Introduction: Sensor-feedback systems can be used to support people after stroke during independent practice of gait. The main aim of the study was to describe the user-centred approach to (re)design the user interface of the sensor feedback system “Stappy” for people after stroke, and share the deliverables and key observations from this process. Methods: The user-centred approach was structured around four phases (the discovery, definition, development and delivery phase) which were fundamental to the design process. Fifteen participants with cognitive and/or physical limitations participated (10 women, 2/3 older than 65). Prototypes were evaluated in multiple test rounds, consisting of 2–7 individual test sessions. Results: Seven deliverables were created: a list of design requirements, a personae, a user flow, a low-, medium- and high-fidelity prototype and the character “Stappy”. The first six deliverables were necessary tools to design the user interface, whereas the character was a solution resulting from this design process. Key observations related to “readability and contrast of visual information”, “understanding and remembering information”, “physical limitations” were confirmed by and “empathy” was additionally derived from the design process. Conclusions: The study offers a structured methodology resulting in deliverables and key observations, which can be used to (re)design meaningful user interfaces for people after stroke. Additionally, the study provides a technique that may promote “empathy” through the creation of the character Stappy. The description may provide guidance for health care professionals, researchers or designers in future user interface design projects in which existing products are redesigned for people after stroke.
DOCUMENT
Purpose: The aims of this study were to investigate how a variety of research methods is commonly employed to study technology and practitioner cognition. User-interface issues with infusion pumps were selected as a case because of its relevance to patient safety. Methods: Starting from a Cognitive Systems Engineering perspective, we developed an Impact Flow Diagram showing the relationship of computer technology, cognition, practitioner behavior, and system failure in the area of medical infusion devices. We subsequently conducted a systematic literature review on user-interface issues with infusion pumps, categorized the studies in terms of methods employed, and noted the usability problems found with particular methods. Next, we assigned usability problems and related methods to the levels in the Impact Flow Diagram. Results: Most study methods used to find user interface issues with infusion pumps focused on observable behavior rather than on how artifacts shape cognition and collaboration. A concerted and theorydriven application of these methods when testing infusion pumps is lacking in the literature. Detailed analysis of one case study provided an illustration of how to apply the Impact Flow Diagram, as well as how the scope of analysis may be broadened to include organizational and regulatory factors. Conclusion: Research methods to uncover use problems with technology may be used in many ways, with many different foci. We advocate the adoption of an Impact Flow Diagram perspective rather than merely focusing on usability issues in isolation. Truly advancing patient safety requires the systematic adoption of a systems perspective viewing people and technology as an ensemble, also in the design of medical device technology.
DOCUMENT
In order to empower more people to become more selfreliant in society, interactive products and services should better match the skills and values of diverse user groups. In inclusive design, relevant end-user groups are involved early on and throughout the design and development process, leading to a better user experience. However, for IT businesses not operating in the academic domain, getting access to appropriate user research methods is difficult. This paper describes the design and prototype development of the Include Toolbox, in close cooperation with practitioners of small to medium sized enterprises (SMEs) in IT. It consists of an interactive app paired with a book. The app helps to find suitable research methods for diverse user groups such as older people, people with low literacy, and children. The book offers background information on the advantages of inclusive design, information on different user groups, and best practices shared by other companies.
DOCUMENT
Due to societal developments, like the introduction of the ‘civil society’, policy stimulating longer living at home and the separation of housing and care, the housing situation of older citizens is a relevant and pressing issue for housing-, governance- and care organizations. The current situation of living with care already benefits from technological advancement. The wide application of technology especially in care homes brings the emergence of a new source of information that becomes invaluable in order to understand how the smart urban environment affects the health of older people. The goal of this proposal is to develop an approach for designing smart neighborhoods, in order to assist and engage older adults living there. This approach will be applied to a neighborhood in Aalst-Waalre which will be developed into a living lab. The research will involve: (1) Insight into social-spatial factors underlying a smart neighborhood; (2) Identifying governance and organizational context; (3) Identifying needs and preferences of the (future) inhabitant; (4) Matching needs & preferences to potential socio-techno-spatial solutions. A mixed methods approach fusing quantitative and qualitative methods towards understanding the impacts of smart environment will be investigated. After 12 months, employing several concepts of urban computing, such as pattern recognition and predictive modelling , using the focus groups from the different organizations as well as primary end-users, and exploring how physiological data can be embedded in data-driven strategies for the enhancement of active ageing in this neighborhood will result in design solutions and strategies for a more care-friendly neighborhood.
The Dutch Environmental Vision and Mobility Vision 2050 promote climate-neutral urban growth around public transport stations, envisioning them as vibrant hubs for mobility, community, and economy. However, redevelopment often increases construction, a major CO₂ contributor. Dutch practice-led projects like 'Carbon Based Urbanism', 'MooiNL - Practical guide to urban node development', and 'Paris Proof Stations' explore integrating spatial and environmental requirements through design. Design Professionals seek collaborative methods and tools to better understand how can carbon knowledge and skills be effectively integrated into station area development projects, in architecture and urban design approaches. Redeveloping mobility hubs requires multi-stakeholder negotiations involving city planners, developers, and railway managers. Designers act as facilitators of the process, enabling urban and decarbonization transitions. CARB-HUB explores how co-creation methods can help spatial design processes balance mobility, attractiveness, and carbon neutrality across multiple stakeholders. The key outputs are: 1- Serious Game for Co-Creation, which introduces an assessment method for evaluating the potential of station locations, referred to as the 4P value framework. 2-Design Toolkit for Decarbonization, featuring a set of Key Performance Indicators (KPIs) to guide sustainable development. 3- Research Bid for the DUT–Driving Urban Transitions Program, focusing on the 15-minute City Transition Pathway. 4- Collaborative Network dedicated to promoting a low-carbon design approach. The 4P value framework offers a comprehensive method for assessing the redevelopment potential of station areas, focusing on four key dimensions: People, which considers user experience and accessibility; Position, which examines the station's role within the broader transport network; Place-making, which looks at how well the station integrates into its surrounding urban environment; and Planet, which addresses decarbonization and climate adaptation. CARB-HUB uses real cases of Dutch stations in transition as testbeds. By translating abstract environmental goals into tangible spatial solutions, CARB-HUB enables scenario-based planning, engaging designers, policymakers, infrastructure managers, and environmental advocates.
Human kind has a major impact on the state of life on Earth, mainly caused by habitat destruction, fragmentation and pollution related to agricultural land use and industrialization. Biodiversity is dominated by insects (~50%). Insects are vital for ecosystems through ecosystem engineering and controlling properties, such as soil formation and nutrient cycling, pollination, and in food webs as prey or controlling predator or parasite. Reducing insect diversity reduces resilience of ecosystems and increases risks of non-performance in soil fertility, pollination and pest suppression. Insects are under threat. Worldwide 41 % of insect species are in decline, 33% species threatened with extinction, and a co-occurring insect biomass loss of 2.5% per year. In Germany, insect biomass in natural areas surrounded by agriculture was reduced by 76% in 27 years. Nature inclusive agriculture and agri-environmental schemes aim to mitigate these kinds of effects. Protection measures need success indicators. Insects are excellent for biodiversity assessments, even with small landscape adaptations. Measuring insect biodiversity however is not easy. We aim to use new automated recognition techniques by machine learning with neural networks, to produce algorithms for fast and insightful insect diversity indexes. Biodiversity can be measured by indicative species (groups). We use three groups: 1) Carabid beetles (are top predators); 2) Moths (relation with host plants); 3) Flying insects (multiple functions in ecosystems, e.g. parasitism). The project wants to design user-friendly farmer/citizen science biodiversity measurements with machine learning, and use these in comparative research in 3 real life cases as proof of concept: 1) effects of agriculture on insects in hedgerows, 2) effects of different commercial crop production systems on insects, 3) effects of flower richness in crops and grassland on insects, all measured with natural reference situations
