Human factors and ergonomics

Background: Adherence to home-based respiratory rehabilitation is a significant challenge for cardiac surgery patients. Few studies have attempted to address this problem. Methods: This research introduces a digital solution to improve adherence to respiratory rehabilitation by offering virtual supervision. It leverages the YOLOv11 pose detection algorithm to track the Voldyne® 2500 incentive spirometer and monitor rehabilitation sessions. Usability and accuracy were evaluated with nine healthy volunteers, combining objective performance metrics with the System Usability Scale (SUS) survey. Results: The models demonstrated high accuracy in spirometer tracking and efficient inference times. The app achieved an average SUS score of 83%, indicating good usability, though refinements to the monitoring algorithms are recommended. Conclusion: This low-cost, non-invasive solution shows potential for clinical use. Future efforts will focus on enhancing usability and accuracy to prepare the app for clinical trials.

Keywords: Cardiac Rehabilitation , Respiratory Therapies , Spirometry , YOLO Network

Extended reality (XR) technologies are no longer peripheral innovations but emerging cornerstones of human–technology interaction across critical sectors. This article takes the position that engineering and healthcare represent the most mature and strategically relevant domains for XR adoption, given their safety-critical nature, intensive training requirements, and strong alignment with the human-centric visions of Industry 5.0 and Healthcare 5.0. We synthesize evidence from product design, manufacturing, training, and patient care to demonstrate how XR is reshaping workflows, skills, and therapeutic practices. Beyond surveying applications, we argue that the future of XR depends on its integration with artificial intelligence, digital twins, and multisensory feedback, converging into systems capable of perceiving, reasoning, and adapting to complex physical and human environments. We contend that widespread adoption will remain limited without open standards, validated protocols, and robust evaluation frameworks addressing safety, interoperability, and data governance. By framing XR as both a technological enabler and a societal imperative, this position article calls for coordinated action among researchers, practitioners, and policymakers to realize XR's role in building sustainable, personalized, and participatory innovation ecosystems.

Keywords: digital industry , extended reality , human-centered innovation , human–computer interfaces/interactions , immersive technology , virtual and augmented reality environments , virtual prototyping , XR for training , XR in healthcare , XR in manufacturing

Hyper-redundant manipulators offer high dexterity and manoeuvrability in constrained environments, yet their design must integrate structural efficiency with environmental adaptability. This study presents a co-design framework for lightweight, cable-driven hyper-redundant manipulators optimised for underwater applications, such as the usage in combination with a Remotely Operated Vehicle. Building on a modular architecture of an eight-degree-of-freedom cable-driven manipulator, the methodology integrates Gaussian process regression-based stress prediction and generative design to achieve mass and size reductions, as well as a hydrodynamically efficient shape while ensuring structural integrity under extreme static loads. A 3D-printed module fabricated from Onyx, a carbon fibre-reinforced nylon, achieved near-neutral buoyancy in seawater, validated through submerged testing of a two-module prototype. An external buoyant element design was then provided for manipulators with no inherent buoyancy, accounting for printability, density mismatch between actual and theoretical density, and joint range of motion. This work advances underwater hyper-redundant robot design by combining data-driven optimisation with modular buoyancy strategies and hydrodynamic efficiency, providing a scalable method for fluid environments.

Keywords: Cable-driven , Design , Hyper-redundant , Manipulator , Optimisation , Robot , Underwater

Industrial Robots (IRs) are typically employed as flexible machines to perform many types of repetitive and intensive tasks within fenced safe areas, ensuring high productivity and cost efficiency. However, their rigid programming approaches often pose challenges during cell commissioning and reset, hindering the implementation of self-reconfigurable systems. In addition, several production lines still need the presence of skilled operators to conduct assisted assembly operations and inspections. This motivates the growing interest in the development of innovative solutions for supporting safe and efficient human–robot collaborative applications. The manual guidance of the IR end-effector is a representative functionality of such collaboration, as it simplifies heavy-part manipulation and allows intuitive robot teaching and programming. The present study reports a sensor-based approach for enabling manual guidance operations with high-payload IRs and discusses its practical implementation on a production cell with an extended workspace. The setup features a KUKA robot mounted on a custom linear track actuated via Beckhoff technology to enable flexible assembly and machining operations. The developed logic and its software configuration, split into multiple control units to allow the manual guiding of both the 6-axis IR and the linear track unit, are described in detail. Finally, an experimental demonstration involving two users with different levels of expertise was conducted to evaluate the approach during target teaching on a physical cell. The results showed that the proposed manual guidance method significantly reduced task completion time by more than 55% compared with the conventional teach pendant, demonstrating the effectiveness and practical advantages of the developed framework.

Keywords: collaborative manufacturing , human–robot interaction , industrial robot , linear track , manual guiding

The future of space exploration relies not only on technological advancements but also on public awareness and policy support. Sustaining long-term investments in lunar and planetary missions requires effectively engaging both the next generation and key decision-makers. However, traditional science communication methods often fail to reach audiences beyond academic and professional circles, limiting public engagement. Virtual Reality and Serious Games offer interactive and immersive experiences that make complex scientific concepts more accessible to non-experts, fostering broader support for space exploration initiatives. This study evaluates the effectiveness of a Virtual Reality Serious Game designed to simulate the Lunar Zebro rover navigating the Moon's surface. The game aims to enhance engagement, simplify scientific concepts, and shape public perception of space missions. Through iterative development and user testing, the study examines the balance between education and entertainment. Preliminary findings indicate that while the game successfully engages users and communicates mission objectives, it is primarily perceived as an interactive experience rather than a standalone educational tool. These insights highlight the potential of VR Serious Games in science communication and their role in promoting future space exploration initiatives.

Keywords: Serious Game , User Experience , Virtual Reality

This study presents the development of a prototype anthropomorphic soft robotic gripper intended for applications in rehabilitation and assistive robotics, where safe and adaptive interaction with humans is required. The device consists of three elastomeric fingers, fabricated in TPU via FFF 3D printing and actuated through pneumatic soft actuators that ensure compliant contact with both biological tissue and rigid objects. A custom 3D-printed pneumatic rotary actuator enables finger reconfiguration, thereby extending the range of grasping modalities. The actuation system comprises six 2/2 solenoid valves controlled by an Arduino Uno and integrated into a dedicated pneumatic circuit. Experimental characterization demonstrated a peak grasping force exceeding 17 N on rigid targets, while functional tests in table-picking scenarios confirmed adaptability to objects of varying shapes and sizes. Owing to its anthropomorphic configuration, mechanical compliance, and ease of fabrication and control, the proposed gripper represents a versatile solution for rehabilitation-oriented devices as well as assistive robotic end-effectors in pick-and-place tasks.

Keywords: additive manufacturing , assistive robotics , pneumatic , rehabilitation , soft actuator , soft gripper

The miniaturization and integration of micro-electromechanical systems (MEMS) have progressively expanded the capabilities of advanced prosthetic hands, enabling not only the replication of human sensory and motor functions but also the implementation of sophisticated mechatronic control, precise manipulation, and adaptive responses to environmental interactions. The aim of this scoping review is to systematically map and evaluate current research on MEMS-integrated prosthetic hands, highlighting how MEMS sensors and mechanical modelling approaches contribute to dynamic control, biomechanical performance and user-centered functionality. Comparative analyses of different modelling techniques and MEMS applications indicate that MEMS-based sensing systems substantially improve the mechanical performance of prosthetic hands by enabling accurate force modulation, enhancing motion stability during dynamic tasks and supporting efficient signal acquisition for real-time control. These features lead to more precise control, smoother movements and enhanced dexterity during activities of daily living (ADL), broadening the functional capabilities of the devices. Microsurgical and neural interface aspects were also examined, including physiological considerations relevant to neural integration and common challenges related to prosthetic implantation, such as potential immunological responses to materials. The increasing role of MEMS in the development of smart, biomimetic prosthetic hands underscores new opportunities for creating highly adaptive devices, optimizing dexterity and environmental interaction and ultimately improving users' quality of life.

Keywords: biomechanical modelling , dynamic control , mechatronic systems , MEMS sensors , prosthetic hand , smart hand prosthesis , smart MEMS

Automotive seat comfort is a critical factor in enhancing driver satisfaction, especially in sports cars, where design must balance comfort features and performance-oriented features like lateral containment and anti-submarining. This study adopts an empirical-analytical approach for assessing and modelling perceived comfort in sports car seats using both objective and subjective data. A total of 64 participants (50 males, 14 females) evaluated two types of sports car seats—a road model (SEAT A) and a racing model (SEAT B)—during 15-min driving simulations using a dynamic simulator equipped with a full-body pressure mat (XSENSOR X3 PRO). Comfort was assessed through a postural comfort questionnaire using 10-point Likert scales. Statistical analysis revealed significant correlations between anthropometry, pressure distribution, and perceived comfort. In light of the correlation analysis, regression models were developed for four anthropometric percentile clusters (0–25th, 25–50th, 50–75th, 75–100th). Models were validated (accuracy > 75%) and one of them (named Model III) achieved accuracies of 95%, 96%, 90%, and 97% for its percentile clusters. The proposed models offer actionable insights for tailoring sports car seats to different user percentiles, enabling more personalized and effective seat designs that enhance both performance and comfort.

Keywords: comfort assessment method , human seat interaction , pressure distribution , sports car seats

Background: This study investigated the biomechanical and physiological demands of the hiking position in Laser sailing, a posture requiring sailors to extend their upper bodies outside the boat to counter wind-induced heeling. This study utilized a mixed-methods approach. Methods: Twenty-two experienced Laser sailors participated in both on-land and offshore assessments. The study combined subjective discomfort ratings, biomechanical measurements, digital human modeling, and muscle activation analysis to evaluate the effects of hiking during and after exertion. Results: A two-way ANOVA showed significant effects by body region and time. The quadriceps, abdominals, and lower back reported the highest discomfort. Key postural angles were identified, including knee and hip flexion, trunk inclination, and ankle dorsiflexion. Muscle activation analysis revealed the highest engagement in the rectus abdominis (46.1% MVC), brachialis (~45%), and psoas major (~41%), with notable bilateral asymmetries. The trunk region had the highest overall activation (28.7% MVC), followed by the upper limbs (~18.7%), while the lower limbs were minimally engaged during static hiking. Conclusions: On-water conditions resulted in greater variability in joint angles, likely reflecting wind fluctuations and wave-induced boat motion. Findings highlight the quadriceps, abdominals, and lower back as primary contributors to sustained hiking, while also emphasizing the importance of targeted endurance training and ergonomic equipment design. These insights can guide training, recovery, and ergonomic strategies to optimize performance and reduce injury risk in Laser sailors.

Keywords: biomechanics , digital human modeling , hiking , laser sailing , muscle fatigue , physical strain , postural discomfort

Digitalization represents a strategic enabler of innovation in industrial processes, particularly within complex and safety-critical domains. In the transition toward Industry 4.0, Augmented Reality (AR) demonstrates considerable potential to reshape work organization by enhancing efficiency and ensuring higher product quality. AR technologies can provide operators with context-aware instructions, interactive visual guidance, and improved operational control during cognitive and technically demanding tasks, such as electrical wiring assembly in the aerospace sector. To investigate the actual potential of video see-through devices, a dedicated AR application was developed for Meta Quest 3. The case study encompassed the digitization of technical documentation, the integration of three-dimensional models, and the design of an interactive User Interface (UI). The Usability of the application and its impact on Cognitive Load (CL) were assessed through controlled laboratory experiments involving two groups: one employing Meta Quest 3 and the other relying on conventional paper-based documentation. The results provide empirical evidence on the practical relevance and limitations of video see-through AR in supporting assembly operations. Specifically, the study revealed that the video see-through mode of Meta Quest 3 presents certain limitations and imposes a higher CL on users, although it also elicited high levels of user satisfaction regarding the use of AR technology. These results underscore the necessity of further optimizing AR hardware and interaction design to mitigate cognitive demands, while confirming the promising role of AR in advancing industrial training and assembly processes.

Keywords: Assistive technologies , Augmented reality , Ergonomics , Human factor , Usability assessment , Video see-through

Random goods inspections are a critical component of customs operations, ensuring that imported and exported goods comply with relevant regulations. Currently, these inspections rely on manual efforts by operators, making them susceptible to delays and increased costs, often attributed to \"human errors\". This paper shifts the narrative from “human errors” to “human factors”, emphasizing the role of cognitive and operational challenges in inspection tasks. We introduce “Virtual Storage Assistant”, a wearable Augmented Reality tool designed to enhance the efficiency and accuracy of customs inspections. By leveraging Augmented Reality, the proposed system aims to bridge the gap between: (1) the required performance standards for the inspection process, and (2) the specific cognitive abilities and skills of customs workers, thereby streamlining operations and reducing associated inefficiencies.

Keywords: Augmented reality , Cognitive ergonomics , Customs inspection , Human error , Human factors

The present work focuses on the use of Immersive Virtual Reality (IVR) to train users by immersing them in safe and controlled Virtual Environment (VE) and enabling them to learn by doing. Particular attention is given to adaptive VR-training systems that are capable of dynamically adjusting the training experience based on user's performance and cognitive state. Considering this, a new methodology for such systems is proposed, that is crafted on the Cognitive Theory of Multimedia Learning (CTML). This methodology aims to help instructors to understand how to adapt VR-training systems to users during their experience in VEs, leading to effective Learning Outcomes and avoiding a high Cognitive Load (CL). This human factor plays a critical role in mediating the relationship between Presence, Immersion, and Learning Outcomes, as the VE generates a CL to users. To have a deeper understanding, factors influencing CL in VEs are presented and relative solutions are proposed. It is our understanding that adaptive VR-training systems, their design, architecture, and attributes, can pave the way to new research directions and that the new methodology presented in this paper will be supportive.

Keywords: Adaptive VR-training system , Cognitive load , Human factors , Learning outcomes , Virtual reality

In response to the global concern over road traffic accidents, particularly among young drivers, there is increasing interest in innovative educational interventions to promote safer driving behaviors. Traditional media campaigns often fail to engage audiences meaningfully. This study, part of a broader research initiative, investigates the effects of Cinematic Virtual Reality (CVR) on participants' physiological responses, specifically focusing on heart rate variability, to assess the effectiveness of fear-based and positive reinforcement scenarios influencing road safety behaviors. A custom-developed CVR application delivered immersive 360° driving scenarios, one based on fear and the other on positive reinforcement, via a Meta Quest 2 headset. A total of 95 participants, aged 18 to 24 and all holding valid driver's licenses, were randomly assigned to one of the two experimental conditions. The study assessed the impact of these approaches on participants' physiological responses by recording electrocardiogram (ECG) data using the BioSignalPlux system. HRV parameters, indicators of stress and arousal, were analyzed to distinguish the physiological effects of the two scenarios. Time-domain, frequency-domain, and nonlinear HRV features were extracted and used for classification. Machine learning algorithms were employed to evaluate the system's performance in differentiating between the two experimental groups. The classification accuracy, sensitivity, and specificity were assessed using 10-fold cross-validation. Results showed that Linear Discriminant Analysis (LDA) achieved the highest classification accuracy.

Keywords: Cinematic Virtual Reality , Machine Learning Approach , Physiological Parameters

This study investigates how the optimal driving position is shaped by the forces acting on the driver and the performance requirements of an FSAE vehicle. Using a comprehensive dataset based on a parametric model, key SAE-standardized input variables are parameterized: the horizontal and vertical coordinates of the H-point, the horizontal distance between the AHP and H-point, the seatback angle, and the steering wheel position. The objective is to identify the ideal driving setup that balances vehicle performance with driver comfort. ANOVA is utilized to determine which of these ergonomic factors most significantly affect acceleration performance, while artificial neural networks provide a comparative method for validating results and predicting outcomes for new configurations. The novelty of this study lies in integrating driver positioning dynamics into performance optimization, providing a systematic approach to vehicle design before the CAD prototyping phase.

Keywords: ANOVA , ergonomics optimization , neural networks , product architecture , Vehicle dynamic

Due to the growing adoption of Immersive Virtual Reality (IVR) in various contexts, understanding how virtual workspaces impact humans and how they should be designed is crucial. Exploring optimal design strategies that can enhance well-being within IVR environments becomes important. In real contexts, biophilic design offers a way to improve well-being by introducing natural elements. IVR can go beyond real-world constraints for integrating biophilic elements, but this aspect is scarcely addressed in literature. A valuable assistance to support the design of IVR workspaces could be offered by generative Artificial Intelligence (AI), which is becoming increasingly integrated into everyday life. The aim of this work is twofold: (i) assessing if the biophilic design of IVR workspaces can improve human well-being and (ii) investigating if AI can inspire the biophilic design properly. Thus, we conducted a user study comparing psycho-physiological and subjective metrics in three conditions. A workspace without biophilia was used as a baseline. The same was enriched with two biophilic designs: one suggested by expert designers and another inspired by AI-generated graphics, simulating a not-expert developer. The findings showed that both biophilic designs significantly improved well-being; however, AI suggestions led to a reduced sense of presence in the IVR environment.

Keywords: Biophilic Design , generative artificial intelligence , industry 5.0 , Virtual Reality , well-being

Spatial audio systems have received nowadays great attention not only from the academic sector but also from the market. Many techniques have been studied for the creation of an immersive scenario, but the development of a large zone, where more than one listener can perceive an immersive audio experience, is based on the use of multichannel approaches and sound field technologies. In this context, the presented study aims at an objective analysis of the listeners' sound experience based on their physiological responses and facial expressions to recognize variations in the subject mental and physical status and in their emotional reactions. Several experiments have been conducted using an immersive loudspeakers sphere installed in a semi-anechoic chamber exploiting Ambisonics technology and monitoring the listeners with a camera-based system equipped with a Facial Coding (FAC) and an advanced multimodal acquisition system to measure different physiological signals.

Keywords: facial coding , immersive audio , physiological monitoring , spatial sound

Immersive audio techniques can create realistic sound environments in the same way humans perceive sound in a natural one. This capability can be applied to car cabin environment to enhance the user's experience and improve the vehicle-driver interaction. In this scenario, our study is focused on the effects these systems have on the driver's experience in terms of emotional responsiveness and degree of immersion. The spatial audio system is realized with a modified version of Recursive Ambiophonic Crosstalk Cancellation and a deep analysis is performed with a real-time monitoring achieved by the implementation of a multimodal approach that exploits deep learning and data fusion techniques to ensure a comprehensive evaluation of the driver's status. Several experimental results are reported by means of a driving simulator equipped with a camera-based driver monitoring system and a physiological acquisition system.

Keywords: automotive audio , driver monitoring system , immersive audio

The prevention of work-related musculoskeletal disorders (WRMSDs) is a critical priority in the transition to Industry 5.0, which emphasizes human-centric, resilient, and sustainable industrial practices. Observational methods commonly used to assess ergonomic risks in the workplace often fall short due to inefficiency, subjectivity, and time-consuming procedures. These traditional approaches typically require ergonomists to estimate critical parameters, such as joint angles or task repetition rates, based on visual observation or video analysis, which can introduce potential biases and inconsistencies. This study proposes a novel framework that leverages wearable sensor technologies to automate and enhance the ergonomic risk assessment process. By integrating data from motion capture systems, mocap gloves, electromyography sensors, and other devices, the approach provides precise, real-time measurements while minimizing the need for manual input to only well-known parameters. The manuscript includes a comprehensive mapping of parameters that can be automatically collected based on recognized standards (e.g., RULA, OCRA, and NIOSH) and outlines the associated computational complexity. Ergonomic indices are generated automatically, ensuring consistent and objective evaluations. The performance of the sensor-based process is evaluated through multiple case studies, comparing it with traditional methods. While the potential of sensor-based approaches to deliver more objective and reliable ergonomic risk assessments is widely acknowledged, this work specifically examines their feasibility for automation and quantifies the benefits in terms of process efficiency. The proposed methodology not only supports the accurate identification of ergonomic risks but also empowers a proactive, worker-focused strategy for occupational health.

Keywords: Ergonomic assessment , Human-centric , Industry 5.0 , Wearable sensors , Work-related musculoskeletal disorders

The total quantity of food waste in Europe has been estimated at around 88 million tons per year. About 42 % is thrown out by households, of which 60 % would be avoidable by increasing users' awareness. The present paper aims to develop an integrated system to reduce household food waste and improve the end-users' lifestyle in terms of health and well-being. A smart fridge able to track the stocks, a web application and a set of related services have been designed and prototyped to guide the user in the proper storage of food and support him/her in purchase planning and food preparation. The system was positively evaluated in terms of usability, it is use contributes to both environmental and economic benefits, leading respectively to a reduction of environmental impacts of about 21 % and a yearly savings amounting up to 285 €, in comparison with a traditional system.

Keywords: environmental sustainability , household food waste , smart fridge

Industry 5.0 (I5.0) emphasizes the importance of humans in modern manufacturing, particularly the need for efficient human-machine interaction. However, current design processes often neglect human factors in the early stages of machine design. Despite the growing recognition of human-centered design (HCD), existing methodologies still lack integrated solutions that fully leverage digital technologies for usability testing in industrial machines. As a result, traditional design and testing approaches remain rigid, limiting the potential of simulation in capturing complex human-machine interactions. This forces designers to rely on incomplete data, often leading to machines optimized for performance but lacking the usability needed for seamless human operation. This paper presents an innovative system that integrates humans into the design phase through two interconnected applications: a Virtual Reality (VR) application, where it is possible to interact with the machine digital model, and a desktop application that mimics the human-machine interface (HMI) to simulate operations on the machine. The two applications are synchronized and allow real-time interaction between the HMI and the virtual machine, enabling a human-centric virtual commissioning and testing of procedures that involve both the physical machine and the HMI. This approach enables iterative refinements before physical prototyping, reducing development costs while enhancing operational efficiency. By combining immersive engagement with the virtual machine and HMI simulation, it facilitates iterative refinements before physical prototyping, optimizing human-machine interaction and ensuring user-centered solutions. The industrial case study demonstrates the potential benefits of the proposed toolkit to optimize machine design according to I5.0 principles, improving both safety and usability.

Keywords: Human-Centered design , Human-Machine interaction (HMI) , Industry 5.0 , Machine design optimization , Virtual commissioning , Virtual reality