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.

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.

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.

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.

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.

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.

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.

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.

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.

High-speed rail might be a solution to reduce energy usage and carbon emissions as rail transport consumes less energy than airplanes. However, in choosing a transport system, time is an important factor in making many passengers choose air travel. This paper studies the reasons why passengers choose a transport mode, and compares the comfort of aircraft and train seats. This study shows that time and costs are the most mentioned factors, but comfort and sustainability can play a deciding role between trains and airplanes on time and cost-competitive travel routes. The train seat is evaluated as the most comfortable, but still, part of the passengers choose the aircraft as the length of sitting on the seat is limited.

In the past decade, human digital twins (HDTs) attracted attention in both digital twin (DT) applications and beyond. In this paper, we discuss the concept and the development of HDTs, focusing on their architecture, key enabling technologies, and (potential) applications. Based on the literature, we identify personal data, model, and interface as three key modules in the proposed HDT architecture, supported by a data lake of human data and a model and interface library. Regarding the key enabling technologies that support the HDT functions, we envision that the internet of things (IoT) infrastructure, data security, wearables, human modeling, explainable artificial intelligence (AI), minimum viable sensing, and data visualization are closely associated with the development of HDTs. Finally, we investigate current applications of HDTs, with a particular emphasis on the opportunities that arise from leveraging HDTs in the field of personalized product design.

Passengers' comfort experience during flights is important in choosing their flights. The focus of this study is passengers’ perceived comfort in different climbing angles during ascent. Twenty-six participants were invited to experience three inclination angles including 3°, 14° and 18° in a Boeing 737 cabin. The angle of 3° was used to simulate cruising stage and the other two were used to simulate different climbing angles. Participants experienced each setting for 20 min where the perceived comfort, their heart rate variability(HRV), and their body contact pressure values on the backrest and seat pan were recorded with questionnaires, HRV bands and pressure mats respectively. The results indicate a preference of 14° inclination angle resembling the cruising angle (3°) and having the slowest moving speed of the center of pressure (COP) on both the backrest and seat pan.

BACKGROUND: A valid distribution of key anthropometric parameters among participants is often a perquisite of ergonomics research. OBJECTIVE: In this paper, we investigated the accuracy of self-reported stature and body mass of the population in the Netherlands. METHODS: Data from 4 experiments was synthesized where in each experiment, participants self-reported their stature and body mass prior to being measured, of which they were not notified before. RESULTS: Statistical analysis of 249 records indicated that on average, participants overreported their stature by 1.31 cm and underreported their mass by 1.45 kg. This is especially true for people with a BMI ≥ 25. CONCLUSION: Two models were proposed to adjust the self-reported stature and body mass for ergonomic researchers in a survey or recruitment. Limitations in using the models are highlighted as well.

Wearables are used to recognize human activities in various applications. However, there is limited evidence on the comfort feelings in using wearables, which is crucial for the adoption and long-term engagement of users in those applications. In this paper, we propose the concept of comfort wearables in the context of in-flight posture recognition. A comfort wearable and a tight-fit version, using identical hardware and software architecture, were prototyped and tested by 35 participants in a Boeing 737 cabin. During the usage of each wearable, participants were asked to perform seven frequently observed in-flight sitting postures and report their overall comfort/discomfort afterwards. A multilayer perceptron neural network was used to classify those activities. Experiment results indicated that participants appreciated the comfort wearable, rating it with significantly higher comfort scores and lower discomfort scores. Cross-validation results also revealed that using the comfort wearable achieved even better accuracy (74.8%) than using the tight-fit wearable (65.8%) in posture recognition. Outcomes of the study demonstrate that ergonomic design and technical accuracy are not competing factors in the wearable design and highlight the opportunities for designing and using comfort wearables in broader contexts.

Personalized designs bring added value to the products and the users. Meanwhile, they also pose challenges to the product design process as each product differs. In this paper, with the focus on personalized fit, we present an overview as well as details of the personalized design process based on design practice. The general workflow of personalized product design is introduced first. Then different steps in the workflow such as human data/parameters acquisition, computational design, design for digital fabrication, and product evaluation are presented. Tools and methods that are often used in different steps in the process are also outlined where in human data acquisition, 3D scanning, and digital human models are addressed. For computational design, the use of computational thinking tools such as abstraction, decomposition, pattern recognition and algorithms are discussed. In design for digital fabrication, additive manufacturing methods (e.g. FDM), and their requirements on the design are highlighted. For product evaluation, both functional evaluation and usability evaluation are considered and the evaluation results can be the starting point of the next design iteration. Finally, several case studies are presented for a better understanding of the workflow, the importance of different steps in the workflow and the deviations in the approach regarding different contexts. In conclusion, we intend to provide designers a holistic view of the design process in designing personalized products as well as help practitioners trigger innovations regarding each step of the process.

Predicting pediatric spinal deformity (PSD) from X-ray images collected on the patient’s initial visit is a challenging task. This work builds on our previous method and provides a novel bio-informed framework based on a mechanistic machine learning technique with dynamic patient-specific parameters to predict PSD. We provide a geometry-based bone growth model that can be utilized in a range of applications to enhance the bio-informed mechanistic machine learning framework. The proposed technique is utilized to examine and predict spine curvature in PSD cases such as adolescent idiopathic scoliosis. The best fit of a segmented 3D volumetric geometry of the human spine acquired from 2D X-ray images is employed. Using an active contour model based on gradient vector flow snakes, the anteroposterior and lateral views of the X-ray images are segmented to derive the 2D contours surrounding each vertebra. Using minimal user input, the snake parameters are calibrated and automatically computed over the dataset, resulting in fast image segmentation and data collection. The 2D segmented outlines of each vertebra are transformed into a 3D image segmentation result. The Iterative Closest Point mesh registration technique is then used to establish a mesh morphing approach and creates a 3D atlas spine model. Using the comprehensive 3D volumetric model, one can automatically extract spinal geometry data as inputs to the mechanistic machine learning network. Moreover, the proposed bio-informed deep learning network with the modified bone growth model achieves competitive or even superior performance against other state-of-the-art learning-based methods.Please check and confirm if the author names and initials are correct for “Yongjie Jessica Zhang” and “Wing Kam Liu”.We confirm they are correct.

Optical motion capturing explains the three-Dimensional (3D) position estimation of points through triangulation employing several depth cameras. Prosperous performance relies on level of visibility of points from different cameras and the overlap of captured meshes in-between. Generally, the accuracy of the estimation is practically based on the camera parameters e.g., location and orientations. Accordingly, the camera network configurations play a key role in the quality of the estimated mesh. This paper proposes an optimal approach for camera placement based on characteristics of a depth camera D435i - Intel RealSense. The optimal problem includes a cost function that contains several minimisation and maximisation terms. The minimisation terms are distance of the cameras to the center of the scanning object, resolution error, and sparsity. And the maximisation terms are distance between each two pair of cameras, percent of captured point from an object, and the level of overlap between cameras. The object is designed based on practical experiments of human walking and is a bounding box around one step of dynamic foot work-space from heel strike posture to toe-off posture. The accuracy and robustness of the algorithms are assessed via experiment measurement, and sensitivity to the number of cameras is investigated. Accordingly, the experiment results determined that the scanning accuracy can be as high as 2.5 % based on a reference scan with a high-end scanner (Artec Eva).

The geometric shapes and the relative position of coils influence the performance of a three-dimensional (3D) inductive power transfer system. In this paper, we propose a coil design method for specifying the positions and the 3D shapes of a pair of coils to transmit the desired power. Given region of interests (ROIs) for designing the transmitter and the receiver coils on two surfaces, the transmitter coil is generated around the center of its ROI. The center of the receiver coil is estimated as a random seed position in the corresponding 3D surface. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the set of coils. In each step, the shape of the extension, i.e., a new turn of the receiver coil, is found as a spiral curve based on the convex hulls of the 2D projected adjacent turns along their normal direction. Then, the optimal position of the receiver coil is found by maximizing the efficiency of the system. In the next step, the position and the shape of the transmitter coil are optimized based on the fixed receiver coil using the same method. This optimization process iterates until an optimum is reached. Simulations and experiments with digitally fabricated prototypes were conducted and the effectiveness of the proposed 3D coil design method was verified.

BACKGROUND: falls and fall-related injuries are common in older adults, have negative effects on functional independence and quality of life and are associated with increased morbidity, mortality and health related costs. Current guidelines are inconsistent, with no up-to-date, globally applicable ones present. OBJECTIVES: to create a set of evidence- and expert consensus-based falls prevention and management recommendations applicable to older adults for use by healthcare and other professionals that consider: (i) a person-centred approach that includes the perspectives of older adults with lived experience, caregivers and other stakeholders; (ii) gaps in previous guidelines; (iii) recent developments in e-health and (iv) implementation across locations with limited access to resources such as low- and middle-income countries. METHODS: a steering committee and a worldwide multidisciplinary group of experts and stakeholders, including older adults, were assembled. Geriatrics and gerontological societies were represented. Using a modified Delphi process, recommendations from 11 topic-specific working groups (WGs), 10 ad-hoc WGs and a WG dealing with the perspectives of older adults were reviewed and refined. The final recommendations were determined by voting. RECOMMENDATIONS: all older adults should be advised on falls prevention and physical activity. Opportunistic case finding for falls risk is recommended for community-dwelling older adults. Those considered at high risk should be offered a comprehensive multifactorial falls risk assessment with a view to co-design and implement personalised multidomain interventions. Other recommendations cover details of assessment and intervention components and combinations, and recommendations for specific settings and populations. CONCLUSIONS: the core set of recommendations provided will require flexible implementation strategies that consider both local context and resources.