Anxiety among pregnant women can significantly impact their overall well-being. However, the development of data-driven HCI interventions for this demographic is often hindered by data scarcity and collection challenges. In this study, we leverage the Empatica E4 wristband to gather physiological data from pregnant women in both resting and relaxed states. Additionally, we collect subjective reports on their anxiety levels. We integrate features from signals including Blood Volume Pulse (BVP), Skin Temperature (SKT), and Inter-Beat Interval (IBI). Employing a Support Vector Machine (SVM) algorithm, we construct a model capable of evaluating anxiety levels in pregnant women. Our model attains an emotion recognition accuracy of 69.3%, marking achievements in HCI technology tailored for this specific user group. Furthermore, we introduce conceptual ideas for biofeedback on maternal emotions and its interactive mechanism, shedding light on improved monitoring and timely intervention strategies to enhance the emotional health of pregnant women.
For over thirty years, there has been a discussion about the effectiveness of educational games in comparison to traditional learning materials. To help further this discussion, we aim to understand ‘how educational games work’ by formalising (and visualising) the educational and motivational aspects of such games. We present a model that focuses on the relationship between three different aspects: user properties, game mechanics, and learning objectives. In two example cases, we have demonstrated how the model can be used to analyse existing games and their game/instructional design, and suggest possible improvements in both motivational and educational aspects based on the model. As such, we introduce a novel approach to analysing educational games and, by inference, a novel design process for designing more effective educational games.
For over thirty years, there has been a discussion about the effectiveness of educational games in comparison to traditional learning materials. To help further this discussion, we aim to understand ‘how educational games work’ by formalising (and visualising) the educational and motivational aspects of such games. We present a model that focuses on the relationship between three different aspects: user properties, game mechanics, and learning objectives. In two example cases, we have demonstrated how the model can be used to analyse existing games and their game/instructional design, and suggest possible improvements in both motivational and educational aspects based on the model. As such, we introduce a novel approach to analysing educational games and, by inference, a novel design process for designing more effective educational games.
Mode heeft een cruciale functie in de samenleving: zij maakt diversiteit en inclusiviteit mogelijk en is een middel voor individuen om zich uit te drukken. Desalniettemin is mode ook een raadsel op het gebied van duurzaamheid, zowel aan de sociale als aan de milieukant. Er bestaan echter alternatieven voor de huidige praktijken in de mode. Dit project heeft tot doel de ontwikkeling van een van die initiatieven te ondersteunen. In samenwerking met twee Nederlandse MKB bedrijven in de mode-industrie, willen we een of meer business modellen co-designen voor het vermarkten van circulair ontworpen laser geprinte T-shirts. Door lasertechnologie te introduceren in plaats van traditionele inktopties, kunnen de T- shirts hun CO2 voetafdruk verder verkleinen en een verstandig alternatief zijn voor individuen, die op zoek zijn naar duurzame modekeuzes. Maar hoewel de technologische haalbaarheid vaststaat, vereist het vermarkten sterke, schaalbare, bedrijfsmodellen. Via een haalbaarheidsstudie willen we dergelijke businessmodellen ontwikkelen en de commercialisering van deze producten ondersteunen. Wij zijn van plan de reacties van de consument op een dergelijke innovatie te bestuderen, evenals de belemmeringen en stimulansen vanuit het oogpunt van de consument, en de inkoop-, toeleveringsketen- en financiële kwesties die kunnen voortvloeien uit de schaalbaarheid van een potentieel bedrijfsmodel. Om praktische relevantie voor de bredere industrie te verzekeren, streven we ernaar om de resultaten te presenteren op evenementen georganiseerd door een van de consortiumpartners (in 2023), als ook om een teaching case en een wetenschappelijk artikel te ontwikkelen op basis van de resultaten van het project.
The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.
Every year in the Netherlands around 10.000 people are diagnosed with non-small cell lung cancer, commonly at advanced stages. In 1 to 2% of patients, a chromosomal translocation of the ROS1 gene drives oncogenesis. Since a few years, ROS1+ cancer can be treated effectively by targeted therapy with the tyrosine kinase inhibitor (TKI) crizotinib, which binds to the ROS1 protein, impairs the kinase activity and thereby inhibits tumor growth. Despite the successful treatment with crizotinib, most patients eventually show disease progression due to development of resistance. The available TKI-drugs for ROS1+ lung cancer make it possible to sequentially change medication as the disease progresses, but this is largely a ‘trial and error’ approach. Patients and their doctors ask for better prediction which TKI will work best after resistance occurs. The ROS1 patient foundation ‘Stichting Merels Wereld’ raises awareness and brings researchers together to close the knowledge gap on ROS1-driven oncogenesis and increase the options for treatment. As ROS1+ lung cancer is rare, research into resistance mechanisms and the availability of cell line models are limited. Medical Life Sciences & Diagnostics can help to improve treatment by developing new models which mimic the situation in resistant tumor cells. In the current proposal we will develop novel TKI-resistant cell lines that allow screening for improved personalized treatment with TKIs. Knowledge of specific mutations occurring after resistance will help to predict more accurately what the next step in patient treatment could be. This project is part of a long-term collaboration between the ROS1 patient foundation ‘Stichting Merels Wereld’, the departments of Pulmonary Oncology and Pathology of the UMCG and the Institute for Life Science & Technology of the Hanzehogeschool. The company Vivomicx will join our consortium, adding expertise on drug screening in complex cell systems.
