Most recent issue published online in the International Journal of the Digital Human.
International Journal of the Digital Human
http://www.inderscience.com/browse/index.php?journalID=379&year=2023&vol=2&issue=3
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International Journal of the Digital Human
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© 2023 Inderscience Enterprises Ltd.
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International Journal of the Digital Human
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http://www.inderscience.com/browse/index.php?journalID=379&year=2023&vol=2&issue=3
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Modelling affective aspects of human-artefact interaction based on Kansei engineering: application to the hairdryer domain
http://www.inderscience.com/link.php?id=133034
Recently in ergonomics and human factors community, there have been calls for incorporating affective aspects, such as pleasure and aesthetics, for product development. This study presents a systematic approach to modelling Kansei, which is users' subjective feeling and impression, by combining variable precision rough sets (VPRS) and association rule mining. The design element reducts corresponding to each Kansei attribute are firstly extracted using β-partition quality-based attribute reduction algorithm. Subsequently, the Apriori algorithm was adopted to induce middle-order association rules. The empirical results involving appearance design of hairdryer domain demonstrate the usefulness of the adoption of VPRS. The induced rules can serve the purpose of working memory and inference engine of a virtual Kansei engineering system, which provides a potential research line for modelling affective aspects of human-artefact interaction in the community of digital human modelling.
Modelling affective aspects of human-artefact interaction based on Kansei engineering: application to the hairdryer domain
Mingcai Hu; Fu Guo; Zenggen Ren; Hao Shao; Vincent G. Duffy
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 143 - 159
Recently in ergonomics and human factors community, there have been calls for incorporating affective aspects, such as pleasure and aesthetics, for product development. This study presents a systematic approach to modelling Kansei, which is users' subjective feeling and impression, by combining variable precision rough sets (VPRS) and association rule mining. The design element reducts corresponding to each Kansei attribute are firstly extracted using β-partition quality-based attribute reduction algorithm. Subsequently, the Apriori algorithm was adopted to induce middle-order association rules. The empirical results involving appearance design of hairdryer domain demonstrate the usefulness of the adoption of VPRS. The induced rules can serve the purpose of working memory and inference engine of a virtual Kansei engineering system, which provides a potential research line for modelling affective aspects of human-artefact interaction in the community of digital human modelling.]]>
10.1504/IJDH.2023.133034
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 143 - 159
Mingcai Hu
Fu Guo
Zenggen Ren
Hao Shao
Vincent G. Duffy
Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110169, China ' School of Industrial Engineering, College of Engineering, Purdue University, Grissom Hall, 315 N. Grant Street, West Lafayette, Indiana 47907-2023, USA
affective aspects
Kansei modelling
human-artefact interaction
Kansei engineering
affective design
variable precision rough sets
VPRS
2023-08-25T23:20:50-05:00
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Verification of manikin motions in human-industrial robot collaborative simulations
http://www.inderscience.com/link.php?id=133025
A recently developed simulation software, IPS-HIRC, combines digital humans and industrial robots into one environment in order to design human-industrial robot collaborative (HIRC) workstations. The aim of this study is to verify the manikin motions predicted by the mathematical algorithm in the software with results obtained from motions performed by humans in experiments. These motions are measured through motion capture data on humans performing a HIRC work task in laboratory workstations. These stations represent HIRC workstations considered in an international heavy vehicle manufacturing company. The results showcase significant correlations in the motions in one of the two use cases, but fewer correlations when comparing the total operation time. The main reason for this is the complexity of the two cases and the lack of professional assembly experience among the test participants. Thus, new verification studies are needed in use cases that more properly represent human motions in a manufacturing workstation.
Verification of manikin motions in human-industrial robot collaborative simulations
Fredrik Ore; Pamela Ruiz Castro; Lars Hanson; Magnus Wiktorsson; Stefan Gustafsson
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 160 - 178
A recently developed simulation software, IPS-HIRC, combines digital humans and industrial robots into one environment in order to design human-industrial robot collaborative (HIRC) workstations. The aim of this study is to verify the manikin motions predicted by the mathematical algorithm in the software with results obtained from motions performed by humans in experiments. These motions are measured through motion capture data on humans performing a HIRC work task in laboratory workstations. These stations represent HIRC workstations considered in an international heavy vehicle manufacturing company. The results showcase significant correlations in the motions in one of the two use cases, but fewer correlations when comparing the total operation time. The main reason for this is the complexity of the two cases and the lack of professional assembly experience among the test participants. Thus, new verification studies are needed in use cases that more properly represent human motions in a manufacturing workstation.]]>
10.1504/IJDH.2023.133025
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 160 - 178
Fredrik Ore
Pamela Ruiz Castro
Lars Hanson
Magnus Wiktorsson
Stefan Gustafsson
School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden; Scania CV AB, Global Industrial Development, Södertälje, Sweden ' School of Engineering Science, University of Skövde, Skövde, Sweden ' School of Engineering Science, University of Skövde, Skövde, Sweden; Department of Industrial and Materials Science, Chalmers University of Technology, Gothenburg, Sweden ' School of Innovation, Design and Engineering, Mälardalen University, Eskilstuna, Sweden; KTH, School of Industrial Engineering and Management, Södertälje, Sweden ' Industrial Path Solutions Sweden AB, Chalmers Teknikpark, 412 88 Göteborg
human-robot collaboration
HRC
simulation
verification
validation
digital human modelling
DHM
industrial robot
motion capture
workstation
2023-08-25T23:20:50-05:00
Copyright © 2023 Fredrik Ore et al
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Bibliometric analysis of user experience research during 1995-2018
http://www.inderscience.com/link.php?id=133033
User experience (UX) has become an effective method to improve the design of different products, technologies, and services, and researchers have made enormous contributions, in theory, context, measurement, and application. While no systematic and clustered review has been conducted for the entire field of user experience, this study aims to collect, count, and cluster studies related to user experience and provide a whole view of research on user experience by using the method of bibliometrics. The review illustrated the development of user experience area, identify the leading authors and papers. Further, it clustered the field into eight research areas based on network analysis. The results would provide a roadmap for further research in the field of user experience.
Bibliometric analysis of user experience research during 1995-2018
Fu Guo; Mingming Li; Xueshuang Wang; Vincent G. Duffy
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 179 - 196
User experience (UX) has become an effective method to improve the design of different products, technologies, and services, and researchers have made enormous contributions, in theory, context, measurement, and application. While no systematic and clustered review has been conducted for the entire field of user experience, this study aims to collect, count, and cluster studies related to user experience and provide a whole view of research on user experience by using the method of bibliometrics. The review illustrated the development of user experience area, identify the leading authors and papers. Further, it clustered the field into eight research areas based on network analysis. The results would provide a roadmap for further research in the field of user experience.]]>
10.1504/IJDH.2023.133033
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 179 - 196
Fu Guo
Mingming Li
Xueshuang Wang
Vincent G. Duffy
Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang, 110167, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang, 110167, China ' Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang, 110167, China ' School of Industrial Engineering, Purdue University, West Lafayette, IN 47906, USA
user experience
review
bibliometrics
network analysis
2023-08-25T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
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196
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Digital human model simulation of the movement variability induced by muscle fatigue during a repetitive pointing task until exhaustion
http://www.inderscience.com/link.php?id=133027
Movement variability is a fundamental feature of human movement. It occurs in all kinds of activity including workplace tasks. Despite its prevalence, workstation designers are hardly aware of it. Neglecting this variability may lead designers to ignore parts of the future operator's activity, thus leading to an incomplete assessment of their occupational risks. This article describes a model-based virtual human and its controller, intended to simulate the movement variability induced by muscle fatigue during a repetitive activity until exhaustion. It associates a multi-body dynamics framework and a three-compartment muscle fatigue model. When simulating a repetitive pointing task, our DHM reproduces some aspects of human movement variability. Improvements are still needed to account for intra- and inter-individual movement variability patterns recently highlighted in the literature. Yet, this approach raises interesting perspectives regarding new DHM features providing workstation designers with more comprehensive ergonomic assessments from the early stages of workstation design.
Digital human model simulation of the movement variability induced by muscle fatigue during a repetitive pointing task until exhaustion
Jonathan Savin; Clarisse Gaudez; Martine A. Gilles; Vincent Padois; Philippe Bidaud
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 197 - 222
Movement variability is a fundamental feature of human movement. It occurs in all kinds of activity including workplace tasks. Despite its prevalence, workstation designers are hardly aware of it. Neglecting this variability may lead designers to ignore parts of the future operator's activity, thus leading to an incomplete assessment of their occupational risks. This article describes a model-based virtual human and its controller, intended to simulate the movement variability induced by muscle fatigue during a repetitive activity until exhaustion. It associates a multi-body dynamics framework and a three-compartment muscle fatigue model. When simulating a repetitive pointing task, our DHM reproduces some aspects of human movement variability. Improvements are still needed to account for intra- and inter-individual movement variability patterns recently highlighted in the literature. Yet, this approach raises interesting perspectives regarding new DHM features providing workstation designers with more comprehensive ergonomic assessments from the early stages of workstation design.]]>
10.1504/IJDH.2023.133027
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 197 - 222
Jonathan Savin
Clarisse Gaudez
Martine A. Gilles
Vincent Padois
Philippe Bidaud
Work Equipment Engineering Division †INRS, VandÅuvre-lès-Nancy, France ' Working Life Division †INRS, VandÅuvre-lès-Nancy, France ' Working Life Division †INRS, VandÅuvre-lès-Nancy, France ' AUCTUS †Inria, Talence, France ' ONERA, Palaiseau, France
movement variability
muscle fatigue
digital human model
DHM
simulation
repetitive pointing activity
ergonomics assessment
workstation design
2023-08-25T23:20:50-05:00
Copyright © 2023 Inderscience Enterprises Ltd.
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222
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VirSen1.0: toward sensor configuration recommendation in an interactive optical sensor simulator for human gesture recognition
http://www.inderscience.com/link.php?id=133032
Research is underway on the use of sensor simulation in generating sensor data to design a real-world human gesture recognition system. The overall development process suffers from poor interactive performance, because developers lack an efficient tool to support the sensor configuration, result checking, and trial-and-error that arise when designing a machine learning system. Hence, we have developed <i>VirSen</i>1.0, a virtual environment with a user interface to support the process of designing a sensor-based human gesture recognition system. In this environment, a simulator produces lightness data and combines it with an avatar's motion to train a classifier. Then, the interface visualises the importance of the features used for the model, via the permutation feature importance, and it provides feedback on the effect of each sensor to the classifier. This paper proposes a complete development process, from acquisition of learning data to creation of a learning model, using a single software tool. Additionally, a user study confirmed that by visualising the importance of the features used in the model, users can create learning models that achieve a certain level of accuracy.
VirSen1.0: toward sensor configuration recommendation in an interactive optical sensor simulator for human gesture recognition
Kana Matsuo; Chengshuo Xia; Yuta Sugiura
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 223 - 241
Research is underway on the use of sensor simulation in generating sensor data to design a real-world human gesture recognition system. The overall development process suffers from poor interactive performance, because developers lack an efficient tool to support the sensor configuration, result checking, and trial-and-error that arise when designing a machine learning system. Hence, we have developed <i>VirSen</i>1.0, a virtual environment with a user interface to support the process of designing a sensor-based human gesture recognition system. In this environment, a simulator produces lightness data and combines it with an avatar's motion to train a classifier. Then, the interface visualises the importance of the features used for the model, via the permutation feature importance, and it provides feedback on the effect of each sensor to the classifier. This paper proposes a complete development process, from acquisition of learning data to creation of a learning model, using a single software tool. Additionally, a user study confirmed that by visualising the importance of the features used in the model, users can create learning models that achieve a certain level of accuracy.]]>
10.1504/IJDH.2023.133032
International Journal of the Digital Human, Vol. 2, No. 3 (2023) pp. 223 - 241
Kana Matsuo
Chengshuo Xia
Yuta Sugiura
Department of Information and Computer Science, Faculty of Science and Technology, Keio University 3-14-1, Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan ' Department of Information and Computer Science, Faculty of Science and Technology, Keio University 3-14-1, Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan ' Department of Information and Computer Science, Faculty of Science and Technology, Keio University 3-14-1, Hiyoshi, Kohoku-ku, Yokohama, 223-8522, Japan
sensor simulator
interactive system
optical sensor
machine learning
graphical user interface
2023-08-25T23:20:50-05:00
Copyright © 2023 Kana Matsuo et al
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