Human factors and ergonomics

Many workers and citizens have been forced to make a lifestyle change in the past two years due to the pandemic emergency. In order to keep a high level of personal health, the doctors suggest to do fitness exercises. Before the pandemic it was possible to do these exercises at the gym or during dedicated session in the office supervised by professional trainers. During the pandemic emergency the gyms were closed, the workers were forced to stay home and the people started to do gym exercises by themselves without the control of a professional figure. This situation could lead to several diseases associated to musculoskeletal disorders if the exercises are performed incorrectly. In this work, an approach based on the pose-estimator application OpenPose is developed. The reference exercise is an isometric squat performed by a professional trainer. During the exercise, thanks to a deep neural network, the pose-estimator gets a series of key-points and vectors which represent the user's pose. A dataset of videos (for both the correct and incorrect postures) has been used to train several machine learning algorithms. The result is an automatic tool that recognizes incorrect poses during the exercise and helps the performer to correct it.

Keywords: Computer vision , Ergonomics , Machine learning , Physiotherapy , Posture assessment

The human hand is a versatile and complex body part. It permits difficult movements with various degrees of precision and force. Several causes can lead to upper limb damage, including musculoskeletal disorders and diseases like stroke. The impairment can affect daily living activities. Patients usually undergo rehabilitation therapy with medical personnel for a long time after the traumatic event. In most cases, they use off-the-shelf medical devices. However, the shape of the upper limbs can differ a lot among people. A bespoke rehabilitative device could provide better comfort and usability, but the design process can be challenging. This work aims to present a digital workflow to generate a 3D virtual reconstruction of the patient's upper limb structure, to be used in the device design. Starting from a 3D scan acquisition of the patient's upper limb, the algorithm allows the creation of a polygonal mesh of the arm and the hand by a semi-automatic procedure. The algorithm uses neural networks' capability to automatically detect the upper limb's landmarks to localize the joints' coordinates. The joints' positions can be used to build a virtual skeleton for a 3D model of a human arm. The mesh of the model is subsequently wrapped around the scan of the real arm. The output consists in the 3D rigged model of the patient's upper limb with a manifold mesh that can be deformed using its virtual skeleton. The results have been assessed with patients who had sports injuries or strokes. The 3D deviations between the scan acquisition of the arm and the resulting model have been evaluated.

Keywords: 3D scan , 3D virtual reconstruction , automatic landmarks detection , neural network , upper limb rigged model

Design methods for sports engineering allow to improve the world around the athlete. In cycling, a sport device that can be useful to reduce and monitor the risk of injuries is a smart glove equipped with pressure sensors. The literature underlined how the current design methods lack the comprehensive consideration of sensors integration for force analysis at the handlebar. Furthermore, the majority of existing solutions is based on resistive pressure sensors. In this work, we present mainly two advancements with respect to the state-of-the-art: (1) user-centered design methodology for the glove development, which allows to take care about the main design parameters which involve the cyclist, namely her/his anthropometric characteristics and her/his sport gesture analysis (achieved by the pressure analysis on the handlebar) during classic grip position of cycling (i.e., top grip); (2) prototyping of custom-made capacitive pressure sensors instead of classic commercial resistive pressure sensors. The work involves the concept generation, the selection of the optimal concept through Kano and Quality of Function Development as well as the preliminary prototyping of one capacitive pressure sensor, realized using a fabrication process involving additive manufacturing techniques and silicon molding.

Keywords: capacitive sensors , human body scanning , injury risk , user-centered design

Although autonomous driving has significantly developed in the last years, its acceptance by users is still low, even due to the different interaction modalities between the human agent and Autonomous Vehicles (AVs). Therefore, this paper proposes an analysis of the existing research on the influence of Human-Machine Interfaces (HMIs) on the user acceptance of AVs from the perspective of interaction design. The authors reviewed the fundamental changes in the way users interact with AVs. The paper focuses on the transfer of the vehicle control between the human and the artificial intelligence agent, the user experience of Non-Driving-Related Tasks (NDRTs) and sharing autonomous driving in public transportation, and the impact of external HMI on Vulnerable Road Users (VRUs). In addition, the paper analyzes the concept of acceptability and describes the existing user acceptance models. Finally, the paper explores the future challenges for promoting the design potential of autonomous vehicle HMIs and proposes areas worthy of research to increase the user's acceptance of this technology

Keywords: autonomous vehicles , human-machine interface , user acceptance model , vulnerable road users

In the context of human–computer interaction (HCI), understanding user engagement (UE) while interacting with a product or service can provide valuable information for enhancing the design process. UE has been a priority research theme within HCI, as it assesses the user experience by studying the individual's behavioral response to some stimulus. Many studies looking to quantify the UE are available; however, most use self-report methods that rely only on participants' answers. This study aims to explore a non-traditional method, specifically electroencephalography, to analyze users' engagement while interacting with an advergame, an interactive form of advertising in video games. We aim to understand if a more interactive type of advertising will enhance the UE and whether, at the same time, it would influence the user's purchase intention (UPI). To do this, we computed and compared the UE during the interaction with an advergame and a conventional TV commercial while measuring the participants' brain activity. After the interaction with both types of advertising, the UPI was also evaluated. The findings demonstrate that a more interactive advertisement increased the participants' UE and that, in most cases, a UE increment positively influenced the UPI. This study shows an example of the potential of physiological feedback applications to explore the users' perceptions during and after the human–product interaction. The findings show how physiological methods can be used along with traditional ones for enhancing the UE analysis and provide helpful information about the advantages of engagement measurement in HCI applications.

Keywords: advergames , EEG , purchase intention , user engagement

The 3D reconstruction of upper limb anatomy plays a significant role in many biomedical fields such as ergonomics, motion rehabilitation, and prosthesis design. In the last few years, the technical advancement of consumer-grade depth cameras has supported the development of portable and low-cost optical 3D body scanners for healthcare applications. The real-time scanning of human body parts, however, still represents a complex task due to the non-stationary nature of the scanning target. This issue imposes that the scanning time must be reduced as much as possible to minimize scanning artifacts. In this regard, depth cameras can capture geometrical information at video frame rates, thus guaranteeing fast acquisition times. Furthermore, the simultaneous use of multiple sensors would minimize undercut geometries, which impair the 3D reconstruction's completeness. In this work, a portable 3D optical scanner has been developed by rigidly assembling three Intel® RealSense™ D415 depth cameras on a lightweight circular frame. The three sensors are mutually calibrated, by using a 3D printed calibration specimen, to simultaneously align acquisitions from the three different camera viewpoints for each scanner pose. The system's effectiveness has been assessed by acquiring the geometry of both a plaster hand and a human hand and comparing the results with those obtained by a high-end stationary structured light scanner. The developed system represents a low-cost handheld alternative to existing body scanners for collecting and storing 3D anatomical data, which can be used in the design process of bespoke medical devices.

Keywords: 3D optical scanning , D415 Intel® RealSense™ , Depth-camera , Upper Limb Reconstruction

Background: Simulation has been recognized as a shift in healthcare education that can improve skills and patient safety and outcomes. High-fidelity simulation of critical medical situations can be a source of stress among participants that can interfere with students' abilities leading to unexpected emotional responses. The aim of this study is to determine if two simulation methods, high-fidelity (HF) and procedural simulation (PS), may be associated with stress responses at a self-perceived and biological level (salivary cortisol variations), and to compare stress levels of the two different simulation method. We also wanted to find independent variables associated with cortisol total hormonal output. Methods: A quasi-experimental before-after study was used including the administration of questionnaires, and biomarkers evaluation by salivary cortisol samples before and after simulation. A total of 148 students were eligible and agreed to participate in the study. We used paired T-test for mean comparison regarding State-trait anxiety for both HF and PT simulations. For NASA-TLX we performed a T-test mean comparison between groups. We used paired T-test mean comparison for cortisol analysis. Multivariable linear regression has been used to assess variables associated with AUCg values and perceived stress. Results: values of STAI-Y scores were relatively higher at the end of the HF and PS sessions. NASA-TLX was significantly higher at baseline for the HF simulations, with respect to the PS simulation. Cortisol fold increase was significantly different in the two groups. Linear regression showed that cortisol AUCg was related to the STAI-Y score in both groups. Conclusion: Participating students developed a stress response both after in the HF and PS training, testified by psychological and biological outputs. According to our results, stress levels were increased for simply being in a simulation scenario than to the intrinsic complexity of the task required. More studies are needed to confirm this trend and to clarify the role of simulated stress response in a long-term learning scenario.

Keywords: Anxiety , Cortisol , High-fidelity , Medical training , Simulation , Stress

The dynamic behavior of a Powered Two-Wheeler (PTW) is much more complicated than that of a car, which is due to the strong coupling between the longitudinal and lateral dynamics produced by the large roll angles. This makes the analysis of the dynamics, and therefore the design and synthesis of the controller, particularly complex and difficult. In relation to assistance in dangerous situations, several recent manuscripts have suggested devices with limitations of cornering velocity by proposing restrictive models. However, these models can lead to repulsion by the users of PTW vehicles, significantly limiting vehicle performance. In the present work, the authors developed an Advanced Rider-cornering Assistance System (ARAS) based on the skills learned by riders running across curvilinear trajectories using Artificial Intelligence (AI) and Neural Network (NN) techniques. New algorithms that allow the value of velocity to be estimated by prediction accuracy of up to 99.06% were developed using the K-Nearest Neighbor (KNN) Machine Learning (ML) technique.

Keywords: advanced rider assistance systems , k-nearest neighbor , machine learning , maximum cornering velocity , powered two-wheeler dynamic behavior

Artificial limbs can help people missing body parts to restore some of their daily-life activities. However, the user should spend up to a few months to intuitively control the new device. During this period, she/he may suffer pain due to wearing or using the prosthesis inappropriately. This research presents a virtual simulator that allows the user to carry out training sessions for controlling the prosthesis. A set of Surface Electromyographic (sEMG) sensors are used to acquire the signals from user's muscles and send them to a recognition algorithm that interprets the patient's intentions. Simultaneously, the patient observes the response of her/his device on the simulator. Two studies are presented: the first study evaluate the performance of three different recognition algorithms i.e., Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP), based on the successful recognition of the patient's intentions. The second study investigates the least number of sEMG sensors to be used, as having less components improves the patient's wearability and decreases the processing time. The developed simulator represents a real prosthetic device, PRISMA hand II. The results showed the superiority of the MLP with 80% of successful recognition when 6-sEMG sensors are used. If a reduced set of gestures is considered (frequently needed by the patient), 90% of successful recognition could be achieved. Less sEMG sensors significantly degraded the performance of the recognition algorithm as only 53.8% of successful recognition could be achieved. All experiments were conducted with the help of a patient with below-elbow amputation.

Keywords: Active prosthetic hand , Biomechatronic application , Multi-Layer Perceptron (MLP) , Pattern recognition , Rehabilitation robotics , sEMG signal processing

Urban mobility scenarios are constantly evolving, and today's solutions may not be adequate in the future. Through innovative analysis and design methods encapsulated by the IDeS methodology, it is possible to plausibly hypothesize a number of key scenarios to be analyzed, for which vehicles can be designed in order to solve the main problems. Scenarios such as the steady growth in public mobility, based on the sharing of electric mini-buses at the expense of the privatization of the means of transport, lead to the gradual rethinking of citizens' needs and the supporting infrastructure. Problems such as the lack of privacy of public vehicles, the efficiency of the infrastructure and recharging modes of e-buses, and autonomous driving are addressed here through methods such as QFD (quality function deployment) and SDE (stylistic design engineering), with the aim of outlining a proposal that, to date, is futuristic but is designed to be concrete and feasible within the next decade. These methodologies were applied to the design of a sustainable urban transport system consisting of an electric mini-bus, effected by rethinking the layout of the interior spaces in favor of areas enabling greater privacy and a mobile recharging system (MBS) capable of offering a new management strategy for the non-stop recharging phase. Through the use of an MBS, which functions as a mobile ‘energy bank' module that is capable of autonomously reaching a mini-bus in need of recharging and extending its autonomy by connecting and recharging it, the proposed system can potentially be enabled to perform its required service during the day without any need to spend time making intermediate stops for the purpose of recharging.

Keywords: autonomous driving , human centered design , minibus , privacy , range , recharging systems

The design research and education landscapes are changing. The widespread development and use of technologies such as Mixed Reality (MR) and the diffusion of Head-Mounted Displays (HMDs) available at low cost are causing a shift in design education toward the Metaverse. In this ever-changing scenario, there is a need to rethink design and teaching methods. However, scientific literature lacks the ability to provide contributions that include MR technology education in the industrial design program. We, therefore, present an innovative laboratory with an integrated multidisciplinary approach that starts from the fundamentals of interaction design and aims to teach students how to design next-generation MR interfaces for the Metaverse. The lab combines theory and practice within three courses: Information Design, Information Systems, and Virtual Design and Simulation. Industrial design students follow a precise multidisciplinary method consisting of five steps, from state-of-the-art analysis to the presentation of a final group design of an MR user interface. Thus, we introduce a class case study by presenting the outcomes of a semester project in the field of household appliances. Evaluation of the teaching method is conducted through a semi-structured questionnaire. Preliminary results show positive outcomes from students in terms of acceptance, effectiveness, usefulness, efficiency, and satisfaction with the teaching method adopted for the laboratory.

Keywords: industrial design , interaction design , metaverse , mixed reality , teaching method , user interface design

Recent analysis has shown deteriorating traffic conditions in urban areas, caused by an increase in the motorization rate, which has risen to 66.6 vehicles per 100 inhabitants. As a result of the pandemic, individuality has grown, hence private vehicles are becoming more prevalent whilst public transport and sharing are negatively affected. Therefore, European policies have encouraged and innovated more sustainable mobility. Thus, the developed project aims to achieve more efficient mobility and more sustainable environments, towards social and economic well-being. The proposed means of transport aims to appeal to an audience with a reduced ability to drive a car as intended. The IDeS methodology was applied to develop a self-driving, urban micro mobility vehicle, aimed to give enough room and equipment for people with moving disabilities. The innovation of the IDeS method is state-of-the-art and ought to satisfy current product needs, which leads to an innovative micromobility vehicle and portrays a design for a car that will help to close the gaps in urban mobility. These design processes, which are distinguished by the fusion of several industrial techniques, enabled the development of a plan that addresses current mobility issues for disabled people and opens to new mobility prospects.

Keywords: design for all , industrial design structure (IDeS) , quality function deployment (QFD) , sharing mobility , stylistic design engineering (SDE)

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. Results suggest how collected data can be useful for the artistic director to estimate the audience's overall level of satisfaction and make choices about the specific characteristics of the performance, and that emotional valence measured on the audience during the show can be useful to predict overall customer satisfaction, as measured using traditional self-report methods.

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

The paradigm of Industry 4.0 involves fully automated and interconnected industrial production processes demanding a great deal of human-machine interaction. This implies the emergence of new problems related to the stress assessment of workers operating in new and more complex work contexts. To address this need, it may be important to implement automated stress detection platform designed to be effective in a real-world work setting. Many works in the literature deal with the stress evaluation topic, they use above all wearable systems that are often intrusive and subject to noise and artifacts that degrade performance. Moreover, most of them integrate supervised machine learning algorithms, which achieve high levels of detection accuracy, but require a complicated training phase, which might not be suitable in a real-world context. To reduce these limitations, a stress detection platform combining data from a wearable and an environmental system is presented in this paper. It analyses heart rate, galvanic skin response and camera RGB signals. The wearable device was designed to be minimally invasive with good signal stability and low noise, while a commercial camera was added to improve the performance of the whole hardware architecture. From the software perspective, the presented solution was first tested and validated using a supervised approach. Subsequently, attention was focused on the analysis and development of an unsupervised solution, implementing three unsupervised algorithms. The best performance was obtained with the Gaussian Mixture Model having an accuracy of 77.4% considering one level of stress and 75.1% with two levels of stress.

Keywords: Ambient sensor , Smart system , Stress monitoring , Unsupervised learning , Wearable sensor

Despite an increase in the use of exoskeletons, particularly for medical and occupational applications, few studies have focused on the wrist, even though it is the fourth most common site of musculoskeletal pain in the upper limb. The first part of this paper will present the key challenges to be addressed to implement wrist exoskeletons as wearable devices for novel rehabilitation practices and tools in the occupational/industrial sector. Since the wrist is one of the most complex joints in the body, an understanding of the bio-mechanics and musculo-skeletal disorders of the wrist is essential to extracting design requirements. Depending on the application, each wrist exoskeleton has certain specific design requirements. These requirements have been categorized into six sections: purpose, kinematics, dynamics, rigidity, ergonomics, and safety. These form the driving factors behind the choice of a design depending on the objectives. Different design architectures are explored, forming the basis for the various technical challenges that relate to: actuation type, power source, power transmission, sensing, and control architecture. This paper summarizes, in a systematic approach, all the current technologies adopted, analyzes their benefits and limitations, and finally proposes future perspectives.

Keywords: design architectures , exoskeletons requirements , wearable devices , wrist exoskeletons

In marketing, the need to make products' packages as much attractive as possible is generally acknowledged as one of the leading assets. However, art designers also aim to surprise people and often break previous assumptions. In 2020, Kunel Gaur has produced a series of “dystopian” images of globally famous brands, by following the principles of minimal design. Although the images clearly contrasted biological principles, they obtained positive to enthusiastic comments from other designers. The present work is aimed at evaluating whether designers' judgement is congruent to other people's perception. Participants were recruited among students in three university faculties to represent these perspectives: designers, marketers and common customers. They compared 50 images produced by the artist. The results showed that designers were more likely to prefer the innovative design and the traditional packaging, while the other two groups appreciated the traditional packaging. Education in a certain domain emerged as significant effect for design skills only, indicating that this skill depends on learning, while both people's preference and field of study may be influenced by common personal factors, not dependent on learning. Although these findings may not be generalized, they show that the perception of innovative product packaging in designers is different from other perspectives.

Keywords: Customers , Design , Graphic packaging , Marketing , Perception

With the high growth and prosperity of e-commerce, the retail industry needs to explore new technologies that improve digital shopping experiences. In the current technological scenario, Virtual Reality (VR) emerges as a tool and an opportunity for enhancing shopping activities, especially for the fashion industry. This study explores whether using Immersive Virtual Reality (IVR) technologies enhances the shopping experience in the fashion industry compared to Desktop Virtual Reality (DVR). A within-subject experiment was carried out involving a sample of 60 participants who completed a simulated shopping experience. In the first mode (DVR), a desktop computer setup was used to test the shopping experience using a mouse and keyboard for navigation. The second mode (IVR) exploited a Head-Mounted Display (HMD), and controllers, that allowed navigation while seated on a workstation to avoid sickness. Participants had to find a bag in the virtual shop and explore its features until they were ready to purchase it. Post-hoc measures of time duration of the shopping experience, hedonic and utilitarian values, user experience, and cognitive load were compared. Results showed that participants experienced higher hedonism and utilitarianism in the IVR shop compared to DVR. The cognitive load was comparable in both modes, while user experience was higher in IVR. In addition, the time duration of the shopping experience was higher in IVR, where users stayed immersed and enjoyed it for longer. This study has implications for fashion industry research, as the use of IVR can potentially lead to novel shopping patterns by enhancing the shopping experience.

Keywords: Fashion industry , Retailing , Shopping experience , User study , Virtual reality

Sustainable production and consumption consist of using goods and services that respond to basic needs and bring a better quality of life without jeopardizing the needs of future generations. Over the last decades, this has become a topic of increasing importance for companies and consumers. Consequently, from one side methods and tools to assess and quantitatively measure the environmental burden of products and processes arose; from the other side, more and more consumers have raised their sensitivity concerning sustainability. However, consumer perceptions and objective data need to be aligned. The present paper addresses the topic of the discrepancy between the environmental sustainability of product lifecycles as perceived by consumers and actual results obtained with well-known and accepted methods and tools. The paper quantifies through Life Cycle Assessment the environmental burdens of three products for the textiles/apparel sector, particularly swimming sport: a pair of goggles, a pair of swimming pool slippers and a swimsuit. Those were subsequently compared with 102 responses to a questionnaire about environmental sustainability. The comparison was made between the qualitative expectation of the customers and the results of the Life Cycle Assessment for the Climate Change impact category, due to the higher awareness and sensitivity of the customers for this indicator, than others. Respondents belong to three distinguished groups: scholars, employees and students. According to the analysis of obtained results and discrepancies, three main recommendations are outlined by the authors to improve the environmental sustainability of apparel products: the need to promote the development of software tools and databases to support the integration of sustainability into products design; training on products sustainability in the academic world must be encouraged in order to provide future designers/product managers with the tools needed to cope with actual challenges; and consumers should be adequately informed. Graphical Abstract: [Figure not available: see fulltext.].

Keywords: Consumer awareness , LCA , Product Sustainability , Questionnaire survey , Swimming product

Background: The COVID-19 outbreak led to the diffusion of several telemedicine solutions. The choice of the correct platform is crucial for ensuring the release of effective assistance. However, there is a lack of an objective method for the assessment of technical features. Objective: This study proposes a methodology for the evaluation of functional requirements of telemedicine platforms. This approach also permits the comparison of solutions in the Italian market by means of defined parameters, thus directing the choice of health care professionals. Methods: The study is divided into three phases. First, a mapping of the telemedicine platforms operating in Italy is performed. Then, the available platforms are selected based on the offered telemedicine activity. Finally, a method for evaluating the investigated platforms is defined. Results: Thirty-three (n = 33) technological systems were identified through an accurate investigation on the web and interviews with IT companies. Fifteen parameters were defined and organized into three categories: (1) usability of the telemedicine platform, (2) security, and (3) technological and organizational aspects. A score between 1 and 4 was assigned to each parameter, proportionally to the completeness of the platform. In particular, 62.96% of platforms reached an average score between 3.01 and 4 points; 33.33% of them had scores between 2.01 and 3, while the remaining 3.70% of solutions obtained a result between 1.01 and 2. Conclusions: The study provides an evaluation approach that is easily usable by health professionals to select the most suitable platform. The number of solutions and quality of information could be updated to obtain a complete tool.

Keywords: technological assessment , telemedicine platforms , telemedicine solutions

User experience (UX) application in the practice of engineering and product design is still limited. The present paper provides insights into research on UX design and recommendations for design practitioners by pointing out common criticalities. These outcomes are achieved through a literature review on how UX relates to design. First, issues in benefitting from UX understanding in design are identified with a specific focus on theoretical contributions. Second, experimental papers investigating UX and design are analysed in relation to previously identified issues. Although issues are present to some extent in all the contributions, the empirical studies dealing with UX in design are overall valid. The results highlight UX\'s support in revealing design requirements, but its capability of steering design processes is arguable, as concrete guidelines for practitioners are not well described. Based on identified issues, the authors propose a checklist to make UX studies in design more reliable and their outcomes more comparable.

Keywords: best practices , design process , user experience , UX applications , UX issues