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.
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.
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.
Accurate 3D digital foot model is extremely useful in shoe or orthotics design and other medical situations such as podiatric therapy. In view of the fact that most of the 3D data-acquisition devices on the market are either expensive though high accuracy (e.g., high-end laser scanner), or with poor maneuverability and efficiency (e.g., image-based stereography), or deficient portability (e.g., large-size scanning machine or types requiring support frame), we propose a new method for human foot scanning in this paper. Microsoft Kinect sensor was adopted as the key device in this approach and proved a smart and efficient scanner in 3D foot data acquisition according to a detailed comparison with other scanners in terms of scan time, cost, operability and portability. Accuracy check of the sphere and foot scanning results also demonstrates decent precision of the proposed scanning system.
It is difficult for electric wheelchair users who suffer from quadriplegia or have compromised motor skills to finely manipulate a joystick. In addition, they risk losing control of the wheelchair upon impacts with steps. In this paper, we describe a system we designed to assist users in finely controlling their speed, depending on the height of the step. The system incorporates a laser range finder to remotely detect the step. During testing, we evaluated the effects of exposing the user to whole-body vibrations in order to estimate the discomfort that arose from the step height and climbing speed. We also verified that this system reduced the impact caused by collisions with steps.
This paper presents leg shape analysis from data collected in the 2012 US Army Anthropometry Survey (ANSUR II) as a case of digital body modelling. We applied principal component analysis (PCA) on 3D leg surfaces (3D PCA) and on relevant anthropometric measurements (1D PCA) of 3,890 male subjects. We compared the first seven significant shape modes (accounting for 94% of shape variation) of 3D PCA with 1D PCA of six anthropometric measurements of the right leg. The analysis shows that each set of PCA results has its own power to describe the shape variation. To explore the relations between anthropometric measurements and 3D shape variation, we also applied a multiple linear regression (MLR) model to 3D PCA scores against anthropometric measurements. The MLR results show a strong correlation between certain measurements and shape modes. Further numerical analysis also revealed a linear relation between the PC weights of length and circumference modes, and the volume and area of leg surfaces.
This paper presents a landmark-based parametric 3D foot model which can be used as the basis for designing customised shoe lasts. 22 points on the surface of the foot are defined as anthropometric landmarks.11 NURBS curves are then generated based on these 22 landmarks to construct the 3D parametric foot surface model using Rhinoceros® and Grasshopper®. Nineteen test subjects participated in an experiment to verify the effectiveness of the proposed model. The mean absolute difference of the ball girth between the 19 models and their corresponding 3D scans was found as 3.53 mm. The mean directed Hausdorff distance between the foot outlines of the models and the 3D scans was identified as 1.40 mm. Regarding the 3D surface, the overall mean bidirectional mean directed Hausdorff distance between the models and the 3D scans of all 19 cases was calculated as 3.68 ± 0.31 mm. Compared to the findings of other researchers, it is concluded that the proposed parametric model can describe the 3D shape of the foot with a reasonable accuracy and it can be used as a basis for shoe last design.
Emotional responses to colour stimuli are referred to as colour emotions, and their psychological constructs relating to colour attributes have been discussed in past studies. However, colour preference, one type of colour emotions, has yet to be explained due to cultural and sex differences. In the current study, we investigated an implicit attitude towards multi-colour stimuli, which was regarded as a colour emotion judged by unconscious mental processes. To extract the implicit attitude and compare it with the explicit one, we conducted affect misattribution procedure, a method of measuring attitudes in social psychology. We obtained emotional responses different from ones measured using semantic differential method in a previous study. We analysed the characteristics of the multi-colour stimuli using scores in computed by the affect misattribution procedure. Results revealed that the explicit attitude towards multi-colour stimuli was affected by their chroma and hue values. The current study provided fundamental knowledge to clarify the psychological construct of colour preference.
The rapid movement towards the connected society requires faster and adaptive decision making to comply with the frequent and unexpected changes in the environment. Not only the theoretical thinking but also the emotional interaction is the key of decision-making process in the connected society. This paper proposes an idea of cyber-physical communication media through the active motion of computer display, which would further strengthen the connection between people in terms of emotional aspect of communication. Using the digital human model of mid-air head motion as well as that of mid-air hand gestures, implementation of the idea is presented in this paper. According to the experimental results, feasibility of cyber-physical motion is discussed for video communication system applications.
Recently, various researches have been conducted about remote collaborative learning. However, unlike face-to-face communication, remote communication is difficult to give nonverbal information such as facial expression and physical. Therefore, it may interfere with the transmission of intention and emotion. In this research, to support intention and emotion transmission in remote collaborative learning, we develop and assess a remote collaborative learning support system using avatar with facial expression on sharing note system. We create 13 types of avatar with facial expression with reference to Russell's emotional circle model. As a result of comparative experiments with and without avatar with facial expression, the drawing time has increased and the test score is higher when there are facial expressions. And since weak positive correlation is observed between the drawing time and the test score, it is presumed that the avatar with facial expression promotes explanatory activities by drawing and enhances the learning efficiency.
It is well known that non-verbal information is important for smoothing communication. On the other hand, it is also suggested that limiting transmitted non-verbal information leads to accurate comprehension. In this research, in order to investigate the influence of visual non-verbal information in presentations on audiences' comprehension, we prepared the four videos in which the presenter was represented differently: normal, shadow, stick figure, and voice-only. Experimental participants answered questionnaires and comprehension tests after watching each presentation video. Then we verified answers from two points of view: feeling of transmission and degree of transmission. The results showed that the normal video was more highly evaluated than the other three types of videos in terms of feeling of transmission. However, the shadow video resulted in a higher degree of transmission than the other three types of videos. Furthermore, we also performed post-experiment-questionnaires and tests one week later and verified the effects of visible non-verbal information on memorability and memory retention.
In the revolutionary era of advanced technologies, computers have benefited humankind in a favourable way by enabling automatic speech-conciliated communication. Even though various assistive tools are available, still visually impaired people are dependent for accessing computer using the traditional input devices, compared to sighted people. To transcend such limitations, the paper discusses an assistive desktop navigation system ESPY that provides the visually impaired individual with the ability to access desktop by mouse movements. By ESPY, user has plenary access of icons on their desktop. ESPY provides assistance to visually impaired people with a navigation proficiency, which allows them to use traditional input devices in a convenient way same as sighted users.
The recent increase in technological maturity has allowed humanoid robots to interact with humans in real-world applications. A simulator of humanoid robots with the characteristics of digital human models plays a significant role for humanoid motion planning in those complex environments. In this paper, a humanoid robotics simulation and control platform is proposed for the developed humanoid robot, NINO. The platform consists of a simulator, the visualisation tool, motion planning algorithms, and a motion control library. It can simulate realistic physical interactions between the robot and its environment during locomotion and keep consistent performance between the simulator and the actual humanoid robot. The simulator can control both the virtual and physical robots. The performance and applications of the simulator platform have been justified through the simulation results of several biped locomotion tasks.
This paper presents a three-dimensional (3D) anthropometry model generation (AMG) software framework based on the latest US Army Anthropometric Survey (ANSUR II) database. The software utilises principal component shapes derived from 3D body scans in the database and employs two complementary methods (feature analysis method and database method) to generate 3D surface models directly from anthropometric feature specifications. Virtual landmarks and 3D features identified on the surface models are the keys for success of the present approaches. It is demonstrated that the features calculated from these models are in good agreement with traditional tape or caliper measurements with a few exceptions due to measurement methodology or posture. Besides surface anthropometry, the software is able to construct a dynamic joint segment framework from any of the models and morph associated bones, muscles, interior organs, and clothing accordingly. This AMG software is a valuable tool for AMG in digital human/warfighter/patient modelling for various applications in biomechanics, human factors or ergonomics, physiology, and medicine.
The current demographic ageing in Europe is the result of a relevant economic, social, and medical development. Nevertheless, at the same time, it is also leading to a significant increase in the demand for long-term care (LTC) to seniors. One viable way to offer qualified cares at home, while at the same time containing costs, is to exploit digital technologies as enablers of a constant interaction between seniors and assisting personnel. In this paper, we propose a top-to-bottom solution to provide at home LTC to seniors: from requirements analysis, to design methodology for ambient intelligence (AmI), to a working prototypal architecture with implementation. The proposed system aims to integrate and leverage off-the-shelf technology with a particular focus on devices designed for videogame consoles. These devices, thanks to a user-friendly interface and a smooth learning curve can play a central role in minimising the interference in the senior's private life.
We study the viewpoint-independence of image features in the classification of identities using multiple-view full-body images. A reliable vision system should be robust in classifying objects from images captured on novel viewpoints. To obtain a robust classifier, 3D models are collected for rendering training and testing images from various viewpoints. These images are then used for extracting features and building classifiers. In this work, we compute multiple view human-body images from a 3D anthropometry human body database. For each subject, a majority of the views are randomly selected to be included in the training dataset and the remaining views are used for testing. More specifically, we use histogram of oriented gradient (HOG) feature-based support vector machine (SVM) as the baseline to be compared with deep auto-encoders network and deep convolutional neural networks (CNN). Through experiments, we conclude that the deep CNN performs the best (deep auto-encoders network as the runner-up) in computing viewpointindependent image features for identity classifications based on 2D full-body images.
This paper aims to provide a retrospective of the use of a digital human modelling tool (SAMMIE) that was perhaps the first usable tool and is still active today. Relationships between digital human modelling and inclusive design, engineering design and ergonomics practice are discussed using examples from design studies using SAMMIE and government-funded research. Important issues such as accuracy of representation and handling multivariate rather than univariate evaluations are discussed together with methods of use in terms of defining end product users and tasks. Consideration is given to the use of the digital human modelling approach by non-ergonomists particularly with respect to understanding of the impact of human variability, jurisdiction and communication issues.
There has been much in the way of excitement and celebration concerning all things 'digital', which has provided the opening 'context' of the 21st century. We now need to stop, take a break and think clearly about our newly emerging areas. This paper's aim is to provide a discussion of the need for a robust theoretical framework for an idea embraced by the digital society - that all things, i.e., artefacts, - are connected by a story or a memory to each other and to people, resulting in an all consuming 'internet of things'. The paper introduces a new project 'The Search for New Frameworks for Digital Research' based at the University of Winchester at Winchester, UK and offers definitions of the area and key terms followed by initial thoughts about how other disciplines choose theoretical frameworks.
The advances and availability of technologies for the acquisition, registration and analysis of the three-dimensional (3D) shape of human bodies (or body parts) are resulting in the formation of large databases of parameterised meshes from which digital human body models can be derived. Such models can be used for the data-driven reconstruction of parameterised human body shapes from partial information such as one-dimensional (1D) measurements or 2D images. In this paper, we propose a new method for the reconstruction of 3D bodies from images gathered with a smartphone or tablet. Moreover, the method is implemented into a prototype app and tested at different levels through three experimental studies including synthetic models, 1:10 scale figurines and real children. The results demonstrate the feasibility of acquiring reliable anthropometric information easily at home by non-experts. This method and implementation have great potential for their application to the personalisation, size recommendation and virtual try-on simulation of wearable products.
