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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (15 October 2023) | Viewed by 10174

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Special Issue Editors

Prof. Dr. Mark Billinghurst

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Guest Editor

Empathic Computing Laboratory, University of South Australia, Adelaide 5095, Australia
Interests: augmented reality; empathic computing; virtual reality; interaction design; gesture based interfaces; multimodal interfaces
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Kiyoshi Kiyokawa

E-Mail Website
Guest Editor

Cybernetics and Reality Engineering (CARE) Laboratory, Nara Institute of Science and Technology, Ikoma, Japan
Interests: augmented reality; mixed reality; virtual reality; human augmentation; 3D user interfaces
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Welcome to the Special Issue for Human–Computer Interaction in Emerging Technologies. There are many ways in which Human–Computer Interaction (HCl) is evolving, each with its own characteristics. In addition to the usual mouse and keyboard input, voice, body gestures, and eye gaze are becoming increasingly prevalent. Research has also been conducted on HCI using facial expressions, heart rate variability, brain activity, and other implicit cues. As for output techniques, not just traditional audiovisual displays, but also haptic, olfactory, and gustatory displays have been investigated in depth. Virtual Reality (VR) and Augmented Reality (AR) can be considered an example of HCI that fully exploits human input and output. In addition, HCI via robots which can replicate the actions of the hands, arms, face, upper body, and legs, is gradually developing. For example, using these technologies, it is becoming possible, to control a robotic prosthetic hand through thought alone.

For this Special Issue, we urge authors to contribute original research articles, works in progress, surveys, reviews, and opinion pieces on HCI research based on robots, virtual reality, and a variety of sensing techniques. Topics of interest include, (but are not limited to):

Robot-based Human–Computer Interaction
Virtual Reality-based Human–Computer Interaction
Augmented Reality-based Human–Computer Interaction
Sensor-based Human–Computer Interaction
Human–Robot Interaction
Multimodal Interaction
IoT for Human–Computer Interaction
Human Augmentation
Assistive Technologies
Affective Computing
Empathic Computing
Hardware for Human–Computer Interaction
Interaction Metaphors
User Experience
Human Factors

Prof. Dr. Mark Billinghurst
Prof. Dr. Kiyoshi Kiyokawa
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

Published Papers (6 papers)

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Research

20 pages, 3469 KiB

Open AccessArticle

Designing a Tangible User Interface (TUI) for the Elderly Based on Their Motivations and Game Elements

by Johnny Alexander Salazar-Cardona, Sandra Cano, Francisco Luis Gutiérrez-Vela and Jeferson Arango

Sensors 2023, 23(23), 9513; https://doi.org/10.3390/s23239513 - 30 Nov 2023

Viewed by 1134

Abstract

The elderly population has grown significantly in recent years, requiring strategies focused on promoting active aging to improve health and well-being. It may be achieved in many ways, including using technology for this population. We propose an interactive system for older adults based on a tangible user interface. A group of 10 experts conducted a heuristic evaluation of a system of this type utilizing a questionnaire and obtaining satisfactory results. This study evaluated the older adult population’s fun and pervasive game experience. The results will provide a basis for continuing to build this interactive system to promote active aging in older adults, either at the cognitive or physical level, depending on the applied approach. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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25 pages, 4346 KiB

Open AccessArticle

A Neurophysiological Evaluation of Cognitive Load during Augmented Reality Interactions in Various Industrial Maintenance and Assembly Tasks

by Faisal M. Alessa, Mohammed H. Alhaag, Ibrahim M. Al-harkan, Mohamed Z. Ramadan and Fahad M. Alqahtani

Sensors 2023, 23(18), 7698; https://doi.org/10.3390/s23187698 - 6 Sep 2023

Cited by 2 | Viewed by 1229

Abstract

Augmented reality (AR) has been shown to improve productivity in industry, but its adverse effects (e.g., headaches, eye strain, nausea, and mental workload) on users warrant further investigation. The objective of this study is to investigate the effects of different instruction methods (i.e., HoloLens AR-based and paper-based instructions) and task complexity (low and high-demanding tasks) on cognitive workloads and performance. Twenty-eight healthy males with a mean age of 32.12 (SD 2.45) years were recruited in this study and were randomly divided into two groups. The first group performed the experiment using AR-based instruction, and the second group used paper-based instruction. Performance was measured using total task time (TTT). The cognitive workload was measured using the power of electroencephalograph (EEG) features and the NASA task load index (NASA TLX). The results showed that using AR instructions resulted in a reduction in maintenance times and an increase in mental workload compared to paper instructions, particularly for the more demanding tasks. With AR instruction, 0.45% and 14.94% less time was spent on low- and high-demand tasks, respectively, as compared to paper instructions. According to the EEG features, employing AR to guide employees during highly demanding maintenance tasks increased information processing, which could be linked with an increased germane cognitive load. Increased germane cognitive load means participants can better facilitate long-term knowledge and skill acquisition. These results suggested that AR is superior and recommended for highly demanding maintenance tasks since it speeds up maintenance times and increases the possibility that information is stored in long-term memory and encrypted for recalls. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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16 pages, 1205 KiB

Open AccessArticle

The Effects of Social Presence and Familiarity on Children–Robot Interactions

by Yi-Chen Chen, Su-Ling Yeh, Weijane Lin, Hsiu-Ping Yueh and Li-Chen Fu

Sensors 2023, 23(9), 4231; https://doi.org/10.3390/s23094231 - 24 Apr 2023

Cited by 2 | Viewed by 2034

Abstract

In children–robot interactions, an impression of a robot’s “social presence” (i.e., an interactive agent that feels like a person) links positively to an improved relationship with the robot. However, building relationships takes many exposures, and there is an intellectual gap in how social presence and familiarity collaborate in modulating children–robot relationships. We investigated whether social presence altered over time, how repeated exposure and social presence affected rapport, and how social presence would modulate children’s attitudes toward the robot. Fourteen children (four female, age = 10.79 ± 1.12) interacted with a companion robot for four days in spontaneous interactions. The findings revealed that children who perceived the robot as having a higher social presence developed a stronger rapport than those who perceived a lower social presence. However, repeated encounters did not change the children’s perceptions of the robot’s social presence. Children rated higher rapport after repeated interactions regardless of social presence levels. This suggests that while a higher social presence initially elevated the positive relationship between children and the robot, it was the repeated interactions that continued solidifying the rapport. Additionally, children who perceived a higher social presence from the robot felt less relational uneasiness about their relationship with robots. These findings highlight the importance of robots’ social presence and familiarity in promoting positive relationships in children–robot interaction. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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18 pages, 5078 KiB

Open AccessArticle

Effects of AR-Based Home Appliance Agents on User’s Perception and Maintenance Behavior

by Takeru Baba, Naoya Isoyama, Hideaki Uchiyama, Nobuchika Sakata and Kiyoshi Kiyokawa

Sensors 2023, 23(8), 4135; https://doi.org/10.3390/s23084135 - 20 Apr 2023

Viewed by 1595

Abstract

Maintenance of home appliances can be tedious. Maintenance work can be physically demanding and it is not always easy to know the cause of a malfunctioning appliance. Many users need to motivate themselves to perform maintenance work and consider it ideal for home appliances to be maintenance-free. On the other hand, pets and other living creatures can be taken care of with joy and without much pain, even if they are difficult to take care of. To alleviate the hassle associated with the maintenance of home appliances, we propose an augmented reality (AR) system to superimpose an agent over the home appliance of concern who changes their behavior according to the internal state of the appliance. Taking a refrigerator as an example, we verify whether such AR agent visualization motivates users to perform maintenance work and reduces the associated discomfort. We designed a cartoon-like agent and implemented a prototype system using a HoloLens 2, which can switch between several animations depending on the internal state of the refrigerator. Using the prototype system, a Wizard of Oz user study comparing three conditions was conducted. We compared the proposed method (Animacy condition), an additional behavior method (Intelligence condition), and a text-based method as a baseline for presenting the refrigerator state. In the Intelligence condition, the agent looked at the participants from time to time as if it was aware of them and exhibited help-seeking behavior only when it was considered that they could take a short break. The results show that both the Animacy and Intelligence conditions induced animacy perception and a sense of intimacy. It was also evident that the agent visualization made the participants feel more pleasant. On the other hand, the sense of discomfort was not reduced by the agent visualization and the Intelligence condition did not improve the perceived intelligence or the sense of coercion further compared to the Animacy condition. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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21 pages, 5162 KiB

Open AccessArticle

Experimental Evaluation of EMKEY: An Assistive Technology for People with Upper Limb Disabilities

by Mireya Zapata, Kevin Valencia-Aragón and Carlos Ramos-Galarza

Sensors 2023, 23(8), 4049; https://doi.org/10.3390/s23084049 - 17 Apr 2023

Cited by 1 | Viewed by 1471

Abstract

Assistive technology can help people with disabilities to use computers more effectively and can enable them to access the same information and resources as people without disabilities. To obtain more insight into the factors that can bring about the design of an Emulator of Mouse and Keyboard (EMKEY) to higher levels of user satisfaction, an experimental study was conducted in order to analyse its effectiveness and efficiency. The experimental study involved 27 participants (M_age = 20.81, SD = 1.14) who performed three experimental games under different conditions (using the mouse and using EMKEY with head movements and voice commands). According to the results, the use of EMKEY allowed for the successful performance of tasks such as matching stimuli (F_(2,78) = 2.39, p = 0.10, η² = 0.06). However, the execution times of a task were found to be higher when using the emulator to drag an object on the screen (t_(52,1) = −18.45, p ≤ 0.001, d = 9.60). These results indicate the effectiveness of technological development for people with upper limb disabilities; however, there is room for improvement in terms of efficiency. The findings are discussed in relation to previous research and are based on future studies aimed at improving the operation of the EMKEY emulator. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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29 pages, 6393 KiB

Open AccessArticle

Multiagent-Based Data Presentation Mechanism for Multifaceted Analysis in Network Management Tasks

by Kazuto Sasai, Ryota Fukutani, Gen Kitagata and Tetsuo Kinoshita

Sensors 2022, 22(22), 8841; https://doi.org/10.3390/s22228841 - 15 Nov 2022

Viewed by 1369

Abstract

Although network management tasks are highly automated using big data and artificial intelligence technologies, when an unforeseen cybersecurity problem or fault scenario occurs, administrators sometimes directly analyze system data to make a heuristic decision. However, a wide variety of information is required to address complex cybersecurity risks, whereas current systems are focused on narrowing the candidates of information. In this study, we propose a multiagent-based data presentation mechanism (MADPM) that consists of agents operating data-processing tools that store and analyze network data. Agents in MADPM interact with other agents to form data-processing sequences. In this process, we design not only the composition of the sequence according to requirements, but also a mechanism to expand it to enable multifaceted analysis that supports heuristic reasoning. We tested five case studies in the prototype system implemented in an experimental network. The results indicated that the multifaceted presentation of data can support administrators more than the selected single-faceted optimal presentation. The final outcome of our proposed approach is the provision of a multifaceted and cross-system data presentation for heuristic inference in network management tasks. Full article

(This article belongs to the Special Issue Human Computer Interaction in Emerging Technologies)

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