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Symbiotic Interaction

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Cover of 'Symbiotic Interaction'

Table of Contents

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    Book Overview
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    Chapter 1 Towards a Definition of Symbiotic Relations Between Humans and Machines
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    Chapter 2 Adapting the System to Users Based on Implicit Data: Ethical Risks and Possible Solutions
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    Chapter 3 Total Immersion: Designing for Affective Symbiosis in a Virtual Reality Game with Haptics, Biosensors, and Emotive Agents
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    Chapter 4 Analysis of the Human-Computer Interaction on the Example of Image-Based CAPTCHA by Association Rule Mining
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    Chapter 5 The “NeuroDante Project”: Neurometric Measurements of Participant’s Reaction to Literary Auditory Stimuli from Dante’s “Divina Commedia”
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    Chapter 6 A Biosymtic (Biosymbiotic Robotic) Approach to Human Development and Evolution
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    Chapter 7 Interactive Content-Based Image Retrieval with Deep Neural Networks
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    Chapter 8 Finding Kairos: The Influence of Context-Based Timing on Compliance with Well-Being Triggers
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    Chapter 9 Maritime Cognitive Workload Assessment
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    Chapter 10 How Human-Mouse Interaction can Accurately Detect Faked Responses About Identity
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    Chapter 11 Prediction of Difficulty Levels in Video Games from Ongoing EEG
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    Chapter 12 Investigating Tactile Stimulation in Symbiotic Systems
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    Chapter 13 Towards Interactional Symbiosis: Epistemic Balance and Co-presence in a Quantified Self Experiment
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    Chapter 14 Digital Me: Controlling and Making Sense of My Digital Footprint
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    Chapter 15 A User-Friendly Dictionary-Supported SSVEP-based BCI Application
Attention for Chapter 11: Prediction of Difficulty Levels in Video Games from Ongoing EEG
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Chapter title
Prediction of Difficulty Levels in Video Games from Ongoing EEG
Chapter number 11
Book title
Symbiotic Interaction
Published by
Springer, Cham, September 2016
DOI 10.1007/978-3-319-57753-1_11
Book ISBNs
978-3-31-957752-4, 978-3-31-957753-1
Authors

Laura Naumann, Matthias Schultze-Kraft, Sven Dähne, Benjamin Blankertz

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 29%
Student > Ph. D. Student 5 29%
Student > Master 3 18%
Professor 1 6%
Student > Bachelor 1 6%
Other 1 6%
Unknown 1 6%
Readers by discipline Count As %
Computer Science 7 41%
Neuroscience 4 24%
Engineering 4 24%
Psychology 1 6%
Unknown 1 6%