Background
A quantitative comfort model will aid in evaluating comfort levels of various target groups before the actual flight of an airplane. However, constructing the model is always a challenge due to the complexity of the phenomenon.

Objectives
In this paper, we present quantitative comfort models to predict the (dis)comfort of passengers flying with turboprops based on objective measures.

Methods
Ninety-seven participants took part in two experiments conducted during real flights, during which forty of them had environmental and personal factors recorded using (self-developed) measurement tools. The collected data were analyzed to model the relations between objective measures and subjective feelings.

Results
Two preliminary models based on gradient boosting regression were developed. The models were able to predict the changes in comfort and discomfort of individual passengers with an accuracy of 0.12±0.01 and 0.21±0.01 regarding normalized comfort and discomfort scores, respectively. Additionally, contributions of different factors were highlighted.

Conclusion
The outcomes of the models show that we took a step forward in modeling the human comfort experience using objective measurements. Anthropometry (including age), seat positions, time duration, and row (noise) emerged as leading factors influencing the feeling of (dis)comfort in turboprop planes.

Comfort is a pivotal construct in human-centered design, connecting technical functionality with well-being across products, services, and systems. The 2023 International Comfort Congress (ICC2023) brought together researchers and practitioners to explore how new contexts of use, predictive approaches, and user diversity are reshaping this field. Contributions in this special issue address comfort in automated driving and turboprop aviation, where physical, psychological, and environmental factors converge. Advances in predictive comfort science demonstrate how objective measures, physiological sensing, and modeling complement traditional self-reports. At the same time, inclusive design approaches—ranging from XR-based co-creation to analyses of posture and movement variability—highlight the importance of accounting for heterogeneous user needs and comfort trade-offs. Together, these studies illustrate a shift toward more adaptive, accessible, and sustainable systems, underscoring comfort as a multidimensional construct that evolves with technological innovation and societal change.

As automated vehicles evolve, seating designs must accommodate a wider range of postures, particularly for non-driving-related activities such as relaxing and sleeping. This study aims to model human back shapes in seated and reclined positions to improve ergonomic seat designs. Human back contour data were collected from 36 participants using a custom measurement device in two setups: a 25° backrest angle and a seat pan angle of 15°, simulating a driving posture, and a 50° backrest angle with the same seat pan angle, representing a reclined posture. Statistical Shape Models (SSMs) were developed to analyze the variability of back contours. The 25° setup exhibited a flatter spinal curve and higher compactness, capturing 79.7 % of the variance with the first principal component (PC1), compared to 74.6 % in the 50° setup. The combined setup balanced these differences, providing a comprehensive model for diverse postures. Overall, PC1, PC2, and PC3 together captured more than 96 % of total contour variance, indicating that variations in back height, neck bending, and lumbar prominence constitute the dominant sources of geometric diversity. These findings offer actionable dimensions for designing ergonomic backrests that support diverse users and postures. Future research should investigate whether implementing these guidelines enhances comfort and should include more diverse populations and a broader range of postures.

Co-creation has become increasingly important as companies strive to develop more customer-centric products and services by involving stakeholders throughout the design process. This paper introduces XR-CO, a multi-sensory, multi-user mixed reality co-creation platform. XR-CO utilizes an optical see-through head mounted display to create a 1:1 immersive mixed reality environment over essential physical prototypes, allowing stakeholders to physically interact with functional prototypes inside the digital environment. By incorporating visual, auditory, somatosensory and vestibular senses, XR-CO maximizes collaboration and triggers meaningful interactions among stakeholders, leading to improved co-creation quality. To validate XR-CO’s effectiveness, a study was conducted involving 32 participants in co-creation sessions for the development of cabin interiors of a new concept aircraft, the Flying-V. Half of the participants used XR-CO platform, while another half used the conventional desktop co-creation setups. The participants appreciated the XR-CO platforms, as indicated by their high scores in CSI, SUS, co-creation experience, and quantity of ideas in terms of quantitative data analysis. Additionally, 4D scanning of participants movements demonstrated that XR-CO provided a true-to-life perception of the digital space. XR-CO facilitated the discovery of more design issues compared to conventional setups, a finding affirmed by an expert panel using qualitative Delphi techniques. The positive user experience and meaningful outcomes observed in these co-creation sessions serve as strong evidence of the efficacy of the XR-CO platform, particularly the newly introduced somatosense. In summary, our study highlights the significance of XR-CO in co-creation processes. The platform’s immersive nature, combined with the integration of multiple sensory inputs, fosters collaboration, enriches interactions, and ultimately leads to improved outcomes.

Background
Current jet airplanes are not sustainable, and turboprop aircraft can be a more sustainable alternative for regional travels. However, the noise levels in turboprops can range from 83 to 92 dB(A), which is higher than jets and is the largest contributor to discomfort in turboprops.

Objective
The objective of this study was to assess the efficacy of utilizing noise-cancelling headphones or earplugs in mitigating (dis)comfort experienced by passengers aboard turboprop aircraft.

Methods
An experiment was designed in a grounded Boeing 737 cabin with the sound source inside. Twenty-four participants experienced four conditions: jet sound (Boeing 737), turboprop (ATR 72) sound, turboprop sound with active noise-cancelling (ANC) headphones, and turboprop sound with earplugs. The sound level used for all conditions in this test ranged between 84.2 and 86.3 dB(A). Passenger experiences were measured using questionnaires, including a newly developed Ear Local Discomfort questionnaire.

Results
The comfort and discomfort scores for the conditions involving ANC headphones and earplugs are significantly improved compared to the conditions without hearing protection. The impact of noise on discomfort is mitigated in these two conditions, though it remains the most prominent factor. ANC headphones cause more discomfort around the ear, while earplugs cause discomfort inside the ear.

Conclusion
The use of ANC headphones and earplugs in a turboprop airplane might increase the acceptance of these airplanes. ANC headphones are slightly preferred over earplugs, but both solutions have specific limitations.

To establish guidelines for sleeping space in vehicles, the sleeping postures of 189 participants are studied, 105 of them were asked to take the position in which they fall asleep and 84 have been asked to assume the position in which they lie most of the time. Seven percent slept on the stomach, 19% on the back and 74% on the side and 49% slept on the side with both legs flexed. For all participants a bed size of 200 × 90 cm will do. It is discussed that for one night while travelling a bed size of 171 × 76 cm might be sufficient as it results in a reasonably good sleep according to another study and in almost half of the cases in this study people sleep on the side with both legs folded. Apart from the sleeping space for a good sleep, attention is needed for a dark environment with a good temperature and relative silence.

Background
In recent years in-chair movements (ICM) have gained attention in comfort and discomfort studies, but the role of these movements in preventing and/or alleviating discomfort remains unclear. Furthermore, differences in study design and terminology make cross-study comparisons difficult.

Objective
This study aims to synthesize current research on ICM, particularly the categorization of different ICM types. It also aims to provide an overview of ICM over time, focusing on their progressions, characteristics, and possible patterns.

Methods
A systematic literature search was conducted based on the PRISMA framework using Scopus, PubMed, and Web of Science databases. Data from the included studies were extracted and organized according to three ICM descriptors: frequency, amplitude, and posture change.

Results
Eighteen out of 230 identified papers met the inclusion criteria. Substantial heterogeneity in terminology and measurement partly explains inconsistencies in findings. Across most studies, ICM frequency increased over time, although a minority reported decreased movement or a “stiffening effect”. Findings regarding ICM amplitude were inconsistent, while a shift or change toward more slumped posture appears to be especially common during driving activities. These variations suggest that ICM patterns are influenced by task demands, seat characteristics, and individual differences.

Conclusion
ICM patterns are not solely time-dependent but are shaped by seat characteristics, task demands, and individual factors. While several studies suggest correlations between ICM strategies and discomfort, the underlying mechanisms remain unclear. Developing a comprehensive ICM framework that integrates movement strategies, and active or dynamic seating approaches will benefit cross-study comparability and provide directions for future ICM research.

The comparatively environmentally friendly turboprop aircraft should be used more often, but still need some improvements, especially regarding noise. To facilitate research into these improvements, an On-Ground Regional Passenger Cabin Demonstrator was built and validated through a comparison with passengers’ reactions to real turboprop flights. Seventy-three subjects answered questions on various environmental factors during a simulated flight in the Cabin Demonstrator. Subject testing revealed that the Cabin Demonstrator was overall perceived as realistic compared to real flights, and the comfort level was comparable to the previously conducted in-flight subject test. Thus, the Cabin Demonstrator can be used for multiple future tests.

Professional truck drivers spend prolonged periods seated, often leading to discomfort and fatigue. Conventional seats are typically designed for average body dimensions rather than individual morphology, which limits their ability to provide optimal support. This study investigates whether 3D-printed personalized seat inserts, developed through an integrated digital workflow, can improve pressure distribution and perceived comfort compared with a standard truck seat. Sixteen participants completed the full workflow from body-data acquisition to comfort evaluation in a static truck buck. Unlike existing personalization approaches, the workflow explicitly incorporates occupational context and task-related posture constraints as design inputs, and validates a complete, reproducible end-to-end process combining vacuum cushion molding, 3D scanning, computational modelling, and large-format additive manufacturing. Pressure mapping and subjective comfort ratings were collected for both baseline and personalized conditions. The personalized inserts reduced mean pressure by 39% and peak pressure by 18%, while increasing contact area by 15%. Subjective comfort scores improved significantly across all regions, particularly in the buttock area, with participants describing firmer yet more stable support. Beyond these ergonomic outcomes, the study contributes a context-driven personalization method and demonstrates that geometric adaptation informed by real use conditions yields quantifiable comfort benefits in an occupational transport setting.

4D-scans of dynamic deformable human body parts help researchers have a better understanding of spatiotemporal features. However, reconstructing 4D-scans utilizing multiple asynchronous cameras encounters two main challenges: 1) finding dynamic correspondences among different frames captured by each camera at the timestamps of the camera in terms of dynamic feature recognition, and 2) reconstructing 3D-shapes from the combined point clouds captured by different cameras at asynchronous timestamps in terms of multi-view fusion. Here, we introduce a generic framework able to 1) find and align dynamic features in the 3D-scans captured by each camera using the nonrigid-iterative-closest-farthestpoints algorithm; 2) synchronize scans captured by asynchronous cameras through a novel ADGC-LSTMbased-network capable of aligning 3D-scans captured by different cameras to the timeline of a specific camera; and 3) register a high-quality template to synchronized scans at each timestamp to form a highquality 3D-mesh model using a non-rigid registration method. With a newly developed 4D-foot-scanner, we validate the framework and create the first open-access data-set, namely the 4D-feet. It includes 4Dshapes (15 fps) of the right and left feet of 58 participants (116 feet including 5147 3D-frames), covering significant phases of the gait cycle. The results demonstrate the effectiveness of the proposed framework, especially in synchronizing asynchronous 4D-scans.

Preserving features or local shape characteristics of a mesh using conventional non-rigid registration methods is always difficult, as the preservation and deformation are competing with each other. The challenge is to find a balance between these two terms in the process of the registration, especially in presence of artefacts in the mesh. We present a non-rigid Iterative Closest Points (ICP) algorithm which addresses the challenge as a control problem. An adaptive feedback control scheme with global asymptotic stability is derived to control the stiffness ratio for maximum feature preservation and minimum mesh quality loss during the registration process. A cost function is formulated with the distance term and the stiffness term where the initial stiffness ratio value is defined by an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based predictor regarding the source mesh and the target mesh topology, and the distance between the correspondences. During the registration process, the stiffness ratio of each vertex is continuously adjusted by the intrinsic information, represented by shape descriptors, of the surrounding surface as well as the steps in the registration process. Besides, the estimated process-dependent stiffness ratios are used as dynamic weights for establishing the correspondences in each step of the registration. Experiments on simple geometric shapes as well as 3D scanning datasets indicated that the proposed approach outperforms current methodologies, especially for the regions where features are not eminent and/or there exist interferences between/among features, due to its ability to embed the inherent properties of the surface in the process of the mesh registration.

Structural electronics has garnered significant attention in the past decade. However, there remains a lack of a systematic approach in designing and manufacturing sensors that leverage both mechanical and electronic properties of materials for different applications. In this paper, we introduce a method for designing piezoresistive force sensors utilizing structural electronics and 3D printing techniques. Based on the principles of piezoresistive force sensing, we defined the geometric profile of the sensor by simultaneously maximizing strain and ensuring as uniform as possible stress distribution across the geometry. CAD models of the sensors were then formulated based on the optimized profile and fabricated using conductive filaments and the material extrusion 3D printing technique. Subsequently, we evaluated the accuracy, the sensitivity, and part-to-part variations of the sensors during loading and unloading. The influence of environmental temperature and humidity on the sensor's response were also investigated and compensated. Experiment results demonstrated the feasibility of the proposed method and revealed potential application domains, as well as limitations of the sensors.

Turboprop aircraft are a useful alternative to reduce CO2 emissions, but they have a higher noise and vibration level compared to turbojets. We investigated how passengers perceived noise and vibration during two turboprop flights in an ATR72.In general, noise as assessed as slightly loud and slightly annoying, but became less noisy and more comfortable over time. Subjects evaluated the vibration as rather comfortable, but the perception of vibration varied for different body areas. Discomfort of vibration decreased. If noise sensitivity is added to these analyses, changes over time largely disappeared showing the complex interaction between characteristics of the person and the environment. In summary, the rather negative evaluation of noise and vibration could be the factors why people decide not to fly with turboprop aircrafts. The development of turboprop aircraft with less noise and vibration remains important so that this more sustainable aircraft type is competitive.

Many new future sustainable aircraft concepts have (electric) propeller propulsion. However, the noise and vibration generated by propeller propulsion might create discomfort for passengers. In the Clean Sky 2 project ‘ComfDemo’, all factors influencing comfort and discomfort are studied, with the aim to improve comfort experience for eco airplanes. The results show that noise, vibration and seat are the most mentioned factors influencing discomfort. The flights without passengers showed different noise characteristics, which makes test flights with passengers inevitable. Noise certainly needs attention, but anthropometrics as well as for instance elbow-elbow width is greater than the 18” seat width for many passengers.

This interactive textbook provides an educational resource into computational design for (industrial) designers. The book focusses on the use of computational design of products/artifacts at a human scale, which might be contrasted by the architectural/build environment scale – a domain which also extensively utilizes computational design principles and tools. Throughout the book, we make use of (commercial) computer-aided-design software, namely Rhinoceros®, and specifically the (build-in) module Grasshopper®.

The lessons and knowledge base offered in this book focus on topics that are specifically relevant for and/or attuned to product design (scale), which are categorized in relation to its goal (e.g. design for personalized fit/comfort/aesthetics), by its means (e.g. design for digital fabrication), or for its role in the design process (e.g. for design exploration or design simulation).

The book is intended for students both at bachelor and master level. As we believe in a learning-by-doing approach, we aimed for a hands-on, easy-to-get-started set of introductory lessons, which is complemented with a knowledge base. The introductory lessons do not assume any specific prior skills or knowledge (in general or with Rhino Grasshopper) to get started. Yet, (some) experience with computer-aided design (CAD), programming, data processing, and/or mathematics will likely be helpful to really delve into the more complex topics, such as those covered in the knowledge base.

The book is currently used as course material in two courses taught at Industrial Design Engineering: “Prototyping with/for Digital Fabrication” (BSc level, part of the Minor Advanced Prototyping), and “Computational design for Digital Fabrication” (MSc level, Elective). The content in this book is in part based on course materials from the above-mentioned courses, which have been been taught to and applied by students with diverse (technical) backgrounds (e.g. industrial design, mechanical engineering, computer science, and electrical engineering). Other parts of the book are inspired by student (graduation) projects and/or follow from research activities by the various contributing authors.

Turboprop aircraft should be improved as they are more environmentally friendly aircraft compared to turbojet aircraft but noise and vibration are often too high for passengers. A simple and uncomplicated way to carry out experiments is using a demonstrator. To determine whether the demonstrator represents the reality, it must be validated. In this project, real flights were first conducted in a turboprop aircraft. During two 70-minute flights, 94 subjects answered questions about symptoms, mood or comfort levels related to noise and vibration, among other things. In the next step, investigations will be carried out in the demonstrator under the same conditions as the real flights. Both results will be compared with each other. If the data from the demonstrator corresponds to that of the real flights, the demonstrator is considered to have been successfully validated. The requirement for this is that the demonstrator data lies within the confidence intervals of the results from the real flights. The aim is to validate a full-scale on-ground demonstrator of a regional turboprop aircraft cabin that will be used for multiple tests like subject tests and comfort evaluation, composite materials and structures, systems and energy consumption.

Taking a nap is a welcome pastime in vehicles such as trains, airplanes, and cars. Flat sleeping cannot always be facilitated because of space and economic constraints, but a larger backrest recline angle is associated with better sleep quality. To define the best and the worst comfort experience and sleep comfort in these settings, and to offer design guidelines to practitioners, six backrest recline angles were compared regarding overall comfort and sleep comfort. The backrest recline angles ranged from 110 to 150 degrees, and 180 degrees was added as a reference. 16 participants were invited to sleep for a duration of 90 min. in each condition. Overall comfort and sleep comfort significantly improve in conditions higher than 120 degrees. Local discomfort is rated relatively low in all angles, but in comparison, people experience high discomfort in the neck, lower back, and lower leg region while in the 110 and 120 degrees condition. It is concluded that in the bigger recline angles the napping comfort experience is higher, with a minimum advised angle of 130 degrees.

Automated driving frees users from the task of driving, allowing them to engage in new activities. Using keywords related to Non-Driving-Related Activities (NDRAs) and automated vehicles (and their variants), with reference to the Society of Automotive Engineers (SAE) levels 3, 4, and 5, the authors identified 2430 studies from various databases and sources. Of these, 47 were included in this study, with 39 included in the meta-analysis. The meta-analysis of the included studies shows a positive correlation between automation levels and the diversity of NDRAs. Communication and interaction with passengers are the most common activities, followed by media consumption, rest, and relaxation. Food and drink consumption slightly surpasses working and productivity, while personal habits and hygiene are less prioritized. Although some users still value vehicle monitoring, this need decreases with higher automation levels. Key activities such as communication, laptop use, and sleeping are highlighted as significant benefits of automation, as users transition away from situational awareness and are able to perform cognitively intensive tasks. The review also addresses potential design implications to support these NDRAs and discusses related regulatory challenges.

When designing wearables that interface with the human head, face and neck, designers and engineers consider human senses, ergonomics and comfort. A dense 3D pressure discomfort threshold map could be helpful, but does not exist yet. Differences in pressure discomfort threshold for areas of the head, neck and face were recorded, to create a 3D pressure discomfort threshold map.

Between 126 and 146 landmarks were placed on the left side of the head, face and neck of twenty-eight healthy participants (gender balanced). The positions of the landmarks were specified using an EEG 10–20 system-based landmark-grid on the head and a self-developed grid on the face and neck. A 3D scan was made to capture the head geometry and landmark coordinates. In a randomised order, pressure was applied on each landmark with a force gauge until the participant indicated experiencing discomfort. By interpolating all collected pressure discomfort thresholds based on their corresponding 3D coordinates, a dense 3D pressure discomfort threshold map was made.

A relatively low-pressure discomfort threshold was found in areas around the nose, neck front, mouth, chin-jaw, cheek and cheekbone, possibly due to the proximate or direct location of nerves, blood veins and soft (muscular) tissue. Medium pressure discomfort was found in the neck back, forehead and temple regions. High pressure discomfort threshold was found in the back of the head and scalp, where skin is relatively thin and closely supported by bone, making these regions interesting for mounting or resting head, face and neck related equipment upon.