Human factors and ergonomics

Achieving reliable user feedback during design is essential for developing products that meet customer needs, but this is challenging due to limited attention to key aspects of user interaction with new products. This paper examines overlooked factors influencing product evaluations at various design stages, focusing on familiarity, contextual information, forms of representation, and visual behavior through a three-study experimental activity (N = 77). Study 1 explored the impact of contextual cues on perception and comprehension of product functions using three unfamiliar products, comparing conditions with and without contextual cues. Study 2 assessed how contextual detail and product familiarity affect function comprehension by tracking visual behavior as participants viewed product images with different backgrounds using remote eye-tracking. Study 3 examined the effects of familiarity and representation detail on evaluation and function understanding by having participants assess digital models, physical prototypes, and end-use products. Results show that contextual cues are crucial for understanding unfamiliar product functions, influencing cognitive and, to a lesser extent, affective aspects. Detailed backgrounds aid function identification, especially with moderately familiar products, with prolonged background observation indicating difficulty in function comprehension. Higher product specification from virtual to physical forms enhances function identification and evaluation, though this effect is lessened by unfamiliarity.

Keywords: contextual factors , familiarity , human-product interaction , representation form , User experience

The widespread availability of Information and Communications Technology paradigms encourages people, especially older adults, to maintain independence in their daily activities, improving health and well-being. However, some elements of criticality can arise when trying to meet two worlds apart. The present work aims to discuss the main factors that affect older people's engagement with a user-centred software platform to increase people's awareness of the availability of services for social care and entertainment purposes. A mixed-method approach was defined to correlate the attitude towards technology, measured through the TechPH index, to the usability and user-experience outcomes. Despite the limited sample size, the findings of this preliminary study suggest that the use of technology is not associated with any increase in the stress level, since the initial perceived difficulty to learn and use the system decreased after some training. Moreover, education level, living conditions, age, gender and TechPH index do not affect the usability of the SW interface, rather it depends on the familiarity with the use of the smartphone, the perceived usefulness and the difficulty in using it.

Keywords: Human-Computer Interaction , Older Adults , Technology Use , Usability , User Experience

Technological development made vehicle safer thanks to the advanced driving assistance systems (ADAS). There exists passive systems, like ABS that boosts vehicle performance during an emergency braking, and active systems, like active cruise control that actively drives car during normal cruise. However, ADAS need to further evolve to continue the risk reduction and to increase automation level. Physiological sensing and deep learning are promising options at these regards. This paper will present a methodology to estimate the driver drowsiness from photoplethysmography (PPG) waveform, acquired by no-invasive probe embedded in the vehicle steering wheel. PPG signal is treated using the innovative hyper-filtering process, then it is elaborated by a convolutional deep architecture. A driver sample, made by 70 people distributed by gender and age, was selected to validate the approach, monitoring PPG and confirming the actual level of drowsiness by electroencephalography. The proposed network makes a classification task to distinguish a wakeful drive from a drowsy one. The developed method has an accuracy of 99%, which were higher than other networks considered for the benchmark.

Keywords: ADAS , automotive physio-sensing , Deep Learning

Hairdressers are exposed to various work-related risk factors due to prolonged awkward postures with repetitive movements. Although this problem is well documented in scientific literature, not much has been done to reduce and/or contain this problem. Therefore, the aim of this study is to contribute for this gap through the suggestion of guidelines or workplace modifications, to reduce MSD for hairdressers, during the shampoo task. The job-tasks of 25 shampoo assistants have been analysed regarding ergonomic risks and perceived discomfort. Shampoo assistants' postures were recorded and processed using Kinovea® software. To evaluate the ergonomic risk level, the RULA method was used, and an ad-hoc questionnaire was created to acquire Perceived Discomfort data. The analysis was supported by DELMIA® V5R16 software. Results showed that the neck and the back were the most critical body parts in terms of discomfort and ergonomic risk. Statistical analysis demonstrated a strong correlation between the body-size percentile and discomfort. As the percentile increased, the perceived overall discomfort increased. Based on the results, a virtual ergonomic-driven redesign was carried out.

Keywords: discomfort , Ergonomics Assessment , Hairdresser , Shampoo , WMSD

In the evolving landscape of driving training, the integration of technology has played a pivotal role in shaping educational methodologies and enhancing learning outcomes. Virtual training methods, which often rely on the use of monitors, have been the standard for decades. However, with the advent of augmented reality (AR), a new dimension of interactive and immersive training is emerging, promising to revolutionize the way driving skills are taught and acquired. This paper aims to explore and compare the effectiveness of virtual monitor-based training with the innovative use of augmented reality in driving simulations. The focus is on understanding how each method affects learning efficiency, user engagement, and the practical applicability of the skills acquired through these training modalities. Virtual monitor-based training systems are valued for their accessibility and cost-effectiveness, making them a prevalent choice in many training programs. On the other hand, augmented reality introduces a layer of interactive elements that overlay the real world or simulated environments, providing real-time feedback and enhancing situational awareness. This paper seeks to delineate the strengths and limitations of the AR-integrated driving training simulations. The goal is to provide insights into how virtual-based training can be optimized to enhance the safety, efficiency, and effectiveness of driving education, ultimately contributing to better-prepare drivers in their driving performances.

Keywords: Augmented Reality , Driving Simulator , User Experience

An Active Noise Control method is presented for selectively reducing the harmonic content of an ambulance siren. The aim is to implement such a system on the headrest of an ambulance to reduce noise exposure for the driver. Based on the FxNLMS feedforward algorithm, two developments are presented: 1) Reference Synthesis, for those cases where the noise to be cancelled is perfectly known, it is demonstrated that the reference signal can be generated by the cancelling hardware, without the need to employ reference microphones nor connecting to the noise source; 2) Switching FxNLMS, the implementation of separate banks of adaptive filters is presented to individually cancel two alternating components of a bitonal siren, as if they were two independent stationary noises. Demonstrations of the working principles are presented through tests carried out with a synthesised version of the real siren as a noise source, and real-time target hardware mounted on a headrest, in laboratory environment.

Keywords: Active Noise Control ANC , Ambulance Siren Noise , Feedforward FxNLMS Algorithm , Real-time Hardware Test , Reference Synthesis , Switching FxNLMS

Remote driving, i.e., the capacity of controlling road vehicles at a distance, is an innovative transportation technology often associated with potential ethical benefits, especially when deployed to tackle urban traffic issues. However, prospected benefits could only be reaped if remote driving can be executed in a safe and responsible way. This paper builds on notions elaborated in the philosophical literature on technological mediation to offer a systematic examination of the extent to which current and emerging Human–Machine Interfaces contribute to hindering or supporting the exercise of responsibility behind the remote wheel. More specifically, the analysis discusses how video, audio, and haptic interfaces co-shape the remote driving experience and, at the same time, the operators' capacity to drive responsibly.

Keywords: human–machine interaction , interface design , remote driving , responsibility , safety , technological mediation

Recently, most research efforts and resourced in Aeronautics are devoted to the development of Advanced Air Mobility (AAM) technologies. This term refers to all air mobility services based on autonomy and electrification of air systems and their infrastructure and when conducted in urban contexts is known as Urban Air Mobility (UAM). However, the integration of these systems and what is their environmental, social and economic impact is still unknown and such ignorance may decelerate its effective implementation and thus enjoyment of the benefits. In this context, visualization and interaction technologies such as Extended Reality Technologies (XR) can be leveraged as enabling technologies aiding in the deployment of AAM and UAM. In this paper, we present an overview of methodologies for designing human-machine interfaces in aeronautics and the results of a study of tools and methods for prototyping virtual urban environments for XR-UAM applications.

Keywords: Human Machine Interfaces , UAM - Urban Air Mobility , XR – Extended Reality

Industry 5.0 emphasizes human-centric approaches in technological advancement, particularly crucial in healthcare applications such as prosthetics development. While individual technologies like additive manufacturing, machine learning, digital twins, and tissue engineering have shown promise in prosthetics innovation, their integration remains a significant challenge. This paper presents a novel multidisciplinary framework developed through the National Centre for High-Performance Computing (CN-HPC) project, which addresses the gap between individual technological capabilities and their coordinated application in personalized prosthetics development. The framework, implemented through collaboration between six research groups from two universities, employs the House of Quality methodology to align technological integration with patient needs. Our approach encompasses a comprehensive seven-step process, from initial patient requirements definition through virtual modeling, production process optimization, virtual sensing, machine learning enhancement, digital twin simulation, to advanced tissue engineering. A data model facilitates seamless information exchange between different technological domains and research groups. This research contributes to the field by providing a scalable, human-centered framework for technology integration in medical device development, potentially extending beyond prosthetics to other healthcare applications. The proposed framework represents a significant step toward realizing the full potential of Industry 5.

Keywords: Healthcare , House of Quality , Human-Centricity , Industry 5.0 , Prosthesis

This paper aims to provide an updated overview about the Human Pose Estimation (HPE), which is a typical Computer Vision-related problem. The review firstly analyzes the importance of the research topic, both in terms of number of publications and application fields. Thanks to the introduction of efficient machine learning techniques, nowadays HPE is feasible without the necessity of specialized and expensive instrumentations. The proposed review considers only the works based on the use of Machine Learning techniques, and it is divided in two parts: an analysis of methodologies presented for the 2D HPE and a similar one for the 3D HPE. Being this last generally approached as an extension of the 2D HPE, the Authors propose a section discussing the effective validity of the most diffused and open source 2D HPE methodologies.

Keywords: Computer Vision , Human Pose Estimation , Human Posture , Movement analysis

Despite the European Union's efforts to decrease workplace accidents, statistics show an increase in accidents in the last years. Therefore, training workers is crucial to prevent injuries. The thriving of new technologies, such as Immersive Virtual Reality, can offer innovative training methods in the industrial field. However, introducing innovative technologies to a user base with an increasing average age necessitates evaluating the impact on workers across various age groups. In this contribution, we developed an IVR system to train workers to learn procedures in industrial environments. We recruited 50 participants and divided them into three age groups: young (19–33 years), middle-aged (34–48 years), and older (49–63 years). Objective (execution errors and times) and subjective metrics (User Experience Questionnaire (UEQ), System Usability Scale (SUS), and Virtual Reality Sickness Questionnaire (VRSQ)) were collected. The results showed that the young group made more mistakes than the other two groups, but there were no statistically significant differences in execution times. The SUS score was statistically significantly higher for the young group than the others, the VRSQ did not show any significant increase.

Keywords: Age-related Performance , Immersive Virtual Reality (IVR) , Industrial Safety Training , User Experience Metrics , Workplace Accident Prevention

The industrial revolutions driven by Industry 4.0 and 5.0 are transforming work practices with new tools like Augmented Reality (AR), which promise to boost productivity in industrial settings. This study introduces an AR application for the HoloLens 2 to evaluate three interaction metaphors - hand-ray, near, and gaze interaction - for moving virtual objects, focusing on accuracy and ergonomics. ErgoSentinel software provided real-time ergonomic analysis through RULA scores, and the NASA-TLX questionnaire assessed perceived workload. Results indicate that ray interaction is the most ergonomically favorable for long-distance tasks, reducing physical strain and enhancing comfort. Near interaction is precise for short-distance tasks but increases physical strain over long distances. Gaze interaction balances physical strain reduction with potential precision loss in long-distance tasks, imposing a higher cognitive load.

Keywords: Augmented Reality , Ergonomics , Industry 5.0 , RULA

Modern design products are increasingly complex and emotionally significant, demanding versatile and collaborative customization. However, a literature and commercial review reveals a limited availability of flexible, multi-user, photorealistic Virtual Reality (VR) systems for product configuration. We introduce MAGIC (Multi-user Advanced Graphic Immersive Configurator), a collaborative platform combining realistic graphics with ergonomic validation using digital avatars, addressing the limitations of 2D visualization and existing tools. MAGIC is evaluated in a yacht design case study involving 30 participants in an immersive, co-located configuration of a sailing yacht to assess the system's usability and the potential of VR for customizing complex products. Results show MAGIC's feasibility in supporting multi-user configuration (100% success rate) and achieving a strong usability score (SUS = 80.83). User feedback highlights that high-quality graphics and additional content significantly enhance immersion and user engagement. However, encountered challenges with navigation methods and spatial perception indicate areas for improvement. MAGIC's collaborative and immersive capabilities can be extended to other industries demanding proactive customer engagement in the customization of large, heavy products and ergonomic design.

Keywords: collaboration , marine industry , multi-user , product configuration , virtual reality , yacht design

This paper presents a method for designing a customized ergonomic office chair backrest aimed at improving user posture and long-term health. Given the importance of ergonomics in workplace settings, this study leverages 3D scanning and additive manufacturing to create personalized cushions that conform precisely to individual anatomical shapes, aligning with ergonomic standards. The process begins with high-resolution scans of both the user's back and a standard chair backrest, followed by cushion modeling in Blender to ensure exact fit and support. Additive manufacturing was selected for cushion fabrication, using a TPU material with an optimized internal structure to enhance comfort. Results indicate a notable improvement in posture alignment and comfort, verified through comparative scans before and after customization. The custom backrest also encourages proper posture through a postural retraining effect and provides a high level of hygiene due to its non-porous material.

Keywords: Additive manufacturing , Custom cushion , Ergonomic chair

This paper presents an integrated approach that combines Industrial Design Structure (IDeS) methodology with Human-Centered techniques to optimize the safety and comfort of hybrid sports vehicles. The study begins with an in-depth analysis of styling trends and then moves on to custom 2D and 3D modeling. A unique method employing calibrated dummies allows customization of the dimensions of the passenger compartment, prioritizing ergonomic features. It has been observed that this approach improves vehicle aesthetics and ensures optimal ergonomic design while prioritizing occupant safety and comfort.

Keywords: Car Design , Ergonomics , Human-Centered Design

The rise of the Metaverse is anticipated to extend the duration of time individuals spend within virtual indoor environments, potentially affecting human well-being. The hype generated by the launch of Apple Vision Pro has increasingly spread the idea of using virtual platforms as a workspace. Our research explores the idea of applying biophilic environmental design within the Metaverse, hence our definition: Metagreenverse. The biophilia hypothesis suggests that humans have an innate tendency to seek connections with the natural world and there is increasing evidence that biophilia can yield health benefits. In this preliminary study, we designed a metaverse office enriched with biophilic elements and investigated how the plants can affect the user experience of 24 participants compared to the same office without biophilic elements. We evaluated the user experience by submitting the User Experience Questionnaire (UEQ), the user emotional response with State-Trait Anxiety Inventory (STAI) questionnaire, the realism of the virtual office with Slater-Usoh-Steed (SUS) test, and the perception time. We found that the integration of biophilic elements into a metaverse workspace influences positively the users' experience.

Keywords: Biophilic Design , Metaverse , Virtual Reality , Well-being , Workspace

Extended Reality (XR) refers to technologies that allow linking virtual and real worlds and include, in a broad sense, Virtual (VR), Augmented (AR), or Mixed (MR) Reality. The interest in XR is increasing mainly in training operations; however, it is important to consider that XR techniques could sacrifice realism and could require high costs to reproduce real environments. The present study addresses this problem and aims to experimentally test how the level of realism can be implemented and increased in practice and how different levels of realism impact the user experience. A framework for the reconstruction of 3D scenes using photogrammetry is proposed and an experimental campaign is presented to understand the user experience of an XR application, with particular attention given to participants' feedback about the level of realism of the virtual scenario. The focus of the research is to outline the improvement of the virtual experience owed to the photogrammetric reconstruction. Participants were asked to give their opinions on the comparison between the reconstructed 3D environment and a conventional shaded virtual environment made up of 3D CAD models. This paper contributes to the still limited empirical debate about the implementation of different levels of realism in virtual applications and its impact on participants' experience. Results show that participants appreciated the photogrammetric reconstructed realistic scenario, proving that realistic scenes can improve the user experience.

Keywords: 3D modeling , experimental campaign , photogrammetry , questionnaire , realism , user experience , virtual reality

It is crucial to prioritize the prevention of work-related musculoskeletal disorders within manufacturing contexts. However, traditional approaches to ergonomic risk assessment often lack efficiency, and objectivity, and are time-consuming. This study focuses on the use of wearable sensors to improve ergonomic risk evaluation. By leveraging this approach, the automatic calculation of ergonomic risk indices across various standard methodologies becomes feasible. The process integrates data from Xsens, Manus gloves, an electromyography system, and traditional measuring tools ensuring comprehensive evaluation. The procedures for calculating ergonomic risk indices according to several standard methods (e.g., RULA, OCRA, and NIOSH) are presented. Continuous monitoring of worker activities and streamlined analysis processes result in notable enhancements in accuracy, reduction of assessment time, and mitigation of potential biases associated with manual observation. Industrial experiments conducted to validate the effectiveness of the proposed method underscore its ability to objectively evaluate physical ergonomic risks.

Keywords: Ergonomic assessment , Inertial motion capture , OCRA , REBA , Work-related musculoskeletal disorders

Work-related musculoskeletal disorders are a pressing public health issue, affecting workers across diverse sectors. Among these, municipal waste collection stands out due to the inherent risks associated with the tasks performed by waste collectors. The adoption of door-to-door waste collection methods, aimed at improving waste sorting rates, has unveiled health and safety concerns related to frequent lifting of small containers from the ground to the truck container. This study delves into the ergonomic challenges encountered by waste collection operators during door-to-door waste collection, utilizing a sensor-based methodology to characterize and quantify these challenges objectively. This research represents one of the few attempts to employ motion capture systems in outdoor work settings to capture operators' movements, derive joint angles, and calculate ergonomic risk indices using methods like REBA and NIOSH. The findings provide valuable insights for devising strategies to mitigate risks. Key recommendations include restricting lifting activities to below shoulder height, elevating collection points, enhancing waste bag grip quality, and promoting adherence to ergonomic guidelines by operators.

Keywords: Ergonomics , Motion capture system , Musculoskeletal disorders , Occupational risks , Waste collection

Maintenance operators usually face complex challenges due to the complexity of modern sophisticated machinery and systems. Only highly experienced operators may have sufficient skills to perform recovery procedures properly and quickly; frequently, not expert operators need for assistance from the manufacturer's after-sales. Therefore, very long recovery times, high maintenance costs, and temporary drop in production take place. In this context, augmented reality (AR) can offer valid support to non-expert operators involved in maintenance activities. In this work, a framework based on user experience (UX) design approach was developed for designing highly usable AR applications to guide operators in performing maintenance procedures safely and efficiently. The proposed framework has been applied to the H2020 European project titled “XMANAI – Explainable Manufacturing Artificial Intelligence”. Results showed that the application developed is suitable to assist not expert operators, preventing them from making mistakes, leading to the upskill and increased productivity for the company.

Keywords: augmented reality , Industry 5.0 , Operator 4.0 , transdisciplinary engineering , user experience design