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The article explores the application of artificial intelligence (AI) in generative design, specifically in the creation of trademark logos, through an academic experience with industrial design students. The study explores AI’s role in enhancing creativity, productivity, and diversity during the conceptual design phase, while capturing students’ perspectives on the creative process. The methodology employed included a qualitative survey with open-ended questions to gather student opinions. Two practical exercises were conducted, one using traditional methods and the other AI, to design logos for fictitious brands. Results indicate that manual designs allow for greater expression of brand identity and emotional attachment, whereas AI-assisted designs offer rapid generation of numerous versions with a professional finish. Students identified key advantages of AI, including time optimization and support in generating new ideas. However, they highlighted limitations such as reduced control over final outcomes and difficulties in editing AI-generated designs. The findings suggest that AI, while lacking the personality and emotional depth of manual designs, can complement traditional methods when used strategically. This study emphasizes the potential of hybrid approaches combining human creativity with AI efficiency to achieve optimal outcomes. It also underscores the need for design education to integrate AI tools, preparing students for a rapidly evolving industry. The research contributes to discussions on balancing efficiency, creativity, and control in professional logo design, proposing strategies for human–AI collaboration in design processes.

Osteoarthritis is a disabling condition that is often associated with other comorbidities. Total hip or knee arthroplasty is an effective surgical treatment for osteoarthritis when indicated, but comorbidities can impair their results by increasing complications and social and economic costs. Integrated care (IC) models supported by eHealth can increase efficiency through defragmentation of care and promote patient-centeredness. This study aims to assess the effectiveness and cost-effectiveness of implementing a mobile health (mHealth)-enabled IC model for complex chronic patients undergoing primary total hip or knee arthroplasty. As part of the Horizon 2020 Personalized Connected Care for Complex Chronic Patients (CONNECARE) project, a prospective, pragmatic, two-arm, parallel implementation trial was conducted in the rural region of Lleida, Catalonia, Spain. For 3 months, complex chronic patients undergoing total hip or knee arthroplasty and their caregivers received the combined benefits of the CONNECARE organizational IC model and the eHealth platform supporting it, consisting of a patient self-management app, a set of integrated sensors, and a web-based platform connecting professionals from different settings, or usual care (UC). We assessed changes in health status (12-item short-form survey [SF-12]), unplanned visits and admissions during a 6-month follow-up, and the incremental cost-effectiveness ratio. A total of 29 patients were recruited for the mHealth-enabled IC arm, and 30 patients were recruited for the UC arm. Both groups were statistically comparable for baseline characteristics, such as age; sex; type of arthroplasty; and Charlson index, American Society of Anesthesiologists classification, Barthel index, Hospital Anxiety and Depression scale, Western Ontario and McMaster Universities Osteoarthritis Index, and Pfeiffer mental status questionnaire scores. Patients in both groups had significant increases in the SF-12 physical domain and total SF-12 score, but differences in differences between the groups were not statistically significant. IC patients had 50% fewer unplanned visits (P=.006). Only 1 hospital admission was recorded during the follow-up (UC arm). The IC program generated savings in different cost scenarios, and the incremental cost-effectiveness ratio demonstrated cost-effectiveness. Chronic patients undergoing hip or knee arthroplasty can benefit from the implementation of patient-centered mHealth-enabled IC models aimed at empowering patients and facilitating transitions from specialized hospital care to primary care. Such models can reduce unplanned contacts with the health system and reduce overall health costs, proving to be cost-effective. Overall, our findings support the notion of system-wide cross-organizational care pathways supported by mHealth as a successful way to implement IC for patients undergoing elective surgery.

(1) Background: Duchenne (DMD) is a rare neuromuscular disease that progressively weakens muscles, which severely impairs gait capacity. The Six Minute-Walk Test (6MWT), which is commonly used to evaluate and monitor the disease’s evolution, presents significant variability due to extrinsic factors such as patient motivation, fatigue, and learning effects. Therefore, there is a clear need for the establishment of precise clinical endpoints to measure patient mobility. (2) Methods: A novel score (6M+ and 2M+) is proposed, which is derived from the use of a new portable monitoring system capable of carrying out a complete gait analysis. The system includes several biomechanical sensors: a heart rate band, inertial measurement units, electromyography shorts, and plantar pressure insoles. The scores were obtained by processing the sensor signals and via gaussian-mixture clustering. (3) Results: The 6M+ and 2M+ scores were evaluated against the North Star Ambulatory Assessment (NSAA), the gold-standard for measuring DMD, and six- and two-minute distances. The 6M+ and 2M+ tests led to superior distances when tested against the NSAA. The 6M+ test and the 2M+ test in particular were the most correlated with age, suggesting that these scores better characterize the gait regressions in DMD. Additionally, the 2M+ test demonstrated an accuracy and stability similar to the 6M+ test. (4) Conclusions: The novel monitoring system described herein exhibited good usability with respect to functional testing in a clinical environment and demonstrated an improvement in the objectivity and reliability of monitoring the evolution of neuromuscular diseases.

Background Comprehensive assessment of integrated care deployment constitutes a major challenge to ensure quality, sustainability and transferability of both healthcare policies and services in the transition toward a coordinated service delivery scenario. To this end, the manuscript articulates four different protocols aiming at assessing large-scale implementation of integrated care, which are being developed within the umbrella of the regional project Nextcare (2016–2019), undertaken to foster innovation in technologically-supported services for chronic multimorbid patients in Catalonia (ES) (7.5 M inhabitants). Whereas one of the assessment protocols is designed to evaluate population-based deployment of care coordination at regional level during the period 2011–2017, the other three are service-based protocols addressing: i) Home hospitalization; ii) Prehabilitation for major surgery; and, iii) Community-based interventions for frail elderly chronic patients. All three services have demonstrated efficacy and potential for health value generation. They reflect different implementation maturity levels. While full coverage of the entire urban health district of Barcelona-Esquerra (520 k inhabitants) is the main aim of home hospitalization, demonstration of sustainability at Hospital Clinic of Barcelona constitutes the core goal of the prehabilitation service. Likewise, full coverage of integrated care services addressed to frail chronic patients is aimed at the city of Badalona (216 k inhabitants). Methods The population-based analysis, as well as the three service-based protocols, follow observational and experimental study designs using a non-randomized intervention group (integrated care) compared with a control group (usual care) with a propensity score matching method. Evaluation of cost-effectiveness of the interventions using a Quadruple aim approach is a central outcome in all protocols. Moreover, multi-criteria decision analysis is explored as an innovative method for health delivery assessment. The following additional dimensions will also be addressed: i) Determinants of sustainability and scalability of the services; ii) Assessment of the technological support; iii) Enhanced health risk assessment; and, iv) Factors modulating service transferability. Discussion The current study offers a unique opportunity to undertake a comprehensive assessment of integrated care fostering deployment of services at regional level. The study outcomes will contribute refining service workflows, improving health risk assessment and generating recommendations for service selection. Trials registration NCT03130283 (date released 04/06/2018), NCT03768050 (date released 12/05/2018), NCT03767387 (date released 12/05/2018).

Current brain-computer interface (BCIs) software is often tailored to the needs of scientists and technicians and therefore complex to allow for versatile use. To facilitate home use of BCIs a multifunctional P300 BCI with a graphical user interface intended for non-expert set-up and control was designed and implemented. The system includes applications for spelling, web access, entertainment, artistic expression and environmental control. In addition to new software, it also includes new hardware for the recording of electroencephalogram (EEG) signals. The EEG system consists of a small and wireless amplifier attached to a cap that can be equipped with gel-based or dry contact electrodes. The system was systematically evaluated with a healthy sample, and targeted end users of BCI technology, i.e., people with a varying degree of motor impairment tested the BCI in a series of individual case studies. Usability was assessed in terms of effectiveness, efficiency and satisfaction. Feedback of users was gathered with structured questionnaires. Two groups of healthy participants completed an experimental protocol with the gel-based and the dry contact electrodes ( = 10 each). The results demonstrated that all healthy participants gained control over the system and achieved satisfactory to high accuracies with both gel-based and dry electrodes (average error rates of 6 and 13%). Average satisfaction ratings were high, but certain aspects of the system such as the wearing comfort of the dry electrodes and design of the cap, and speed (in both groups) were criticized by some participants. Six potential end users tested the system during supervised sessions. The achieved accuracies varied greatly from no control to high control with accuracies comparable to that of healthy volunteers. Satisfaction ratings of the two end-users that gained control of the system were lower as compared to healthy participants. The advantages and disadvantages of the BCI and its applications are discussed and suggestions are presented for improvements to pave the way for user friendly BCIs intended to be used as assistive technology by persons with severe paralysis.

Background Chronic diseases are generating a major health and societal burden worldwide. Healthy lifestyles, including physical activity (PA), have proven efficacy in the prevention and treatment of many chronic conditions. But, so far, national PA surveillance systems, as well as strategies for promotion of PA, have shown low impact. We hypothesize that personalized modular PA services, aligned with healthcare, addressing the needs of a broad spectrum of individual profiles may show cost-effectiveness and sustainability. Methods The current manuscript describes the protocol for regional implementation of collaborative self-management services to promote PA in Catalonia (7.5 M habitants) during the period 2017–2019. The protocols of three implementation studies encompassing a broad spectrum of individual needs are reported. They have a quasi-experimental design. That is, a non-randomized intervention group is compared to a control group (usual care) using propensity score methods wherein age, gender and population-based health risk assessment are main matching variables. The principal innovations of the PA program are: i) Implementation of well-structured modular interventions promoting PA; ii) Information and communication technologies (ICT) to facilitate patient accessibility, support collaborative management of individual care plans and reduce costs; and iii) Assessment strategies based on the Triple Aim approach during and beyond the program deployment. Discussion The manuscript reports a precise roadmap for large scale deployment of community-based ICT-supported integrated care services to promote healthy lifestyles with high potential for comparability and transferability to other sites. Trial registration This study protocol has been registered at ClinicalTrials.org ( NCT02976064 ). Registered November 24th, 2016.

Freehand sketching is an important part of the design process that allows one to communicate in a quick and gestural way the first ideas about new concepts and is a medium for graphic thinking. It is important for architects and designers because it is a mechanism of representation, conceptualization, and abstraction for the communication between the creators and their audience. All academic courses related to industrial design include subjects aimed at acquiring skills in the use of manual tools of graphic representation, recognizing their importance in the integral training of the designer. However, sometimes the methodologies implemented in some subjects fail to develop adequately the skills of the students, who finish their studies with shortcomings in the field of graphic representation. This paper describes exercises that are part of a methodology designed to help students of industrial design acquire the skills to make an agile and effective use of freehand sketching. Through different uses of the elements of formal expression, the exercises address topics such as shape analysis, composition, light, color, and descriptive illustration. The methodology is applied experimentally in a subject of the bachelor’s degree in industrial design and product development engineering at Universitat Jaume I, introducing the students to different instruments and techniques of sketching and proposing various enriching ways of direct observation of the objectual reality that surrounds them. The paper concludes by evaluating the positive impact of the implemented methodology.

The novel BackHome system offers individuals with disabilities a range of useful services available via brain-computer interfaces (BCIs), to help restore their independence. This is the time such technology is ready to be deployed in the real world, that is, at the target end users’ home. This has been achieved by the development of practical electrodes, easy to use software, and delivering telemonitoring and home support capabilities which have been conceived, implemented, and tested within a user-centred design approach. The final BackHome system is the result of a 3-year long process involving extensive user engagement to maximize effectiveness, reliability, robustness, and ease of use of a home based BCI system. The system is comprised of ergonomic and hassle-free BCI equipment; one-click software services for Smart Home control, cognitive stimulation, and web browsing; and remote telemonitoring and home support tools to enable independent home use for nonexpert caregivers and users. BackHome aims to successfully bring BCIs to the home of people with limited mobility to restore their independence and ultimately improve their quality of life.

Background: According to the European Patient Forum, patient empowerment is the process helping people gain control over their own lives, by increasing their ability to act on issues that they themselves regard as important. Methods based solely on clinical criteria (i.e. professional training and experience) or combined with rules-based approaches (i.e. thresholds for parameters triggering pre-established decisions) constitute most of current practice. In contrast, regular usage of predictive modelling tools for clinical decision support (establishing relationships between sets of variables and outcomes, through statistical or machine learning methods) and/or patient’s support through suitable recommendations or nudges is in its infancy, despite seemingly a natural step towards customization of care. Methods: In the CONNECARE project (ID: 689802), intelligence is delivered to patients and clinicians in the form of automated, contextual, and personalized data analysis and decision making, by dedicated ICT tools: the Recommender System (RS) and three Clinical Decision Support Systems (CDSS). The RS has two goals: (i) enabling patients’ awareness regarding their compliance to prescriptions, thus of the evolution of their condition (i.e. worsening adherence to treatment), and (ii) pursue engagement of patients during treatment, thus a more active role in the process (by sending personalized messages). The goal of the CDSS is threefold: (i) deliver to clinicians risk assessment and stratification services (CDSS-risk), so as to let them focus on the most critical cases, (ii) provide geolocation services (CDSS-map) to color patients on a map depending on severity of condition (e.g., according to Charlson risk index), and existence of socio-cognitive and economic barriers to treatment (i.e., anxiety, living alone, low incomes), while suggesting optimal routes for home visits and nearby, relevant medical facilities; and (iii) assist clinicians in designing personalized clinical pathways (CDSS-path), by suggesting “templates” of the process (in the form of a workflow) to be further specialized manually. Both tools operate by constantly monitoring patients’ data (i.e., latest clinical measurements, current prescriptions) – while respecting privacy concerns – so as to feed algorithms specifically conceived so as to balance the tradeoff between (i) scientific relevance (i.e. state-of-art techniques) and (ii) clinical acceptance (i.e. validation by domain experts). Results: The CONNECARE system is a federation of subsystems each providing goal-oriented functionalities, whose main components are the Self-Management System and the Smart Adaptive Case Management system. To be smart, adaptive, and personalized, they rely on the RS and CDSS, which are now being integrated in the next release of the system, already adopted in implementation studies started in May 2018 in Lleida, Israel, and Groningen. Conclusions: Approaches to increase patient empowerment vary from patient self-management programs, to promoting patient involvement in treatment decision-making, to facilitating the physician-patient cooperation. Under the umbrella of the CONNECARE project, we defined intelligent systems aimed at providing support to patients through a recommender system and to clinicians through a combination of three clinical decision support systems.

This article describes a Digital Health Framework (DHF), benefitting from the lessons learnt during the three-year life span of the FP7 Synergy-COPD project. The DHF aims to embrace the emerging requirements - data and tools - of applying systems medicine into healthcare with a three-tier strategy articulating formal healthcare, informal care and biomedical research. Accordingly, it has been constructed based on three key building blocks, namely, novel integrated care services with the support of information and communication technologies, a personal health folder (PHF) and a biomedical research environment (DHF-research). Details on the functional requirements and necessary components of the DHF-research are extensively presented. Finally, the specifics of the building blocks strategy for deployment of the DHF, as well as the steps toward adoption are analyzed. The proposed architectural solutions and implementation steps constitute a pivotal strategy to foster and enable 4P medicine (Predictive, Preventive, Personalized and Participatory) in practice and should provide a head start to any community and institution currently considering to implement a biomedical research platform.