

    1. Front Matter

      Pages 159-159
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    2. Multimodal Measures and Data Fusion

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 161-171

    3. Emotion and Cognitive Load

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 173-183

    4. Stress and Cognitive Load

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 185-194

    5. Trust and Cognitive Load

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 195-214

  6. Making Cognitive Load Measurement Accessible

    1. Front Matter

      Pages 215-215
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    2. Dynamic Cognitive Load Adjustments in a Feedback Loop

      • Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji et al.
      Pages 217-227
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Keywords

About this book

This book explores robust multimodal cognitive load measurement with physiological and behavioural modalities, which involve the eye, Galvanic Skin Response, speech, language, pen input, mouse movement and multimodality fusions. Factors including stress, trust, and environmental factors such as illumination are discussed regarding their implications for cognitive load measurement. Furthermore, dynamic workload adjustment and real-time cognitive load measurement with data streaming are presented in order to make cognitive load measurement accessible by more widespread applications and users. Finally, application examples are reviewed demonstrating the feasibility of multimodal cognitive load measurement in practical applications.

This is the first book of its kind to systematically introduce various computational methods for automatic and real-time cognitive load measurement and by doing so moves the practical application of cognitive load measurement from the domain of the computerscientist and psychologist to more general end-users, ready for widespread implementation.

Robust Multimodal Cognitive Load Measurement is intended for researchers and practitioners involved with cognitive load studies and communities within the computer, cognitive, and social sciences. The book will especially benefit researchers in areas like behaviour analysis, social analytics, human-computer interaction (HCI), intelligent information processing, and decision support systems.

Reviews

“The content of this volume is a fair reference source for researchers and stakeholders interested in the investigation and application of the construct of cognitive load. … this is a good reference for those who are interested in the application of cognitive load and its measurement, with the aim of designing multimodal human-computer interactive systems better aligned with limited mental capacities of humans.” (Luca Longo, Computing Reviews, March, 2017)

Authors and Affiliations

  • (NICTA), National ICT Australia, Sydney, Australia

    Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji, Dan Conway

Bibliographic Information

  • Book Title: Robust Multimodal Cognitive Load Measurement

  • Authors: Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji, Dan Conway

  • Series Title: Human–Computer Interaction Series

  • DOI: https://doi.org/10.1007/978-3-319-31700-7

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing Switzerland 2016

  • Hardcover ISBN: 978-3-319-31698-7Published: 24 June 2016

  • Softcover ISBN: 978-3-319-81099-7Published: 31 May 2018

  • eBook ISBN: 978-3-319-31700-7Published: 14 June 2016

  • Series ISSN: 1571-5035

  • Series E-ISSN: 2524-4477

  • Edition Number: 1

  • Number of Pages: XIV, 254

  • Number of Illustrations: 66 b/w illustrations, 65 illustrations in colour

  • Topics: User Interfaces and Human Computer Interaction, Biological Psychology, Biometrics

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