Abstract: The evolving landscape of educational technologies has ushered Virtual Reality (VR) in the forefront of higher education. As the COVID-19 pandemic propelled a rapid shift toward e-learning, the demand for high-quality distance education has surged, prompting an exploration of VR as a viable solution. While existing research indicates that VR supports student engagement and learning experiences compared with traditional teaching methods, the lack of shared pedagogical frameworks and systematic analyses of its applications leaves a deeper investigation of VR's potentials and limitations in enhancing learning outcomes still unexplored. This paper presents a systematic literature review aimed at filling this gap by considering studies that evaluate VR-based teaching methods in comparison with traditional ones in higher education contexts in order to assess the strengths and weaknesses of this technology in improving students' learning outcomes and achieve inclusive education. The analysis focuses on a set of dimensions including the adopted research design, participants' characteristics, disciplinary field of application, VR technological features (i.e., immersivity, interactivity, operability, commercial availability, and presence of VR training), adopted teaching methodologies, assessed VR impact on learning outcomes and presence of studies involving students with disabilities or Specific Learning Disorders (SpLDs). Based on inclusion/exclusion criteria, a total of 71 studies of VR in higher education were analysed. Most of analysed studies employed quantitative methods (67%), while no qualitative studies were found. More than half of the studies were conducted with undergraduate students (61%). Most of the studies involved VR in STEM disciplines, with almost half of them concerning Health Sciences (45%). VR solutions were most frequently immersive (63%), predominantly using Oculus Rift and HTC Vive HMDs, interactive (59%), single-user (92%) and non-commercial (57%). Only a small portion of studies included a VR training in the research protocol (8%). Most of the studies compared lecture-based methodologies as control condition with active methodologies in the VR condition. Learning outcomes were positively influenced by immersivity, interactivity and active methodologies, although at different degrees. No study involved students with disabilities or SpLDs in the experimentation.

Keywords: Augmented and virtual reality | Human-computer interface | Media in education | Post-secondary education | Teaching/learning strategies

Abstract: The study presents a new method based on generative design and multi-criteria analysis to select the best design option accounting for engineering performance, economic feasibility and other design goals (e.g. novelty, compliance). A comparison between topology optimization and generative design is proposed and discussed.

Keywords: Engineering Design | Generative Design | Mechanical Design | Topology Optimization | TOPSIS Algorithm

Abstract: Writing is first-order instrumental learning that develops throughout the life cycle, a complex process evolving from early childhood education. The identification of risk predictors of dysgraphia at age 5 has the potential to significantly reduce the impact of graphomotor difficulties in early primary school, which affects handwriting performance to such an extent that it can become illegible. Building on established scientific literature, this study focuses on screening processes, with particular attention to writing requirements. This paper proposes a novel prevention and intervention system based on new technologies for teachers and educators or therapists. Specifically, it presents a pilot study testing an innovative tactile device to analyze graphomotor performance and motor coordination in real time. The research explores whether this haptic device can be used as an effective pedagogical aid for preventing graphomotor issues in children aged 5 to 6 years. The results showed a high level of engagement and usability among young participants.

Keywords: decision support system | dysgraphia | dysgraphia early identification | dysgraphia risk predictors | graphomotor skills | handwriting | haptic training | specific learning disorders

Abstract: This study contributes to understanding semi-automated ergonomic risk assessments in industrial manufacturing environments, proposing a practical tool for enhancing worker safety and operational efficiency. In the Industry 5.0 era, the human-centric approach in manufacturing is crucial, especially considering the aging workforce and the dynamic nature of the entire modern industrial sector, today integrating digital technology, automation, and sustainable practices to enhance productivity and environmental responsibility. This approach aims to adapt work conditions to individual capabilities, addressing the high incidence of work-related musculoskeletal disorders (MSDs). The traditional, subjective methods of ergonomic assessment are inadequate for dynamic settings, highlighting the need for affordable, automatic tools for continuous monitoring of workers’ postures to evaluate ergonomic risks effectively during tasks. To enable this perspective, 2D RGB Motion Capture (MoCap) systems based on computer vision currently seem the technologies of choice, given their low intrusiveness, cost, and implementation effort. However, the reliability and applicability of these systems in the dynamic and varied manufacturing environment remain uncertain. This research benchmarks various literature proposed MoCap tools and examines the viability of MoCap systems for ergonomic risk assessments in Industry 5.0 by exploiting one of the benchmarked semi-automated, low-cost and non-intrusive 2D RGB MoCap system, capable of continuously monitoring and analysing workers’ postures. By conducting experiments across varied manufacturing environments, this research evaluates the system’s effectiveness in assessing ergonomic risks and its adaptability to different production lines. Results reveal that the accuracy of risk assessments varies by specific environmental conditions and workstation setups. Although these systems are not yet optimized for expert-level risk certification, they offer significant potential for enhancing workplace safety and efficiency by providing continuous posture monitoring.

Keywords: Computer vision | Deep learning | Ergonomic monitoring | Ergonomic Risk Assessment | Motion capture | Work-related MSDs

Abstract: This chapter explores the challenging topic of emotion recognition by affective computing. The importance of considering and understanding people’s emotions in interaction design is discussed, focusing on the role of human emotions in the entire life cycle of human–system interaction as a means to innovate products and services. The measurement of emotions is also analyzed, including the classification of human emotions and recognition methods, as well as current techniques for measuring emotional responses. An emotional-based approach and related technologies are considered in managing the entire life cycle of human–system interaction as an innovation driver. This chapter also presents how to use affective computing in cross-transversal applications, concentrating on potential applications and different case studies.

Abstract: With the expansion of the Internet and mobile services, digital exclusion due to accessibility barriers remains a concern, particularly in understanding complex web content. This study investigates the application of Large Language Models (LLMs) like OpenAI’s ChatGPT for simplifying sentences in line with easy-to-read (E2R) guidelines. Through two exploratory studies, we assess LLMs’ awareness of E2R guidelines and their capability to simplify sentences to enhance cognitive accessibility in an archaeological museum context. The first one aims to assess LLMs’ general knowledge about E2R guidelines. The second one evaluates their ability to perform SS conforming to E2R guidelines in order to generate accessible textual information for an archaeological museum. To this end, results of SS provided by LLMs are compared with text made by students who attended training on the E2R guidelines and those made through a co-design process with people with cognitive disabilities.

Keywords: Cognitive accessibility | Easy to Read | Large Language Models | Sentence Simplification

Abstract: The paper proposes a novel unified classification of digital games, i.e., video games and serious games, due to the recent interest of academia and industry for their use to achieve several educational purposes. The paper reviews existing cataloging systems and proposes a five-definition based matrix cataloging including a set of key digital game metadata, unifying existing knowledge and highlighting commonalities between cataloging systems. It offers a higher-level categorization of digital games that retain distinctions where necessary, thus unifying both categories of digital games.

Keywords: Cataloging | Concept Design | Serious games | Videogame

Abstract: No abstract available

Abstract: This paper aims to explore the potential offered by emotion recognition systems to provide a feasible response to the growing need for audience understanding and development in the field of arts organizations. Through an empirical study, it was investigated whether the emotional valence measured on the audience through an emotion recognition system based on facial expression analysis can be used with an experience audit to: (1) support the understanding of the emotional responses of customers toward any clue that characterizes a staged performance; and (2) systematically investigate the customer’s overall experience in terms of their overall satisfaction. The study was carried out in the context of opera live shows in the open-air neoclassical theater Arena Sferisterio in Macerata, during 11 opera performances. A total of 132 spectators were involved. Both the emotional valence provided by the considered emotion recognition system and the quantitative data related to customers’ satisfaction, collected through a survey, were considered.

Keywords: artificial intelligence | customer experience | customer satisfaction | emotion recognition | facial expression recognition

Abstract: The use of eXtended Reality (XR) technologies, including augmented reality (AR), virtual reality (VR), and mixed reality (MR), has become increasingly popular in museums to enhance the visitor experience. However, the impact of XR technologies on Learning Performance in the context of archeological museums needs to be better understood. This study aims to investigate the relationships between Usability, Presence and Learning Performance by developing XR experiences showcasing archeological artefacts and conducting user testing to evaluate their effectiveness. A laboratory test is conducted to compare a VR application with a mobile AR one, presenting the digital models of five archeological findings. Descriptive statistics are used to compare the two case studies, providing valuable insights into the impact of XR technologies on the visitor experience from a learning perspective. The study confirms that Usability has a more significant effect on learning than Presence and can help designers and museum managers better understand the factors contributing to a successful XR experience.

Keywords: Cultural heritage | Technological Benchmarking | XR Technologies

Abstract: Virtual museum systems have been shown to play a key role in enhancing visitor’s experience and increasing the accessibility of cultural artifacts. In this context, the use of haptic interfaces based on force feedback could increase the level of immersivity of these systems and the quality of the interaction between visitors and cultural artifacts, introducing tactile information that could enrich the experience of all people, also in the case of visitors with disability. However, HD present limits concerning the ease of use of the device. This paper provides the results of an exploratory research carried out within the Research center of Teaching and learning, Disability and Educational Technology of the University of Macerata (TIncTec), consisting in two studies. Study 1 aims to analyze the learning performance of people with and without disabilities concerning this device. Study 2 aims to assess whether HD can provide useful support for conceptualizing the shape of virtual objects. To this end, we considered the 6 DoF high fidelity force feedback Geomagic Touch X by 3D system. A total of 30 people has been involved, including both children and adults with and without disabilities. The considered VR applications were developed in Unity 3D, using the 3D Systems Openhaptics Unity Plugin.

Keywords: Accessibility | Cultural Heritage | Force Feedback | Haptic Interfaces | Inclusive Museum | Special Education | Virtual Museum | XR Technologies

Abstract: Nowadays, web designers are forced to have an even deeper perception of how users approach their products in terms of user experience and usability. Remote Usability Testing (RUT) is the most appropriate tool to assess the usability of web platforms by measuring the level of user attention, satisfaction, and productivity. RUT does not require the physical presence of users and evaluators, but for this very reason makes data collection more difficult. To simplify data collection and analysis and help RUT moderators collect and analyze user’s data in a non-intrusive manner, this research work proposes a low-cost comprehensive framework based on Deep Learning algorithms. The proposed framework, called Miora, employs facial expression recognition, gaze recognition, and analytics algorithms to capture data about other information of interest for in-depth usability analysis, such as interactions with the analyzed software. It uses a comprehensive evaluation methodology to elicit information about usability metrics and presents the results in a series of graphs and statistics so that the moderator can intuitively analyze the different trends related to the KPI used as usability indicators. To demonstrate how the proposed framework could facilitate the collection of large amounts of data and enable moderators to conduct both remote formative and summative tests in a more efficient way than traditional lab-based usability testing, two case studies have been presented: the analysis of an online shop and of a management platform.

Keywords: affective computing | deep learning | gaze detection | remote usability testing | usability | usability assessment

Abstract: This paper introduces a web-platform system that performs semi-automatic compute of several risk indexes, based on the considered evaluation method (e.g., RULA—Rapid Upper Limb Assessment, REBA—Rapid Entire Body Assessment, OCRA—OCcupational Repetitive Action) to support ergonomics risk estimation, and provides augmented analytics to proactively improve ergonomic risk monitoring based on the characteristics of workers (e.g., age, gender), working tasks, and environment. It implements a body detection system, marker-less and low cost, based on the use of RGB cameras, which exploits the open-source deep learning model CMU (Carnegie Mellon University), from the tf-pose-estimation project, assuring worker privacy and data protection, which has been already successfully assessed in standard laboratory conditions. The paper provides a full description of the proposed platform and reports the results of validation in a real industrial case study regarding a washing machine assembly line composed by 5 workstations. A total of 15 workers have been involved.

Keywords: Ergonomics risk assessment | Extended reality | Human-centered manufacturing | Machine learning | Motion capture

Abstract: This study introduces a new operational tool based on the AEIOU observational framework to support the design of adaptive human machine interfaces (HMIs) that aim to modify people’s behavior and support people’s choices, to improve safety using emotional regulation techniques, through the management of environmental characteristics (e.g., temperature and illumination), according to an approach based on the nudging concept within a design thinking process. The proposed approach focuses on research in the field of behavioral psychology that has studied the correlations between human emotions and driving behavior, pushing towards the elicitation of those emotions judged to be most suitable for safe driving. The main objective is to support the ideation of scenarios and/or design features for adaptive HMIs to implement a nudging strategy to increase driving safety.

Keywords: adaptive HMI | affective computing | automotive | driving safety | emotion regulation | nudge

Abstract: Immersive virtual environments represent a great opportunity for museums to enhance visitor experience through edutainment. However, to provide an enjoyable entertainment and learning experience for all visitors, including people with disabilities, the virtual museum must not only be accessible, but also inclusive: they must provide greater equality and cultural and learning opportunities for all social groups. To achieve this goal, the concept of Universal Design needs to evolve into a user-centered approach where people are involved in co-designing the virtual museum experience. In this context, the article describes a pilot study conducted at the University of Macerata, which explores the possibility of using high-fidelity prototyping in a virtual laboratory to support the co-creation of an immersive virtual museum environment with relevant target users, including children and people with disability, from the earliest design stages.

Keywords: Immersive Virtual Reality | Inclusive education | Inclusive Museum | Virtual Museum

Abstract: This paper describes a pilot study conducted at the University of Macerata, within the project Inclusion 3.0. It aims to explore the possibility of using high-fidelity prototyping in a virtual laboratory to support the co-creation of an immersive virtual learning environment with people with disability and Specific Learning Disorders (SLDs), from the earliest design stages.

Keywords: disability | Inclusion | project | SLD | specific learning disorders | virtual

Abstract: This study aims at comparing three assembly training applications based on different XR technologies characterized by different degrees of immersion (i.e., an MR application based on Hololens 2, a desktop AR application and a digital handbook visualized on a monitor). A total of 54 subjects, recruited among students and personnel of Università Politecnica delle Marche, have been involved. They were assigned to 3 groups age and gender matching. Each group is asked to complete the training related to the assembly of a Lego commercial set (i.e., LEGO 10593), using one of the three considered applications.

Keywords: Assembly training | Augmented Reality | Immersion | Manufacturing | Recall Performance

Abstract: This paper introduces a system that enable the collection of relevant data related to the emotional behavior and attention of both student and professor during exams. It exploits facial coding techniques to enable the collection of a large amount of data from the automatic analysis of students and professors faces using video analysis, advanced techniques for gaze tracking based on deep Learning, and technologies and the principles related to the Affective Computing branch derived from the research of Paul Ekman. It provides tools that facilitates the interpretation of the collected data by means of a dashboard. A preliminary experiment has been carried out to investigate whether such a system may help in assessing the evaluation setting and support reflection on the evaluation processes in the light of the different situations, so as to improve the adoption of inclusive approaches.

Keywords: Affective computing | Deep learning | E-leaning | Emotion recognition | Gaze tracking

Abstract: This article introduces at a conceptual level a system based on AI technologies, able to determine the customer profile, in order to support customer experience design and management accordingly to a customer-centered approach, by extracting information from video stream provided by the security cameras installed in a store. The system collects customer demographic and behavioral information (e.g., age, gender, time spent in determined areas of the store, time spent interacting with the salesperson, etc.) through Deep Learning algorithms, in a completely anonymous way, without saving bio-metric data. To predict the customer profile based on the collected data it exploits a Bayesian Belief Network (BBN).

Keywords: Customer experience | Customer profiling | Machine learning | Predictive models | Video analysis

Abstract: This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergonomic assessment are evaluated by a proper experiment, designed and per-formed to: (1) compare the data provided by it with those collected from a motion capture golden standard system; (2) compare the RULA scores obtained with data provided by it with those obtained with data provided by the Vicon Nexus system and those estimated through video analysis, by a team of three expert ergonomists. Tests have been conducted in standardized laboratory conditions and involved a total of six subjects.

Keywords: Ergonomic risk assessment | Industrial ergonomics | Motion capture | Postural analysis | RULA

Abstract: This article reports the results of a research aimed to evaluate the ability of a haptic interface to improve the user experience (UX) with virtual museum systems. In particular, two user studies have been carried out to (1) compare the experience aroused during the manipulation of a 3D printed replica of an artifact with a pen-like stylus with that aroused during the interaction (visual and tactile) with a 3D rendering application using a haptic interface and PC monitor, and (2) compare the users' perceived usability and UX among a traditional mouse-based desktop interface, haptic interface, and haptic gamified interface based on the SUS scale and the AttrakDiff2 questionnaire. A total of 65 people were involved. The considered haptic application is based on the haptic device Omega 6 produced by Force Dimension, and it is a permanent attraction of the Museo Archeologico Nazionale delle Marche.

Keywords: haptic interface | user experience | Virtual museum | virtual reality

Abstract: This paper describes the final assessment of a student with SLD who uses compensatory tools to verify the effectiveness of the strategies adopted to support the construction of an inclusive assessment environment. The proposed case study is part of long-term research conducted by the University of Macerata. New technologies for analyzing emotional feedback based on the analysis of facial expressions collected from both students and professors during the exam supported the observation.

Keywords: Emotional feedback | Evaluation strategies | Inclusive university teaching | University students Dyslexia

Abstract: Driver behaviour recognition is of paramount importance for in-car automation assistance. It is widely recognized that not only attentional states, but also emotional ones have an impact on the safety of the driving behaviour. This research work proposes an emotion-aware in-car architecture where it is possible to adapt driver’s emotions to the vehicle dynamics, investigating the correlations between negative emotional states and driving performances, and suggesting a system to regulate the driver’s engagement through a unique user experience (e.g. using music, LED lighting) in the car cabin. The relationship between altered emotional states induced through auditory stimuli and vehicle dynamics is investigated in a driving simulator.

Keywords: Driver monitoring system | Emotion recognition | Facial expression recognition

Abstract: In the last years, museums have begun to apply new technological solutions to manage their exhibits in a more open, inclusive, and creative way, to improve the visitors' experience to respond to the need to expand the audience. The main goal is to face the increasing competition in an economy referred to as the “Experience Economy”. To this end, Augmented Reality technology seems to represent a good solution for museum guide systems, to improve visitors' learning and enjoyment. In this context, the present paper proposes a museum guide system based on Spatial Augmented Reality powered by dynamic projection. The paper describes the overall HW and SW system architecture and reports in detail the developed process adopted to design and implement a museum guide and entertainment application, in the context of the “Studiolo of Federico da Montefeltro” in the Ducal Palace of Urbino. A preliminary survey has been carried out, which involved a total of 79 subjects, aimed at investigating the quality of visitor's experience, aroused by the proposed application, in terms of the “Four Experience Realms” defined by Pine & Gilmore (1998).

Keywords: Cultural heritage | Dynamic projection | Experience economy | Museum guide | Spatial augmented reality

Abstract: This paper introduces a new recommendation system for museums able to profile the visitors and propose them the most suitable exhibition path accordingly, to improve visitors’ satisfaction. It consists of an interactive touch screen totem, which implements a USB camera and exploits Convolutional Neural Network to perform facial coding to measure visitors’ emotions and estimate their age and gender. Based on the detected level of emotional valence, the system associates visitors with a profile and suggests them to visit a selection of five works of art, following a specific itinerary. An extensive experimentation lasting 2 months has been carried out at the Modern Art Museum “Palazzo Buonaccorsi” of Macerata. Results evidence that the proposed system can create an interactive and emotional link with the visitors, influencing their mood in the Pre-Experience phase and in the subsequent Post-Experience phase.

Keywords: Affective computing | Cultural heritage | Emotion recognition | Facial expression recognition

Abstract: This paper introduces an e-learning platform for the management of courses based on MOOCs, able to continuously monitoring student’s behavior through facial coding techniques, with a low computational effort client-side, and to provide useful insight for the instructor. The system exploits the most recent developments in Deep Learning and Computer Vision for Affective Computing, in compliance with the European GDPR. Taking as input the video capture by the webcam of the device used to attend the course, it: (1) performs continuous student’s authentication based on face recognition, (2) monitors the student’s level of attention through head orientation tracking and gaze detection analysis, (3) estimates student’s emotion during the course attendance.

Keywords: Affective Computing | Deep Learning | E-leaning | Facial Coding | Facial Recognition

Abstract: Virtual museum systems, based on different X-reality technologies, has begun to spread, as they represent decisive tools to promote exhibitions and reaching out to audiences. Although budgetary considerations have so far limited the choice of technologies a wide range of possible technological options are available today at low cost. This paper provides the results of an empirical study, with the aim to determine the most appropriate technologies to satisfy the visitors’ expectation and maximise their likelihood to repeat and recommend the experience. The study focuses on the comparison of the performance of five VM systems for visualise digital reproduction of archaeological finds, based on different technologies (i.e., PC desktop, holographic display, 3D stereoscopic projection, head mounted display and mobile Augmented Reality).

Keywords: Augmented reality | Mixed reality | Presence | Virtual Museum | Virtual reality | Visitor experience | X-Reality technologies

Abstract: Predictive Maintenance (PdM) is a prominent strategy comprising all the operational techniques and actions required to ensure machine availability and to prevent a machine-down failure. One of the main challenges of PdM is to design and develop an embedded smart system to monitor and predict the health status of the machine. In this work, we use a data-driven approach based on machine learning applied to woodworking industrial machines for a major woodworking Italian corporation. Predicted failures probabilities are calculated through tree-based classification models (Gradient Boosting, Random Forest and Extreme Gradient Boosting) and calculated as the temporal evolution of event data. This is achieved by applying temporal feature engineering techniques and training an ensemble of classification algorithms to predict Remaining Useful Lifetime (RUL) of woodworking machines. The effectiveness of the proposed method is showed by testing an independent sample of additional woodworking machines without presenting machine down. The Gradient Boosting model achieved accuracy, recall, and precision of 98.9%, 99.6%, and 99.1%. Our predictive maintenance approach deployed on a Big Data framework allows screening simultaneously multiple connected machines by learning from terabytes of log data.

Keywords: Big data platform | Feature engineering | Machine learning | Predictive maintenance | Remaining useful lifetime

Abstract: Nowadays, smartphones and laptops equipped with cameras have become an integral part of our daily lives. The pervasive use of cameras enables the collection of an enormous amount of data, which can be easily extracted through video images processing. This opens up the possibility of using technologies that until now had been restricted to laboratories, such as eye-tracking and emotion analysis systems, to analyze users' behavior in the wild, during the interaction with websites. In this context, this paper introduces a toolkit that takes advantage of deep learning algorithms to monitor user's behavior and emotions, through the acquisition of facial expression and eye gaze from the video captured by the webcam of the device used to navigate the web, in compliance with the EU General data protection regulation (GDPR).

Keywords: Affective Computing | Convolutional Neural Networks | Deep Learning | Gaze detection | User Experience

Abstract: This paper introduces a motion analysis system based on a network of common RGB cameras, which provides the measurement of various angles considered for postural assessment, in order to facilitate the evaluation of the ergonomic indices commonly used for the determination of risk of musculoskeletal disorders of operators in manufacturing workplaces. To enable the tracking of operator postures during the performed tasks, the system exploits the multi person keypoints detection library “OpenPose”.

Keywords: Assembly line | Ergonomic assessment | Manufacturing | Motion capture | OCRA index | Posture analysis

Abstract: The paper describes the conceptual model of an emotion-aware car interface able to: map both the driver’s cognitive and emotional states with the vehicle dynamics; adapt the level of automation or support the decision-making process if emotions negatively affecting the driving performance are detected; ensure emotion regulation and provide a unique user experience creating a more engaging atmosphere (e.g. music, LED lighting) in the car cabin. To enable emotion detection, it implements a low-cost emotion recognition able to recognize Ekman’s universal emotions by analyzing the driver’s facial expression from stream video. A preliminary test was conducted in order to determine the effectiveness of the proposed emotion recognition system in a driving context.

Keywords: Driver Monitoring System | Emotion recognition | Facial expression recognition

Abstract: Very often historical buildings used as museums are characterized by rooms completely covered with decorations (e.g. frescoes, inlay, etc.) rich in details and symbolic contents. Providing adequate information to the visitors to allow them to fully appreciate the artworks is of paramount importance in this context. X-reality technologies have the potential to provide an effective response to the need to combine the educational mission of museums with the ability to involve visitors emotionally, allowing the public to learn new knowledge in a playful way. This study introduces a Museum Guide System, based on Dynamic Projection, to increase the involvement of visitors to the Studiolo by Federico da Montefeltro at Urbino, minimizing technology intrusiveness by ensuring a complete fusion of digital contents with the physical environment. The system is able to track the visitors, to detect their profile and to offer information and multimedia contents tailored to the characteristics of the audience (e.g.

Keywords: Adaptive system | Digital Cultural Heritage | Dynamic projection | Museum Guide System | Spatial Augmented Reality

Abstract: This paper introduces a new system capable of adaptively managing multimedia contents (e.g. music, video clips, etc.) and lighting scenarios based on the detected user's emotional state. The system captures the emotion from the user's face expression mapping it into a 2D valence-arousal space where the multimedia content is mapped and matches them with lighting color.

Abstract: MoBeTrack (Mobile Behaviour Tracking) is a toolkit for automated collection of data necessary to support User Experience (UX) assessment of mobile applications. In contrast to existing frameworks, it is able to collect user demographic information (i.e., age and gender), trace any user interaction and recognize user's emotions during the use of an application.

Abstract: This article proposes the use of an expert knowledge-based system capable of identifying possible machine tool failures caused by accidental events (e.g., cable disconnection, incorrect parameterization of machining, impact event, etc.). The proposed approach aims to identify the unpredictable causes of failures, starting from the analysis of the process data provided by the PLC Data Logger, without requiring to sensorize the machine in order to collect ad hoc condition monitoring data. To this end, it uses the experts rules and Fuzzy Logic algorithms to activate data analysis based on known machine fault conditions. The proposed approach has been validated on real case studies. A prototype system was developed in Python to identify electrospindle failures that occur when the spindle of a CNC machining center for woodworking is subjected to a strong axial impact.

Keywords: Expert systems | Fuzzy logic | Machine diagnostics

Abstract: An important area of risk management practice for manufacturing companies relates to the prevention of injuries and musculoskeletal disorders (MSDs). The greater benefits can be achieved where a preventive approach is used, based on ergonomic design of workplaces and attention to human requirements and limitations as well as human-machine interaction principles. The research aims at providing a pragmatic approach to support the application of ergonomic risk management in practice. It defines a multipath methodology to investigate human factors impacting on safety by considering the specific workspace, the adopted tools, the overall production environment and the workers’ activity. An industrial case study is described to illustrate the methodology and demonstrate the benefits for companies.

Keywords: Design methods | Digital manufacturing | Ergonomics | HCD | Human-centred design | Risk management

Abstract: Predictive Maintenance concerns the smart monitoring of machine to avoid possible future failures, since because it is better to intervene before the damage occurs, saving time and money. In this paper, a Predictive Maintenance methodology based on Machine learning approach is presented and it is applied to a real cutting machine, a woodworking machinery in a real industrial group, producing accurate estimations. This kind of strategy is important to deal with maintenance problems given the ever increasing need to reduce downtime and associated costs. The Predictive Maintenance methodology implemented allows dynamical decision rules that have to be considered for maintenance prediction using a combined approach on Azure Machine Learning Studio.

Abstract: This paper describes the conceptual model and the implementation of an emotion aware system able to manage multimedia contents (i.e., music tracks) and lightning scenarios, based on the user’s emotion, detected from facial expressions. The system captures the emotions from the user’s face expressions, mapping them into a 2D valence-arousal space where the multimedia content is mapped and matches them with lighting color. A preliminary experimentation involved a total of 26 subjects has been carried out with the purpose of assess the system emotion recognition effectiveness and its ability to manage the environment appropriately.

Keywords: Affective computing | Ambient intelligence | Emotion detection | Emotion recognition | Emotion-aware system | Face expression recognition | Smart environment

Abstract: The Internet of Things market is rapidly increasing and offers a wide variety of Smart Products (SPs) apparently similar but with different potentialities that the average user fails to perceive. In order to reduce purchase risks, consumers rely on online product reviews, which do not often reflect the effective quality of the products. For this aim, this paper proposes a systematic method to objectively evaluate SPs in a comprehensive way to support the consumer in choosing the product that most satisfies his/her needs.

Keywords: customer satisfaction | Internet of Things | products reviews | smart products ratings | systematic evaluation method

Abstract: The present work introduces an emotional tracking system to monitor Shopping Experience at different touchpoints in a retail store, based on the elaboration of the information extracted from biometric data and facial expressions. A preliminary test has been carried out to determine the system effectiveness in a real context regarding to emotion detection and customers' sex, age and ethnicity discrimination. To this end, information provided by the system have been compare with the results of a traditional video analysis.

Keywords: customer experience | emotion analysis | emotion tracking | face recognition | facial expression | shopping experience

Abstract: The technology has become a common part of our daily lives, and the integration of touchscreen technology into devices is quickly becoming equally common. In recent years, much research has been conducted on how people interact with handheld devices and on different types and uses of touchscreen technology, but there are few studies regarding people with severe problems of dexterity. For this reason, the present study aims to understand the effect of expertize with touchscreen on the performance of basic touch-gestures (i.e., tapping, dragging, pinching and spreading) in the case of people with Systemic Sclerosis. The performances of a total of twelve patients with SSc, six with and six without previous experience with touchscreen technology, were compared in the study.

Keywords: Accessibility | Hand dysfunction | Human computer interaction | Scleroderma | Systemic sclerosis | Touch gestures | Touchscreen interface | Usability

Abstract: The present work introduces an emotional tracking system to monitor Shopping Experience at different touchpoints in a store, based on the elaboration of the information extracted from biometric data and facial expressions.

Keywords: Customer experience | Emotion analysis | Emotion tracking | Shopping experience

Abstract: Interorganizational cooperation and in particular dyadic relationships are increasingly considered as key factors for small-and medium-sized enterprises' (SMEs) business success in the ultra-competitive context of globalization. To support the development of successful relationships, this paper proposes a qualitative approach to assess the quality of business-to-business (B2B) between SMEs based on the Relational Capability framework proposed by Alves et al. (2016). The proposed approach is applied to a real relationship between two SMEs, to verify its applicability in order to understand whether the quality of the relationship has an impact on the success of jointly produced products.

Keywords: B2B | Business relationship | Business relationship assessment | Dyadic relationships | Relational capabilities | Relationship between SMEs

Abstract: This research aims to develop a system that examines and reacts to the changing behaviors and emotions of individuals in order to improve their shopping experience. The system is able to track emotions in real time at different touchpoints in a store and control a set of networked devices to configure the sensing space and all provided services responsive to the cus-tomers’ needs.

Keywords: Context-aware computing | Emotion recognition | Methods for CX | Shopping experience

Abstract: Spatial Augmented reality (SAR) represents a key technology for the development of smart manufacturing as it is barrier free, does not require the use of Head Mounted Displays or any other wearable devices and it fits most of the industrial constraints. The paper presents a novel SAR-based system to support the manual work in future smart factories. It conveys technical instructions during assembly, provides alerts in case of risks for humans' safety and finally identifies which postures can bring to muscoloscheletric problems if repeated. Experiments with 30 participants demonstrated the effectiveness of the proposed SAR-based system as compared LED monitor-based system and the overall achieved usability. The results proved that SAR technology improves the operators' performance with respect to a LED monitor-based system and that users well accept it.

Keywords: Augmented Reality | Ergonomic assessmnt | In-Situ projection | Musculoskeletal Disorders evaluation | task guidance

Abstract: In the last decade, the environmental sustainability has become an important issue that drives more and more the consumer decisions. Consequently, industrial companies are called to meet the growing demand for more sustainable products. Especially in the furniture sector, customers pay serious attention to the emissions that negatively affect human health and so they request products with low volatile organic compounds (VOCs) emissions. This represents a big challenge because it requires the strictly control of each component provided by all the supply chain actors through expensive laboratory tests. For this aim, the present paper proposes a method to estimate the total VOCs emissions of furniture products starting from the characteristics of all semi-finished products (e.g., geometric features, product composition, process information and functionality) and through the definition of an appropriate impact scale based on historical data.

Keywords: Furniture products | Indoor air quality | Product declaration | Sustainable Manufacturing | VOC emissions

Abstract: This study describes an User-Centered approach to design an User Interface (UI) to support daily activities of people with dementia. Such interface is the main hub of a home automation system able to monitor the house and reminds to the users some information when they approach the door to leave the home. In order to involve end users in UI evaluation at the end of the first stage of the design process, a specific experimental protocol, based on task analysis, structural interview, and behavioral observation, is defined. It allows to evaluate user-machine interaction considering aspects related to both adequacy of product feature and user's subjective opinion and behavior. A disposable high fidelity prototype of the UI is realized by using a touch screen tablet. Two tests, respectively dedicated to verify the adequacy of the icons and the understandability of the interface, are performed. A total of 20 subjects with different MMSE score are involved. Results show that people with low and medium dementia are able to understand and use the touch interface and provide some suggestion about how the GUI can be improved.

Keywords: Assistive Technology | Dementia | Human-Computer Interaction | Usability Evaluation

Abstract: This paper presents a structured User Centered Design (UCD) method to design and develop a highly usable smart home platform to manage the energy consumption of connected appliances. It exploits advanced Tangible Augmented Reality (TAR) technologies to virtually prototype the conceived design solutions and carry out usability testing with sample users. Usability tests are carried out both on traditional high fidelity prototypes and on an innovative Tangible Augmented Reality prototype. Experimental results prove the efficiency of the UCD approach supported by virtual prototypes, instead of traditional ones, the reliability of TAR prototypes to detect usability problems and assess user satisfaction, and its high interaction quality.

Keywords: Human Centered Computing | Human Computer Interaction | User Centered Design | User Interface Design | Virtual Prototyping | Virtual Reality

Abstract: During old age, perceptual and cognitive abilities naturally decline, resulting in an increased difficulty at performing complex activities, e.g., cooking. A digital cookbook, complying with design recommendations, was designed to assist older adults in meals preparation. In particular, three versions were compared in a between-subjects experiment: one based on text, one based on text and images and one integrating text and videos. The study reports on a preliminary evaluation aiming at (a) testing the feasibility of the digital cookbook as a means for assisting older users and (b) which feature was more effective. All versions were well-received. Results from behavioral observations suggest that the image-based version was more beneficial as compared to its video-based counterpart. No differences emerged between the image-based and the text-based versions. In general, the digital cookbook proved to be an effective tool. However, the inclusion of complex multimedia materials, e.g.

Keywords: Ageing in place | Older adults | Touch screen interface

Abstract: Touchscreen technologies have become increasingly common in personal devices, so it seems necessary to improve their accessibility and usability for the older people. In the past years, a lot of studies have been conducted to improve touch interfaces, however, most them do not consider older people with very low attitude with ICTs. Moreover, the majority of studies date back 2014, so they lack to consider the most innovative technologies available today. The present study involves a sample of older people without previous experience with ICTs with the aim of analyzing how basic features of a touchscreen interface affect their performances with typical touch-gestures. A total of 22 participants have been involved.

Keywords: Accessibility | Human computer interaction | Older people | Touch gestures | Touchscreen interface | Usability

Abstract: In the recent years, the creation of a good Customer Experience has become one of means to help companies in competing in the arena of retail. This have led to a focus shift from product design to the customer services' design and customer marketing with the aim to elicit a unique experience able to improve customer satisfaction, influence customer's decision-making and foster repurchasing. In this context, the present paper investigates the close interplay between Customer Experience and User Experience and describes an experiment to give evidence of the effects of the customer journey on the user experience.

Keywords: Experience design | Organisation of product development | User centred design

Abstract: The purpose of the research is to develop an intelligent system able to support the design and management of a Customer Experience (CX) strategy based on the emotions tracked in real time at the different touchpoints in a store. The system aim is to make the shopping experience responsive to the customers’ emotional state and behaviour and to suggest successful product/service design guidelines and customer experience (CX) management strategies whose implementation may affect current and future purchases.

Keywords: Big Data | Collaborative CX design approach | Customer experience | Emotional recognition

Abstract: Search engines play an important role in determining the success of e-commerce. Despite many efforts have been made to improve searching methods (SM) they remain mostly limited to semantic elaboration of keywords. This implies that the SM are not capable of supporting the research of products that best satisfy customers, according to their characteristics and background. To overcome this limitation, this paper introduces an approach able to define a new ontological model that formalizes the knowledge necessary to implement a search engine capable to guide the customer to search the desired product or service according to his/her characteristics and needs. To this purpose, three essential aspects have been considered: a User Ontology (UO), a Product Ontology (PO) and rules (or properties) to link the user and product ontologies.

Keywords: Internet of things | Ontologies connection | Product ontology | User ontology | User-centred design

Abstract: Wearable computers allow users to record and access information at any time. The adoption and use of such devices is largely dependent on the users’ acceptance of the technology. Previous studies investigated technology acceptance of wearables without having end-users directly trying the technology. The present paper aims at assessing the user acceptance of a wearable device to support cooking related activities, together with aspects of usability and experience of use. To this end, we developed a kitchen apron with embedded commands for navigating through the contents of a digital cookbook and asked a group of younger (N = 15, mean age 23.9 SD = 2.5) and older users (N = 15, mean age 30.3 SD = 7.6) to deploy it while preparing a recipe. Respondents’ opinions were collected using questionnaires after they had accomplished the cooking task required. Overall, the kitchen apron was well received by both younger and older adults.

Keywords: Technology acceptance | Wearable computers

Abstract: Over the last years, several approaches have been defined to support Universal Design. However, a method that allows supporting universal design process in a systematic way is still lacking. Consequently, very often, products are merely designed according to design guidelines, without considering their effective context of use, while the success of products is often determined by the experience, intuition and sensitivity of designers, rather than by a real good design practice.

Keywords: Ability-oriented design | Adaptive systems | Human factors | Universal design | User-centered design

Abstract: In an inclusive and accessible smart environments context the implementation of the “design for all” method presents several critical issues. In fact, the universal design represents a difficult challenge for the designer because it depends on the complexity of human intentions in a particular time and place.

Keywords: Adaptable user interfaces | Universal design

Abstract: The present paper proposes a new adaptive smart kitchen environment able to support different users with several typologies of impairment (i.e., visual, motor, cognitive) in performing cooking activities. This system is managed through an adaptive user interface, which guides the user in food preparation according to users' capabilities and needs and permits household appliances controlling.

Keywords: Adaptive User Interface | Design for all | Human Computer Interaction | Smart Environment

Abstract: Search engine efficiency is an essential prerequisite to ensure a satisfactory on-line purchasing experience. Despite powerful tools available today, search engine is limited to a semantic elaboration of keywords and they do not allow users finding product categories that do not belong to their knowledge sphere. In this context, in order to make an effective search engine it is necessary to provide tools able to understand what the user is looking for and suggest the products that best satisfy their needs, regardless of users' background. To this aim, this paper proposes an innovative smart search strategy, based on artificial intelligence technologies. In order to highlight the system potential, the smart object market case study has been considered.

Keywords: Adaptive systems | Internet of Things | Product evaluation | Search dngine

Abstract: What is User Experience (UX) and how does it relate to Usability? The understanding of the mutual relationship between UX and product usability has a strong impact on product design methodologies and on the design outcomes' success.

Abstract: Smart Objects (SOs) market offers a wide variety of products apparently similar but characterized by different features that the average users fail to perceive. Consequently, their purchasing is often based on price and brand affection. In this context, users need a tool able to guide them in choosing the most suitable object to satisfy their expectations. To this purpose, this paper proposes a new systematic method to assess SOs in a comprehensive way: it allows to objectively assess and compare products and provides evaluation results tailored on users' needs.

Keywords: Internet of Things | Smart objects | Systematic evaluation process | Usability

Abstract: The present study proposes a new method to manage adaptation behaviour of adaptive system according to the output information provide by a user model based on Bayesian Belief Network (BBN). Such method has been applied in the development of smart interfaces for cooking and kitchen management, such as meal preparation and interaction with the major kitchen appliances, pandering the user's skills, expertise and disabilities. Nevertheless, this method is flexible and suitable enough to be used in other application contexts.

Keywords: Adaptive Interface | Bayesian Network | Decision making algorithm | Smart Home

Abstract: The continuous progress of interaction technologies reveals that we are witnessing a revolution that is leading to a redefinition of the concept of “user interface” and to the development of new ways to interact with the electronic devices of all sizes and capabilities. Current trends in research related to the Human-Machine Interaction (HMI) show a considerable interest toward gesture, motion-based and full-body based interactions. In this context, a User-Centered Design (UCD) methodology to implement these novel interaction paradigms into consumer products is proposed with the aim to improve its usability, intuitiveness and experience.

Keywords: Design methods | Gesture interaction | User interfaces | User-Centered design

Abstract: Nowadays to design a product able to adapt to end-users with different needs and abilities it is necessary to manage a multitude of information coming from the analysis of different context of use. This means that we have to handle parallel and interdependent UCD multiple process. This research aims to define a methodology, which may apply this philosophy into design practice.

Keywords: Universal design | User centered design

Abstract: Designing a multi-user adaptive interface means designing for diversity in end-users and contexts of use, and implies making alternative design decisions, at various levels of the interaction project, inherently leading to diversity in the final design outcomes. Nowadays Adaptive User Interfaces (AUIs) is becoming one of the major objectives addressed by Human Computer Interaction research. The present study provides an overview about the methods currently applied to the definition and development of AUIs. In order to study and develop adaptive user interfaces with the purpose to guarantee socialization, safety and environmental sustainability in a domestic day-by-day living space, a new method of holistic and adaptive user interface is proposed to support the modeling of information related to the user and the context of the interaction. In order to generate the user profiles, subjects older than 40Â years with different levels of technology affinity will be considered. These prototypes will be tested through different use cases in the context of smart home environments.

Abstract: In order to study and develop adaptive user interfaces with the purpose to guarantee socialization, safety and environmental sustainability in a domestic day-by-day living space, a new method of holistic and adaptive user interface is proposed to support the modelling of information related to the user and the context of the interaction to generate the user profiles, subjects older than 40 years with different levels of technology affinity have been considered.

Keywords: Adaptive interfaces | Design for AAL | User interfaces | User-centered design

Abstract: Quality of life of various types of people can strongly benefit of a design process developed to take into account needs and requirements of end users. In this context the paper present a study on the cognitive and physical abilities of elderly persons, to design a friendly kitchen, that is considered one of the most complex home environment for the provided functionalities and involved human capabilities. A robust inclusive design approach is conceived to make simple and intuitive the interaction between humans and the systems installed in the kitchen environment.

Keywords: home environment | mixed reality | user-centred-design | virtual prototyping

Abstract: In the last years, some attempts have been made to explore the use of smart objects, with the purpose of monitoring well-being and supporting people's independent living. However an inventory of characteristics of smart products currently available on the market is still lacking.

Keywords: Home Environment | Inclusive Design | Internet of Things | Universal Design

Abstract: Smart home grids require that their control devices are both usable and acceptable. The assessment of device usability and acceptability is often neglected due to the cost of prototyping solutions to be submitted to end-user during the different stages of the design process. In this context, the present paper describes a structured User-Centered Design (UCD) approach to develop usable control devices. It exploits advanced Tangible Augmented Reality (TAR) technique to represent the achieved design solution and perform usability testing without increasing development time and costs.

Keywords: Human-Computer Interaction | Smart Home | Tangible Augmented Reality | Virtual Prototyping

Abstract: Highly usable human-system interfaces can have a large benefit on the quality of life for the elderly and disabled. New emerging product design technologies, such as Virtual Reality (VR) and Augmented Reality (AR), give many opportunities to evaluate and improve system usability in the early design stages. In this way different design alternatives can be evaluated in terms of physical and cognitive performance. In this context the present paper describes a systematic approach for designing highly usable home environments and optimizing human-machine interaction. VR/AR technologies are adopted for user interface evaluation.

Keywords: Augmented Reality | Home environment usability | Inclusive design | User interfaces | Virtual Reality

Abstract: No abstract available