Human factors and ergonomics

The fourth industrial revolution (I4.0) is driving the development of automated and intelligent manufacturing systems, but managing these systems poses challenges, especially for maintenance and process control. The emerging Industry 5.0 (I5.0) concept advocates for a human-centered approach, integrating human skills with advanced technologies to address such challenges. This study introduces a novel holistic evaluation of ergonomics, moving beyond traditional physical assessments to include cognitive ergonomics, thus providing a more comprehensive analysis of operator interactions with industrial systems. The proposed approach leverages Virtual Reality (VR) simulations combined with wearable devices to collect data on users' movements and physiological parameters. This enables simultaneous evaluation of physical workload and cognitive demands, fostering early identification of ergonomic issues in the design process. Unlike traditional methods, our framework emphasizes a deeper integration of devices for enhanced data analysis, ensuring that both physical and cognitive factors are addressed. As a case study, the redesign of an automated packaging machine was undertaken. Results demonstrated significant ergonomic improvements, reducing the EAWS (European Assessment Work-Sheet) score (from 30% to 50% approx.) and incorporating cognitive ergonomics into the evaluation. These findings highlight the potential of this approach to enhance the operator's experience and optimize human-machine interaction in modern industrial environments.

Keywords: digital simulation , ergonomics and human factors , Human-centered design , industry 5.0 , virtual maintenance , virtual reality

The rapid evolution from Industry 4.0 to Industry 5.0 has heightened the need for integrating sustainability practices within complex system designs, particularly in the manufacturing sector. The research presents the development of a Sustainability Digital Twin (SDT) framework aimed at enhancing sustainable design practices for complex engineering systems. This framework integrates digital product models with sustainability indicators and uses Virtual Reality (VR) and Augmented Reality (AR) to promote Green Design principles. The approach begins with the definition of specific Sustainability Key Performance Indicators (S-KPIs) obtained by Life Cycle Assessment (LCA) tools. After that, using VR and AR allows to design and develop customized interactive dashboards to provide a comprehensive overview of sustainability indicators across the social, environmental, and economic dimensions, and to support decision-making along the product lifecycle. A core element of this transdisciplinary methodology is the adoption of a human-centered design philosophy, ensuring that user interfaces are intuitive and user-friendly, to Green Design tools, with the support of advanced digital technologies. The integration of human-machine interaction models aims at extending the current Green Design practices, mainly focused on environmental performances, towards social areas, including human-centric aspects such as usability, accessibility, comfort and pleasure in use. The research applies the proposed transdisciplinary approach to an industrial case study on automatic production lines, focusing on the ceramics industry, developed in collaboration with a world leading company in this sector.

Keywords: Augmented reality , Digitization , Green design , Human-Centered Design , Industry 5.0, Virtual reality , Sustainability digital twin

Despite the significant surge in innovation and the ongoing trend of increasing automation levels in manufacturing and logistics brought along by Industry 4.0, companies continue to heavily depend on human labor to meet market demands for product customization and reduced time-to-market. Consequently, there is a pressing need for companies to enhance workforce skills within a shorter timeframe, leading to an increased demand for new training methodologies aimed at accelerating knowledge acquisition at a high-quality level. As the Industry 5.0 paradigm emerges, there is a renewed emphasis on human-centricity, encouraging collaboration between humans and machines to address new challenges in industrial environments. Extended Reality (XR) technologies offer a promising solution to bridge the gap between operators' needs and industrial requirements, enabling operators in navigating complex indoor spaces efficiently and safely, optimizing operational workflows and enhancing overall productivity. This research explores the application of XR technologies in indoor navigation, a crucial aspect of modern industrial environments. Two distinct approaches are introduced and compared: AR-Tablet-based and MR-HoloLens-based. Through a real industrial case study focused on indoor navigation in a spare part warehouse, technical insights are gathered to inform effective implementation strategies in logistics settings.

Keywords: Extended Reality , Human factors , Indoor Navigation , Microsoft HoloLens 2 , Operator training

The “Augmented Humans” term refers to the opportunity to improve human possibilities by using innovative technologies such as Artificial Intelligence (AI) and Extended Reality (XR). Digital therapies, particularly suitable for those treatments requiring multiple sessions, are increasingly being adopted for home-based treatment, enabling continuous monitoring and rehabilitation for patients, thus alleviating the burden on healthcare facilities by facilitating remote therapy sessions and follow-up visits. Among these, the Mirror Therapy (MT) for patients suffering from Phantom Limb Pain (PLP) could benefit greatly. This paper proposes a novel “Augmented Humans” framework for the treatment of PLP through home-based MT; the framework is designed to consider the activities carried on by the therapy center, the patient, and the system supporting the treatment. Moreover, an XR-based solution that integrates a Deep Learning (DL) approach has been developed to provide patients with a self-testing and self-assessment tool for conducting at-home rehabilitation sessions independently, even in the absence of physical medical staff. The DL algorithm enables real-time monitoring of rehabilitation exercises and automatic provision of personalized feedback on the gesture's performance, supporting the progressive improvement of the patient's movements and his ability to adhere to the treatment plan. The technical feasibility and usability of the proposed framework have been evaluated with 23 healthy subjects, highlighting an overall positive user experience. Remarkable results were obtained in terms of automatic gesture evaluation, with macro averaged accuracy and F1-score of 95%, paving the way for the adoption of the “Augmented Humans” approach in the healthcare domain.

Keywords: Augmented humans , Augmented therapy , Deep learning , Digital therapy , Extended reality , Home-based treatment , Phantom limb pain

Featured Application: Use of virtual reality technology in numerosity estimation tasks. Numeracy, the ability to use basic mathematical skills in everyday life, is essential in modern society. Recent studies have shown a connection between numeracy and visual numerosity perception, yet traditional 2D screen-based assessment methods often lack ecological validity and participant engagement. This study evaluates the viability of conducting numerosity estimation tasks in virtual reality (VR) and to determine whether hallmarks of numerosity processing, typically observed in laboratory settings, can be replicated in immersive environments. Six participants completed a psychophysical evaluation in VR, comparing the numerosity of visual stimuli consisting of two sets of spheres. The VR experiment successfully replicated two distinctive patterns found in traditional psychophysical studies: increased precision and decreased response times at high numerosities. Specifically, Weber fractions drop by approximately a factor of two, with values ranging from ~15% for low and intermediate conditions to ~8% in high numerosities, and response times decreases from ~663 ms for low numerosities to ~593 ms for high numerosities. These findings highlight that VR can be effectively used for numerosity estimation tasks, providing a controlled and immersive environment that traditional methods cannot achieve, while significantly expanding methodological possibilities in psychophysical research.

Keywords: human–computer interaction , numerosity estimation , perception , virtual reality

In the context of Industry 4.0, the Operator 4.0 paradigm plays a crucial role in seamlessly integrating new digital technologies into smart factories. These technologies are designed to accommodate workers with varying skills, capabilities, and preferences. To promote the adoption of these innovative digital tools and ensure high user acceptance, it is essential to prioritize human factors and place workers at the heart of the development process. This can be achieved through structured design strategies, such as those employed in user-centered design approaches. Within this framework, this paper introduces an innovative Augmented Reality tool designed to facilitate and streamline real-time inspection activities performed by operators on assembled products at the workplace. The development of this tool was based on a user-centered design approach, which actively engaged end-users at different stages of design and testing phases. User studies were conducted using a real case study to evaluate the usability and user acceptance of the proposed solution. The results are encouraging, indicating a promising path forward for the effective and valid implementation of this AR tool in an industrial setting.

Keywords: Industrial augmented reality , Industry 4.0 , Operator 4.0 , Technology acceptance model , Usability , User-centered design

This article investigates the cognitive load (CL) in the underexplored context of computer-Aided design (CAD), focusing on identifying the most effective electroencephalography (EEG) features for measuring CL variations. While previous research has demonstrated that the EEG can distinguish between CL levels in various domains, there is limited understanding of whether existing EEG-based indicators can accurately reflect CL changes in CAD activities. To address this gap, the study first extracted a list of potential EEG-based CL indicators from the literature and then evaluated their applicability to CAD tasks through an experimental study involving 24 engineering designers performing CAD modeling tasks of varying complexity. The experimental study employed two complementary methods: NASA TLX as a subjective measurement and EEG as a psychophysiological measurement, enabling a comprehensive analysis of the CL in CAD tasks by validating and comparing the findings from both methods. The results revealed six EEG features sensitive to changes in the CL, with an increase in parietal alpha task-related power emerging as the most prominent indicator. This study makes a novel contribution by examining the relationship between the EEG-based CL indicators and the NASA TLX scores, highlighting meaningful correlations, and emphasizing the importance of both frequency bands and cortical areas when interpreting EEG signals in relation to CL. © 2025 American Society of Mechanical Engineers (ASME).

Keywords: cognitive ergonomics , cognitive load , computer-aided design , electroencephalography , human performance

Occupational exoskeletons have been proven to provide a substantial support to workers; nonetheless, their efficiency is tightly related to proper fitting to the human body, and the acceptability of these devices might be hampered by discomfort produced by high pressures or reduced stability of the harnesses, that can result in scrubbing at the belts. This work aims to establish a numerical model that is computationally efficient and able to virtually assess the fitting of the exoskeleton and its comfort. A multibody model has been set up for this aim, where a discretised approximation was implemented for the flexible belts, paying special care to the proper setup of contact parameters between these belts and the human body. The results provided reliable estimations of contact pressures, being the numerical results within the confidence interval of experimental peak shoulder pressures found in literature. The model was then validated using experimental data collected immediately after the exoskeleton was worn and during squat and stoop movements. The model accurately estimated the internal strip force required for the exoskeleton stability under gravity (30.6 N) without generating skin injuries, in accordance with experimental results (35.6 ± 14.1 N). Relative movements between the exoskeleton and the human body were investigated for the stoop and squat actions; results showed that the exoskeleton moved of 10.2 cm during the stoop and 7.1 cm during the squat, so replicating the actual system behaviour (9.34 ± 2.20 cm and 9.04 ± 1.81 cm in experimental tests). The numerical model was proved to be able to accurately replicate the interaction of the exoskeleton-human body system, so representing a useful tool for the design of these devices.

The accessibility of nature trails for people with motor disabilities and impairments stands as a significant challenge for inclusive tourism. In the present study, we would like to present a review of research, approaches, and solutions to enable people with motor impairments to enjoy nature trails independently or with assistance. The study is conducted from the perspective of public bodies that aim to reduce the accessibility barriers for People with Disabilities (PwDs) by adapting and improving the conditions of the trails and by providing clear and comprehensive information about the difficulties that hikers may encounter on a trail while using a specific aid. The paper initially presents the wide variety of aids for outdoor mobility, including both those to be used independently (i.e., self-propelled wheelchairs that can be equipped with additional small wheels, off-road wheels and/or auxiliary drives) and those that require assistance (e.g., single-wheeled wheelchairs). Then, we shift focus onto the difficulty classification of trails for PwDs, analysing papers and guidelines that tried to define objective evaluation criteria such as the slope, the trail surface, and the length of the sloping sections. Starting from these studies, the paper proposes a synthesis of the different classifications that consider, for the first time, all the aids available on the market, thus filling the gaps of the single studies. In the last sections, we present some national and international guidelines with tailored and practical solutions to improve the accessibility of nature trails and some studies about the inclusive planning that directly involves PwDs, as well as on the need for a better training of tourism service providers. The present work aims to stimulate a debate on the barriers and opportunities related to the accessibility of hiking trails, contributing to making nature a truly accessible experience for all.

Keywords: accessible hiking , barrier-free trails , inclusive design , inclusive tourism , mobility aids , motor disability , motor impairment , self-propelled wheelchair , trail classification

The progressive population ageing is rapidly transforming our societies. Assistive robots become an opportunity to favour the ageing in place allowing elderlies to remain in the home environment while increasing safety, healthy lifestyles, and remote monitoring for facilitating early intervention in an emergency. The present pilot work aims to compare two different human-robot interactions based on both usability and user-experience standardized scales and semi-structured interviews administered to a group of 10 elderly people to identify the factors affecting technology acceptance. The use of two different robots based on touch screen (Temi) and oral communication (Ohmni) equipped with specific sensors is investigated in four different scenarios with both clinical and social purposes: cognitive stimulation, nutritional control, physiological parameters monitoring, and entertainment. The study's findings report that the initial distrust in innovative and unusual technologies may be reduced by approaching them in a controlled environment. However, the perception of the usefulness and usability of robots, and more generally of technology, is also influenced by the personal nature of the user and the reason for use. Indeed, robots appear to be a threat to older adults' independence, especially those who stay fit and behave independently. Concerning the robots' interaction modes, most users preferred a combined interaction based on both vocal and written communication to make up for hearing or visual problems. Moreover, a robot exhibiting both a static and dynamic mode was preferred. However, further studies should be devoted to the optimization of the adopted technologies considering the users' feedback for improved adaptivity and technology acceptance.

Keywords: Healthy ageing , Human-robot interaction , Older adults , Socially assistive robots , Technology acceptance , Usability , User experience

Controls and prevention activities for musculoskeletal disorders are increasingly encouraged in the industrial context. Several ergonomic assessment techniques exist. However, they primarily focus on the biomechanical and postural load requirements of job tasks and rely on self-report and observational methods rather than direct measurements, which are often too intrusive. This study investigates whether a commercially available low-intrusive and low-cost wearable sensor can be utilised to assess muscular effort and fatigue, thereby improving decision-making in work and workstation design. For this purpose, the potential of the Myo™ armband has been explored. The electrical activity of the upper limbs (arm and forearm) was evaluated through 15 physically tasks (manual handling and assembly) conducted in laboratory conditions. Satisfactory results were obtained from the correlation and significance analysis, considering the EMG signal, the Borg scale, and the activity level (e.g., load, distance, n° of repetitions). Further experimentation was conducted to validate the proposed approach in a real production facility.

Keywords: Electromyography , Human-centered manufacturing , Muscle effort and fatigue , Physical ergonomics , Upper limbs , Work-related musculoskeletal disorders

A major challenge in constructing models of the human body or body parts stems from the fact that they are actually composed of several solid bodies articulated together. Consequently, 3D models must be parameterised with reference to joint angles: scans of the foot taken at different plantar/dorsal flexion angles were used in this study as a benchmark. The imple-mented methodology was based on the regression fitting of landmark trajectories obtained on a limited number of foot poses; these same landmarks were then used to guide 3D mesh morphing to predict foot geometry at different plantar/dorsal flexion angles. A careful optimi-sation of the methodology was performed to identify the optimal set of foot scans. The comparison between the actual foot shapes obtained by 3D laser scanning and the predicted shapes showed that the average error is at most 6.57 ± 2.74 mm. The methodology indications were finally drawn based on these error estimates. Further works will consider combined motions including flexion/extension, internal/external rotation, and foot inversion/eversion. © 2025 by the authors of this article.

Keywords: 3D laser scanner , 4D model , foot landmarks , mesh morphing , shape prediction

This study investigates the perception of postural discomfort experienced by passengers seated in the middle rear seat of a vehicle—an area often overlooked in ergonomic research. A total of 20 participants (12 males and 8 females) were involved in a pilot test using two car models: a City Car (Fiat Panda) and a C-SUV (Renault Arkana). Each participant completed a short on-road ride (~24 min, 11.7 km) in both vehicles. Discomfort was assessed using a 5-point Likert scale, considering both overall and localized body discomfort, as well as other elements/factors, such as those involved in the human–car interaction (e.g., the central tunnel, the headrest, AC vents, and other passengers). The results showed that overall discomfort was significantly higher in the City Car (mean: 3.75 ± 0.72) compared to the SUV (mean: 3.00 ± 1.16). The most affected body regions in the City Car were the arms (mean: 3.95), knees (3.90), and legs/feet (3.55). In the SUV, discomfort was lower across all regions, with the arms (3.15) and knees (3.05) still being notably impacted. Strong correlations were observed between discomfort and several vehicle features: backrest width, headrests, interference with adjacent passengers, and rear air conditioning vents. This study highlights specific ergonomic issues in the middle rear seat and suggests design improvements, including wider backrests and headrests, repositioned air vents, and the inclusion of lateral supports. These findings offer actionable insights for automotive manufacturers to enhance passenger comfort in multi-passenger configurations.

Keywords: car seat , discomfort , passenger behavior , posture , rear seat

Background: Both industries and academia are paying deep attention to the concept of trust in automation since it is significant that creates people's desire to use and buy autonomous cars. Objectives: Regarding the previously introduced trust questionnaire by our research team, this study was conducted to present more objective insights of this questionnaire to show its convergent validity based on the physiological data. Methods: Using a dynamic driving simulator, the 8-step experiment was performed on 29 min with 21 participants. The steps provided building, improvement, destruction, and re-building of trust. The experiment contained both manual and autonomous driving. Subjects completed stress and trust scales regarding the experience they performed. Finally, they answered to the trust questionnaire; their heart rate was acquired throughout the experiment. Results: The Mean ± SD of participants' trust score was 139 ± 5.76. Self-driving car's unsafe behaviors were accompanied by a rise in the individuals' heart rates (objective metrics of stress). Throughout the two phases of fastest and riskiest parts of the scenario, people felt the highest stress (6 out of 10) and the least trust (4.33 out of 10), that were obtained from the mentioned one question scale. Conclusion: Regarding the results, the mean score of people's trust from our multi-dimensional questionnaire is far from the desired score, which is 235. Objective (heart rate) and other subjective data (stress and trust) confirmed that the participants' trust in an autonomous vehicle was low.

Keywords: Autonomous vehicles , Heart Rate , Multi-dimensional questionnaire , Stress , Trust

Quality of Life (QoL) is a critical construct centered on well-being, serving as a fundamental theoretical framework for exploring individual and collective well-being across multiple dimensions. This study aims to enhance the evaluation of QoL by adopting the WHODAS 2.0 (World Health Organization Disability Assessment Schedule) as a reference. Developed by the World Health Organization (WHO), WHO-DAS 2.0 provides a standardized, cross-culturally validated instrument for measuring health, disability, and, more broadly, QoL, as it allows for examining the relationship between functioning, daily activities, social participation, and overall well-being. The primary objective of this study is to develop a chatbot that employs structured questions to collect comprehensive data on various aspects of individuals' lives, supporting the identification of critical areas and promoting well-being. Subsequently, the information collected will be analyzed to conduct a preliminary assessment and identify the most impaired QoL domains. The combination of the methodological rigor of WHODAS 2.0 and the capabilities offered by chatbot technology creates an innovative synergy, capable of over-coming traditional challenges in measuring and interpreting QoL data. Unlike conventional assessment methods, the proposed system not only identifies difficulties but also transforms collected data into opportunities for personal growth and social inclusion.

Keywords: Chatbot , Inclusive technologies , Large Language Models (LLMs) Digital health , Quality of Life

In recent years, the application of ergonomics to workplace safety monitoring has gained increasing interest from companies and public institutions, allowing for the evaluation of the potential impact that dangerous situations may have on workers during their routine activities. This study presents a method for real-time monitoring of human physiological and motor responses to simulated workplace hazards during virtual reality safety training. The setup allows for precise measurements of both physiological and postural parameters during simulated scenarios. Moreover, a representative case study involving the sudden arrival of a forklift in a warehouse is presented. Five healthy participants were exposed to this scenario, with changes in heart rate variability and trunk posture being captured. The results demonstrate the effectiveness of sensor-based monitoring in detecting stress responses and postural adaptations to hazardous stimuli. This approach provides a basis for understanding human responses in simulated hazardous environments and may help to optimize safety training aimed at increasing workers' risk perception and improving overall workplace safety. Although based on a small sample, the findings provide preliminary insights into the feasibility of sensor-based monitoring during VR safety training.

Keywords: heart rate , kinematic analysis , markerless motion analysis , posture , safety , trunk , virtual reality

Application of wearable robotic devices in training programs is gaining more and more interest. In the last few years, several training devices based on haptic and audiovisual stimuli have been developed to enhance training by stimulating proprioception. Transparency of these devices is a key parameter for the evaluation of their performance. In this study, we present the results of a transparency study of SIDE, a fully wearable 4-degree-of-freedom exoskeleton that provides haptic feedback to shoulder and elbow. The study examines transparency both kinematically and with respect to muscle activations using inertial sensors and surface electromyography, respectively. The study involved seven healthy subjects, who were asked to perform simple movements with their shoulder and elbow in two conditions (with and without an exoskeleton) and with three different masses. Our analysis, conducted using a repeated-measures ANOVA test, revealed that from a kinematic perspective, there were no observable differences between conditions. However, our findings showed greater muscle activation, especially for the anterior, middle, and posterior deltoids and the biceps brachii, when the exoskeleton was in use. At the conclusion of the experiment, subjective opinions of the participants were collected, revealing that they had not perceived any difference between the conditions.

Keywords: Biomechanics measurements , EMG , Exoskeleton , IMU , Surgeon training , Transparency

Technological advancements are profoundly reshaping industrial environments, particularly by introducing paradigms such as Industry 4.0 and Industry 5.0, prioritizing increased productivity alongside worker well-being improvements. Concurrently, the European Union reports a fast-aging population, reflected in the industrial workforce. Consequently, assessing the impact of emerging technologies across different age groups is crucial. This study employed an Immersive Virtual Reality (IVR) system to simulate a high-risk industrial scenario for training workers on safety and operational procedures. Fifty participants were divided into three age groups: young ranging from 19 to 33 years old, middle-aged ranging from 34 to 48 years old, and older ranging from 49 to 63 years old. The IVR system recorded execution times and errors, while subjective measures were collected using the User Experience Questionnaire, System Usability Scale, and Virtual Reality Sickness Questionnaire (VRSQ). The results show that younger participants committed significantly more errors but completed tasks faster, although this difference was not statistically significant. Self-assessment scores revealed no significant increase in VRSQ values across groups, while younger participants rated the system's hedonic quality significantly higher than the older group. System usability was rated substantially higher than the minimum acceptable threshold, with younger participants providing significantly better evaluations compared to older ones. This study highlights the importance of a human-centered design in IVR systems, complying with age-related needs to enhance usability. This approach ensures IVR technology in industrial training achieves optimal efficiency and effectiveness across diverse workforce demographics.

Keywords: Age-related performance , Immersive virtual reality , Industrial safety training , User experience metrics , Workplace accident prevention

The emergence of generative AI, large language models, and foundation models is fundamentally reshaping computer science, and visualization and visual analytics are no exception. We present a systematic framework for understanding how human-centered AI (HCAI) can transform the visualization discipline. Our framework maps four key HCAI tool capabilities-amplify, augment, empower, and enhance-onto the four phases of visual sensemaking: view, explore, schematize, and report. For each combination, we review existing tools, envision future possibilities, identify challenges and pitfalls, and examine ethical considerations. This design space can serve as an R&D agenda for both visualization researchers and practitioners to integrate AI into their work as well as understanding how visualization can support HCAI research. © IEEE.

Keywords: Artificial intelligence , Ethical technology , Flow visualization , Visual analytics

The advent of virtual simulation and Augmented Reality has had a profound impact on industrial processes, enhancing operational efficiency and optimising production workflows. This paper presents a comprehensive study on the development and implementation of a Mixed Reality Lab designed for the assembly and disassembly of industrial products. The primary objective is to create an advanced and intuitive Virtual Reality (VR) environment that facilitates industrial operators' learning and reduces training time while minimising errors. The project encompasses the scanning and 3D modelling of industrial components using various technologies, including photogrammetry, structured light, laser scanning, and LiDAR. These techniques are evaluated for their precision and effectiveness in generating accurate 3D models. The VR environment is developed using Unity, incorporating features that support interactive and immersive user experiences. Detailed methodologies for the creation and refinement of point clouds, mesh generation, and virtual environment setup are provided. The assembly and disassembly processes are tested using a brake assembly as a case study, thereby demonstrating the system's ability to manage complex industrial tasks. The results indicate significant improvements in training efficiency and operational precision, with potential applications across various industrial sectors.

Keywords: Mixed reality , Simulation , Training , User-centred application