Search Results (275)

This study aims to develop an innovative and functional mastectomy bra that addresses the physical, aesthetic, and psychological needs of post-mastectomy women. Mastectomy bras play a vital role in prosthesis stability, body image improvement, and quality of life. Using CLO 3D virtual fitting software-2024.2.214, two bra models were designed and evaluated for ergonomic fit and aesthetic appearance. The virtual prototyping method enabled design evaluation without physical sample production, providing an efficient and sensitive approach for user-centered design. Features such as prosthesis stability, user comfort, and aesthetic elements were optimized, while Tencel–PES–elastane and nylon–elastane fabrics were compared for pressure performance and body fit. Results showed similar performance for both fabrics; however, Tencel was recommended as a sustainable option due to its superior moisture absorption, breathability, and skin-friendly properties. The 3D virtual prototyping method offered an effective evaluation tool while addressing the psychological needs of women who prefer not to participate in physical fittings. This approach presents an innovative and sustainable model that can be applied to the design of other specialized garments. This study presents an innovative contribution by integrating advanced CLO 3D virtual prototyping technology into the design process, enabling ergonomic and aesthetic evaluations without the need for physical samples, especially for women in the sensitive post-operative period. This innovative approach not only streamlines the design process but also establishes a sustainable framework for specialized garment production. The utilization of Tencel–polyester–elastane fabric as a sustainable alternative demonstrates suitable performance in terms of comfort and ergonomic fit while promoting environmentally friendly practices. These findings highlight the significance of digital prototyping methods in garment design and offer a user-centric, eco-conscious model applicable to other specialized garments. Full article

The design of Web3 applications presents unique challenges due to their complex technical requirements. Despite the increasing spread of this technology, there is a notable lack of comprehensive, empirically grounded design guidelines for developing user-friendly Web3 interfaces. This study addresses this gap through a systematic three-phase approach: (1) developing initial guidelines from a literature review and industry sources (n = 31), (2) conducting evaluations using a 14-point framework based on the initial guidelines to test its effectiveness across diverse Web3 applications (n = 25), and (3) validating refined guidelines through expert evaluation sessions (n = 7). Expert evaluations highlighted the need for task-oriented rather than category-based organization of design principles. Based on these findings, we developed a structured framework organizing guidelines into four key task flows, each with three implementation levels. The framework emphasizes progressive disclosure of blockchain concepts, integrated user education, and clear state visualization. Our findings contribute to academic discussion and industry practice by providing empirically validated patterns for Web3 interface design. This study lays a foundation for creating more accessible and user-friendly decentralized applications, though future work should focus on longitudinal validation and adaptation to emerging technologies. Full article

In an era of increasing reliance on digital health solutions, safeguarding user privacy has emerged as a paramount concern. Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. Unlike conventional centralized systems, FLORA ensures that sensitive information remains on users’ devices, with predictive algorithms powered by local computations. Blockchain technology provides immutable consent tracking and model update transparency, further improving user trust. In addition, FLORA’s design incentivizes participation through a token-based reward system, fostering collaborative data contributions. This work illustrates how the integration of cutting-edge technologies creates a secure, scalable, and user-centric health application, setting a new standard for privacy-preserving digital health platforms. Full article

Background: Smart home technologies (SHTs) hold promise for supporting older adults by enabling early detection and intervention in mental health challenges such as depression, anxiety, and cognitive decline. However, adoption remains limited due to usability, accessibility, and privacy concerns. Methods: This narrative review examined the literature from 2010 to early 2024 related to SHTs and their impact on older adults’ mental health. In total, 34 relevant studies met the inclusion criteria, and also, a standardized quality assessment tool was used to evaluate the methodological soundness of the included studies. Results: Findings reveal that interface complexity, cognitive overload, high costs, and privacy concerns are significant barriers to adoption. Accessibility challenges, including physical and sensory impairments, further reduce engagement and inclusivity. Key facilitators for user acceptance include user-centric design, personalization, participatory co-development, and cultural adaptations. SHTs incorporating AI-driven features, such as behavioral monitoring, medication reminders, and social engagement tools, demonstrate significant potential for early mental health interventions. Based on these findings, we propose a holistic framework integrating technical innovation with human-centered design to address these challenges and optimize SHTs for mental healthcare. Conclusions: Tailored systems that prioritize usability, accessibility, ethical data management, and user feedback can empower older adults to maintain autonomy, support aging in place, and enhance their quality of life with dignity. Full article

Despite being well-positioned to promote healthy lifestyles in young children, early years practitioners often face barriers to supporting child weight management. This mixed-methods study aimed to assess the preliminary effectiveness and acceptability of an e-learning toolkit (HealthyWEY) designed to upskill and support multi-agency professionals to promote healthy weight in early childhood. A total of 54 health visitors/community nursery nurses, 38 children’s centre staff and 17 other health professionals engaged with the HealthyWEY e-learning, which drew on self-determination theory and consisted of nine modules that were completed over 7–10 weeks. Non-parametric statistical analysis using Wilcoxon’s signed-rank tests were used to explore participants’ practice-based knowledge, psychological needs satisfaction and motivations for prioritising pre-school child weight from pre- to post-intervention. Focus groups (n = 11) were conducted with a sub-sample of multi-agency professionals (n = 39) to explore the process of implementation across sites, while interviews were also conducted with two parents/carers who took part in consultations with HealthyWEY-trained practitioners. After completing the HealthyWEY e-learning, participants perceived fewer barriers to pre-school child weight management (median change = −0.7; p < 0.001), greater autonomy (median change = 0.7, p < 0.001), competence (median change = 0.8, p < 0.001) and relatedness (median change = 0.4, p < 0.001) and a higher autonomous motivation towards promoting healthy weight (median change = 0.3, p < 0.001). E-learning was perceived to be highly relevant to participants’ roles and congruent with local child weight strategies. Challenges to implementation included time constraints and disruptions related to the COVID-19 pandemic. Recommendations for a better user experience were offered by enhancing the toolkit’s design and interactivity. Engagement with the HealthyWEY e-learning led to promising changes in perceived barriers and motivational variables. The toolkit was perceived to be acceptable amongst multi-agency workforces, albeit challenging to prioritise within time-pressured health and early years settings. Full article

Developing effective cognitive training tools for older adults, specifically addressing executive functions such as planning, is a challenging task. It is of paramount importance to ensure the implementation of engaging activities that must be tailored to the specific needs and expectations of older adults. Furthermore, it is essential to provide the appropriate level of complexity for the planning task. A human-centred approach was used to address the issues identified in the design of the tool. Two pilot studies were conducted with older adults to fine-tune the training task and optimize its suitability for them. This also led to an enhancement of the underlying planning engine, transitioning from a simple fast-forward planner (PDDL4J) to an advanced heuristic search planner (ENHSP). The results show that user studies enabled the development of a cognitive training system that gradually increased the proposed difficulty levels of the planning task while maintaining usability and satisfaction among older adults. This highlights the importance of conducting user studies when implementing cognitive training tools for older adults. Full article

The rapid advancement of intelligent technologies, including sensing devices, artificial intelligence, and the Internet of Things, has significantly accelerated the progress in industrial technology, particularly within the medical enterprise sector. Wearable innovations for health management have introduced novel approaches to physiological monitoring and early disease detection, contributing to an improved quality of life. In the context of sustainable development, wearable devices demonstrate considerable potential for supporting long-term healthcare solutions, particularly in the post-pandemic era, where the demand for smart health solutions continues to rise. This study aims to identify critical product design indicators for wearable devices that align with sustainable health management goals. Utilizing expert questionnaires and employing a combination of the Fuzzy Delphi Method and the DEMATEL-based Analytic Network Process (ANP), this research systematically evaluates the key factors influencing wearable device design. The findings highlight three primary aspects, six criteria, and 16 design indicators, with pivotal factors including “Compatibility”, “Foresight”, “Integration”, “Comfort”, “Appearance”, “Customization”, and “Intelligence”. These indicators provide a comprehensive framework for developing wearable devices that address diverse user needs while promoting individual well-being and sustainable health management. This study offers valuable insights into the design and development of wearable devices that support sustainable healthcare practices, advance social responsibility, and strengthen preventive care initiatives. Full article

According to official surveys, the number of adolescents with mental health problems in Poland is increasing, which is also typical of other European countries. At the same time, programmes are being introduced to secure infrastructure and adequate therapeutic space by expanding or creating new, architecturally friendly centres. The comfort of the stay created by appropriate spatial conditions must be developed with the participation of the users (patients, staff and visitors). A qualitative study was carried out among staff, based on the structured interview method. The aim of the study was to diagnose the elements of architectural space that support health. It was hypothesised that the architecture of health care facilities could promote mental health. Using advances in environmental psychology, evidence-based design, and elements such as architectural form, spatial-functional layout and the surrounding environment were considered. The results of the study identified features of a user-friendly environment, creating a set of recommendations based on the research-by-design method. Consequently, the recommendations were implemented into the conceptual design. Their validity was proven using the example of the design of a health centre for young people in Klawa, Poland. Full article

Smart cities are complex urban environments that rely on advanced technology and data analytics to enhance city services’ quality of life, sustainability, and efficiency. As these cities continue to evolve, there is a growing need for a structured framework to evaluate and integrate products that align with smart city objectives. This paper introduces the Pentagon Framework, a comprehensive evaluation method designed to ensure that products and their materials meet the specific needs of smart cities. The framework focuses on five key features—smart, sustainable, sensing, social, and safe—collectively called the Penta-S concept. These features provide a structured approach to categorizing and assessing products, ensuring alignment with the city’s goals for efficiency, sustainability, and user experience. The Smart City Pentagon Framework Analyzer is also presented, a dedicated web application that facilitates interaction with the framework. It allows product data input, provides feedback on alignment with the Penta-S features, and suggests personality traits based on the OCEAN model. Complementing the web application, the Smart City Penta-S Compliance Assistant API, developed through ChatGPT, offers a more profound, personalized evaluation of products, including the life cycle phase recommendations using the IPPMD model. This paper contributes to the development of smart city solutions by providing a flexible framework that can be applied to any product type, optimizing its life cycle, and ensuring compliance with the Pentagon Framework. This approach improves product integration and fosters user satisfaction by tailoring products and their materials to meet specific user preferences and needs within the smart city environment. The proposed framework emphasizes citizen-centric design and highlights its advantages over conventional evaluation methods, ultimately enhancing urban planning and smart city development. Full article

Urbanization intensifies the need for sustainable public transportation that balances financial viability, environmental sustainability, and social equity. Traditional fare-setting methods often focus narrowly on financial objectives, neglecting broader impacts. This study introduces a novel collaborative game-theoretic model integrating user sentiment analysis to optimize fare policies. By incorporating utilities of passengers, operators, and governments, and employing the Shapley value for fair benefit distribution, this model aims to maximize social welfare. The methodology frames fare optimization as a cooperative game among stakeholders, integrating passenger preferences through sentiment analysis. The social welfare function combines the utilities of all stakeholders and is maximized under operational, environmental, and financial constraints. Implemented in Python and applied to Isparta, Turkey, the model identifies an optimal fare of 19.5 TL (ranged between 14 and 26.50 TL) that maximizes social welfare, aligning closely with existing fares. Shapley value analysis distributes the benefits, assigning 221,457 (35.6%) units to passengers, 54,562 (8.7%) units to operators, and 347,433 (55.7%) units to the government, highlighting significant environmental gains for the government. Sensitivity analyses confirm the model’s robustness across varying trip volumes, suggesting its applicability to diverse urban settings. This research contributes to socially equitable and user-centric fare policies by providing a comprehensive framework aligning stakeholder interests. Policymakers can leverage this model to design fare strategies promoting sustainability, efficiency, and collaboration in public transportation systems. Full article

This work addresses the task allocation problem in spatial crowdsensing with altruistic participation, tackling challenges like declining engagement and user fatigue from task overload. Unlike typical models relying on financial incentives, this context requires alternative strategies to sustain participation. This paper presents a new solution, the Volunteer Task Allocation Engine (VTAE), to address these challenges. This solution is not based on economic incentives, and it has two primary goals. The first one is to improve user experience by limiting the workload and creating a user-centric task allocation solution. The second goal is to create an equal distribution of tasks over the spatial locations to make the solution robust against the possible decrease in participation. Two approaches are used to test the performance of this solution against different conditions: computer simulations and a real-world experiment with real users, which include a qualitative evaluation. The simulations tested system performance in controlled environments, while the real-world experiment assessed the effectiveness and usability of the VTAE with real users. This research highlights the importance of user-centered design in citizen science applications with altruistic participation. The findings demonstrate that the VTAE algorithm ensures equitable task distribution across geographical areas while actively involving users in the decision-making process. Full article

Background: Visual impairment can significantly impact an individual’s daily activities. Patients require regular monitoring, typically occurring within hospital eye services. Capacity constraints have necessitated innovative solutions to improve patient care. Existing digital solutions rely on task-based digital home monitoring such as visual acuity testing. These require active involvement from patients and do not typically offer an indication of quality of life. Digital phenotyping refers to the use of personal digital devices to quantify passive behaviour for detecting clinically significant changes in vision and act as biomarkers for disease. Its uniqueness lies in the ability to detect changes passively. The objective was to co-design an accessible smartphone app (OverSight) for the purposes of digital phenotyping in people with sight impairment. Methods: Development of OverSight included stakeholder consultations following principles of user-centred design. Apple iOS software frameworks (HealthKit, ResearchKit, and SensorKit) and a SwiftUI developer toolkit were used to enable the collection of active and passive data streams. Accessibility and usability were assessed using the System Usability Scale (SUS) and feedback following a 3-month pilot study. Consultations with patients informed the design of OverSight, including preferred survey scheduling and the relevancy of patient support resources. Results: Twenty visually impaired participants (mean age 42 ± 19 years) were recruited to the pilot study. The average score on the SUS was 76.8 (±8.9), indicating good usability. There was a statistically significant moderate negative correlation between SUS scores and visual acuity in both the better (r = −0.494; p ≤ 0.001) and worse eye (r = −0.421; p ≤ 0.001). Conclusions: OverSight offers promising potential for collecting patient-generated health data for the purposes of digital phenotyping in patients with eye disease. Through further testing and validation, this novel approach to patient care may ultimately provide opportunities for remote monitoring in ophthalmology. Full article

Objectives: This study explores stroke rehabilitation facility design in Australia, identifying the key design typologies at multiple scales and assessing them against the critical design criteria for stroke rehabilitation. Background: The physical environment plays a crucial role in stroke rehabilitation, affecting patient recovery and well-being. However, limited research examines how design can support therapeutic outcomes in these facilities. Method: From a systematic review of 257 Australian stroke rehabilitation facilities, 30 were selected for detailed design review, with an in-depth room-level analysis conducted for 10. Using the modified PRISMA framework and a typology analysis approach, this study integrates architectural precedent with clinical research methods. Results: Typologies were identified at the site, building, ward, and room levels. Acute hospital wards (53%) and ‘blocks’ (73%) were the most common site and building arrangements, respectively. At the ward level, ‘racetrack with courtyard’ layouts enhanced natural light, views, and access to landscaped areas. A room-level analysis revealed limited innovation, with most rooms adhering to standard designs, though some adaptations improved visual connectivity and personal control. Hybrid nurse stations and courtyards supported efficiency, social interaction, and therapeutic stimulation. Conclusions: This study highlights the user-centred design strategies tailored to stroke patients’ needs and the importance of evidence-based approaches prioritising well-being. Future research should incorporate 3D spatial analysis for actionable design recommendations. Full article

The increasing adoption of electric vehicles offers a way to combat the harmful impacts of climate change and to improve city living standards. Yet limited access to and lack of consistency among electric vehicle charging stations present obstacles for electric vehicle owners. This study advocates for an approach that positions the preferences of electric vehicle drivers first when choosing an electric vehicle charging station. By considering relevant factors to electric vehicle drivers and treating the problem as a grey system where certain information is known while other aspects are unknown, this research aims to empower users to make decisions aligned with their needs. The best–worst method is employed to assign preferences allowing electric vehicle users to make informed choices based on their priorities. The grey relational analysis method is utilized to rank electric vehicle charging stations based on user preferences. The best–worst method-grey relational analysis approach, as shown by examples, efficiently assists electric vehicle users in choosing the optimal electric vehicle charging station. This study acknowledges and incorporates the often-overlooked perspectives of electric vehicle drivers into a user-centric solution in existing research models. The gained insights carry significance for managing transportation and energy systems and designing user-friendly applications pertaining to electric vehicle charging station selection. Full article

Electric vehicles (EVs) play a vital role in the transition to renewable energy and decarbonisation, and there is increasing global interest in expanding their use. However, the growing number of EVs poses challenges to the electricity grid due to increasing energy demand. Vehicle-to-grid (V2G) technology can address these issues by allowing for EVs to charge and discharge energy, thus helping to balance the grid when needed. Aggregating vehicles in designated parking areas optimises energy transfer, making it crucial to identify suitable parking locations and forecast the energy available from parked vehicles. A spatial–temporal framework ensures that V2G services operate efficiently considering both the location and the timing of vehicle parking. This paper reviews studies on temporal–spatial V2G parking demand, identifying high-demand areas such as shopping centres and workplaces, where vehicles park for extended periods. Strategic locations of V2G hubs in these areas ensures seamless integration into existing mobility patterns without disrupting users’ routines. In addition, this review examines user acceptance, technical feasibility, and V2G’s role in reducing grid demand peaks. The findings indicate the potential of effectively implemented V2G services to enhance electricity grid stability and efficiency while minimising disruptions to EV users. Full article