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Cognitive and Physiological Assessments in Human-Computer Interaction
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Cognitive and Physiological Assessments in Human-Computer Interaction

A special issue of Big Data and Cognitive Computing (ISSN 2504-2289).

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 15373

Special Issue Editors

Prof. Dr. Valentin Schwind

E-Mail Website
Guest Editor
Frankfurt University of Applied Sciences, Frankfurt, Germany
Interests: human–computer interaction; virtual reality; augmented reality; social acceptance; collaboration
Dr. Thomas Kosch

E-Mail Website
Guest Editor
Telecooperation Lab, Technical University of Darmstadt, 64289 Darmstadt, Germany
Interests: physiological user interface design; physiological interaction; human augmentation; mixed reality

Special Issue Information

Dear Colleagues,

Cognitive and physiological measures have made astonishing progress in the evaluation, assessment, and creation of novel interaction scenarios for user interfaces. Research in human–computer interaction (HCI) applies these concepts throughout various disciplines, including ubiquitous computing, gesture- and speech-based interaction, mixed reality, medicine and healthcare, Industry 4.0, Internet of Things (IoT), games, entertainment, and many more. These developments show an immense need to integrate human senses and behavior into computational decisions and processes. We see great opportunities in the current development of artificial intelligence (AI) and envision devices capable of not only tracking users but also interacting with them in a foreseeing and predictive manner.

This development includes research into the redesign, appropriate modeling, and guidelines for cognitive as well as physiological sensing. On one hand, predictions provide the opportunity to adapt systems to the characteristics of users, improving the way in which they interact with them; on the other hand, perceptual integration from cognitive sciences must be reconsidered in the design of automated systems where users and systems can adapt to each other. This has a significant impact on automation, digitalization, and how users interact with their devices in their daily lives.

This Special Issue provides a forum for colleagues and scholars to report the most up-to-date research results in the HCI field, as well as comprehensive surveys of the state of the art in relevant specific areas of cognitive and physiological assessments. Both original contributions with theoretical novelty and practical solutions for addressing particular problems of cognitive and physiological assessments in HCI are solicited. The Special Issue welcomes original, unpublished research contributions including, but not limited to, methodological, quantitative, qualitative, or mixed-methods studies focusing on issues around usability and user interaction with new technologies.

Prof. Dr. Valentin Schwind
Dr. Thomas Kosch
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Intelligent and context-aware user interfaces in HCI
  • HCI in smart and AI-based systems
  • Physiological sensing and perceptual integration
  • Eye tracking
  • Brain sensing
  • Brain–computer interfaces
  • Ubiquitous computing and implicit interaction
  • Mobile and wearable devices
  • Accessibility in HCI
  • Learning and education in HCI
  • User experience and usability evaluation
  • Cognitive and physical user augmentation
  • Visual and haptic displays
  • Interfaces/Perception/Presence in VR/AR/MX Medicine, healthcare, and wellbeing with HCI
  • Human behavior sensing
  • Gesture interfaces
  • Privacy, security, social, and ethical aspects
  • Games and entertainment in HCI
  • Smart products and IoT

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Published Papers (3 papers)

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Research

19 pages, 980 KiB  
Article
Social Acceptability in Context: Stereotypical Perception of Shape, Body Location, and Usage of Wearable Devices
by Jessica Sehrt, Bent Braams, Niels Henze and Valentin Schwind
Big Data Cogn. Comput. 2022, 6(4), 100; https://doi.org/10.3390/bdcc6040100 - 23 Sep 2022
Cited by 7 | Viewed by 3232
Abstract
Assessing social acceptability is vital when designing body-worn mobile devices. Previous research found evidence that using stereotyping content model (SCM) mobile devices can systematically predict ratings of the warmth and competence of their wearers. However, it is currently unknown if other contextual dimensions [...] Read more.
Assessing social acceptability is vital when designing body-worn mobile devices. Previous research found evidence that using stereotyping content model (SCM) mobile devices can systematically predict ratings of the warmth and competence of their wearers. However, it is currently unknown if other contextual dimensions of mobile device usage can also systematically affect those ratings. In two studies, we investigate if and how shape and body location of a body-worn mobile device as well as the activity in which the device is being used can systematically influence stereotypical ratings. Our results suggest that this is evident in some but not all cases. We conclude that people further differentiate between the placement of the device, particularly devices in the user’s hand, and during an activity in which the device can contextually be misused. This indicates that users further differentiate the context and that more contexual information is helpful while operationalizing the SCM as a measure for social acceptability. Full article
(This article belongs to the Special Issue Cognitive and Physiological Assessments in Human-Computer Interaction)
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21 pages, 3407 KiB  
Article
A Novel Method of Exploring the Uncanny Valley in Avatar Gender(Sex) and Realism Using Electromyography
by Jacqueline D. Bailey and Karen L. Blackmore
Big Data Cogn. Comput. 2022, 6(2), 61; https://doi.org/10.3390/bdcc6020061 - 30 May 2022
Cited by 2 | Viewed by 5435
Abstract
Despite the variety of applications that use avatars (virtual humans), how end-users perceive avatars are not fully understood, and accurately measuring these perceptions remains a challenge. To measure end-user responses more accurately to avatars, this pilot study uses a novel methodology which aims [...] Read more.
Despite the variety of applications that use avatars (virtual humans), how end-users perceive avatars are not fully understood, and accurately measuring these perceptions remains a challenge. To measure end-user responses more accurately to avatars, this pilot study uses a novel methodology which aims to examine and categorize end-user facial electromyography (f-EMG) responses. These responses (n = 92) can be categorized as pleasant, unpleasant, and neutral using control images sourced from the International Affective Picture System (IAPS). This methodology can also account for variability between participant responses to avatars. The novel methodology taken here can assist in the comparisons of avatars, such as gender(sex)-based differences. To examine these gender(sex) differences, participant responses to an avatar can be categorized as either pleasant, unpleasant, neutral or a combination. Although other factors such as age may unconsciously affect the participant responses, age was not directly considered in this work. This method may allow avatar developers to better understand how end-users objectively perceive an avatar. The recommendation of this methodology is to aim for an avatar that returns a pleasant, neutral, or pleasant-neutral response, unless an unpleasant response is the intended. This methodology demonstrates a novel and useful way forward to address some of the known variability issues found in f-EMG responses, and responses to avatar realism and uncanniness that can be used to examine gender(sex) perceptions. Full article
(This article belongs to the Special Issue Cognitive and Physiological Assessments in Human-Computer Interaction)
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19 pages, 2274 KiB  
Article
Virtual Reality Adaptation Using Electrodermal Activity to Support the User Experience
by Francesco Chiossi, Robin Welsch, Steeven Villa, Lewis Chuang and Sven Mayer
Big Data Cogn. Comput. 2022, 6(2), 55; https://doi.org/10.3390/bdcc6020055 - 13 May 2022
Cited by 24 | Viewed by 5302
Abstract
Virtual reality is increasingly used for tasks such as work and education. Thus, rendering scenarios that do not interfere with such goals and deplete user experience are becoming progressively more relevant. We present a physiologically adaptive system that optimizes the virtual environment based [...] Read more.
Virtual reality is increasingly used for tasks such as work and education. Thus, rendering scenarios that do not interfere with such goals and deplete user experience are becoming progressively more relevant. We present a physiologically adaptive system that optimizes the virtual environment based on physiological arousal, i.e., electrodermal activity. We investigated the usability of the adaptive system in a simulated social virtual reality scenario. Participants completed an n-back task (primary) and a visual detection (secondary) task. Here, we adapted the visual complexity of the secondary task in the form of the number of non-player characters of the secondary task to accomplish the primary task. We show that an adaptive virtual reality can improve users’ comfort by adapting to physiological arousal regarding the task complexity. Our findings suggest that physiologically adaptive virtual reality systems can improve users’ experience in a wide range of scenarios. Full article
(This article belongs to the Special Issue Cognitive and Physiological Assessments in Human-Computer Interaction)
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