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Robust multimodal cognitive load mea...
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Chen, Fang.
Robust multimodal cognitive load measurement[electronic resource] /
紀錄類型:
書目-電子資源 : Monograph/item
杜威分類號:
004.019
書名/作者:
Robust multimodal cognitive load measurement/ by Fang Chen ... [et al.].
其他作者:
Chen, Fang.
出版者:
Cham : : Springer International Publishing :, 2016.
面頁冊數:
xiv, 254 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:
Springer eBooks
標題:
User-centered system design.
標題:
Human-computer interaction.
標題:
Multimodal user interfaces (Computer systems)
標題:
Computer Science.
標題:
User Interfaces and Human Computer Interaction.
標題:
Biological Psychology.
標題:
Biometrics.
ISBN:
9783319317007
ISBN:
9783319316987
內容註:
Preface -- Part I: Preliminaries -- Introduction -- The State-of-The-Art -- Theoretical Aspects of Multimodal Cognitive Load Measures -- Part II: Physiological Measurement -- Eye Based Measures. Galvanic Skin Response Based Measures -- Part III: Behavioural Measurement -- Linguistic Feature Based Measures -- Speech Signal Based Measures -- Pen Input Based Measures -- Mouse Based Measures -- Part IV: Multimodal Measures and Affecting Factors -- Multimodal Measures and Data Fusion -- Emotion and Cognitive Load -- Stress and Cognitive Load -- Trust and Cognitive Load -- Part V: Making Cognitive Load Measurement Accessible -- Dynamic Cognitive Load Adjustments in A Feedback Loop -- Real-Time Cognitive Load Measurement: Data Streaming Approach -- Applications of Cognitive Load Measurement -- Part VI: Conclusions -- Cognitive Load Measurement in Perspectives.
摘要、提要註:
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 computer scientist 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.
電子資源:
http://dx.doi.org/10.1007/978-3-319-31700-7
Robust multimodal cognitive load measurement[electronic resource] /
Robust multimodal cognitive load measurement
[electronic resource] /by Fang Chen ... [et al.]. - Cham :Springer International Publishing :2016. - xiv, 254 p. :ill. (some col.), digital ;24 cm. - Human-computer interaction series,1571-5035. - Human-computer interaction series..
Preface -- Part I: Preliminaries -- Introduction -- The State-of-The-Art -- Theoretical Aspects of Multimodal Cognitive Load Measures -- Part II: Physiological Measurement -- Eye Based Measures. Galvanic Skin Response Based Measures -- Part III: Behavioural Measurement -- Linguistic Feature Based Measures -- Speech Signal Based Measures -- Pen Input Based Measures -- Mouse Based Measures -- Part IV: Multimodal Measures and Affecting Factors -- Multimodal Measures and Data Fusion -- Emotion and Cognitive Load -- Stress and Cognitive Load -- Trust and Cognitive Load -- Part V: Making Cognitive Load Measurement Accessible -- Dynamic Cognitive Load Adjustments in A Feedback Loop -- Real-Time Cognitive Load Measurement: Data Streaming Approach -- Applications of Cognitive Load Measurement -- Part VI: Conclusions -- Cognitive Load Measurement in Perspectives.
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 computer scientist 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.
ISBN: 9783319317007
Standard No.: 10.1007/978-3-319-31700-7doiSubjects--Topical Terms:
340091
User-centered system design.
LC Class. No.: QA76.9.H85
Dewey Class. No.: 004.019
Robust multimodal cognitive load measurement[electronic resource] /
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Preface -- Part I: Preliminaries -- Introduction -- The State-of-The-Art -- Theoretical Aspects of Multimodal Cognitive Load Measures -- Part II: Physiological Measurement -- Eye Based Measures. Galvanic Skin Response Based Measures -- Part III: Behavioural Measurement -- Linguistic Feature Based Measures -- Speech Signal Based Measures -- Pen Input Based Measures -- Mouse Based Measures -- Part IV: Multimodal Measures and Affecting Factors -- Multimodal Measures and Data Fusion -- Emotion and Cognitive Load -- Stress and Cognitive Load -- Trust and Cognitive Load -- Part V: Making Cognitive Load Measurement Accessible -- Dynamic Cognitive Load Adjustments in A Feedback Loop -- Real-Time Cognitive Load Measurement: Data Streaming Approach -- Applications of Cognitive Load Measurement -- Part VI: Conclusions -- Cognitive Load Measurement in Perspectives.
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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 computer scientist 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.
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