Full-body motion-based game interaction for older adults

Older adults in nursing homes often lead sedentary lifestyles, which reduces their life expectancy. Full-body motion-control games provide an opportunity for these adults to remain active and engaged; these games are not designed with age-related impairments in mind, which prevents the games from being leveraged to increase the activity levels of older adults. In this paper, we present two studies aimed at developing game design guidelines for full-body motion controls for older adults experiencing age-related changes and impairments. Our studies also demonstrate how full-body motion-control games can accommodate a variety of user abilities, have a positive effect on mood and, by extension, the emotional well-being of older adults. Based on our studies, we present seven guidelines for the design of full-body interaction in games. The guidelines are designed to foster safe physical activity among older adults, thereby increasing their quality of life. Copyright 2012 ACM

Assessing the adaptation of arable farmers to climate change using DEA and bio-economic modelling

The objective of this article is to assess the impact of climate change on arable farming systems in Flevoland (the Netherlands) and to explore the adoption of different adaptation strategies. Data Envelopment Analysis (DEA) is applied that uses empirical data from individual farms to identify “best” current farm practices and derive relationships regarding current farm managemen

Adapting agriculture in 2050 in Flevoland; perspectives from stakeholders

Although recently more research has gone into farm level studies, little attention has been given to the variety of responses of farmers, considering their characteristics, objectives and the socio-economic, technological and political contexts (Reidsma et al, 2010). In the Agri-Adapt project we focus on farm level adaptation within an agricultural region considering the socio-economic context of 2050

Climate change adaptation in agriculture; the use of multi-scale modelling and stakeholder participation in the Netherlands

Abstract about a research project to develop a methodology to assess adaptation of agriculture to climatic and socio-economic changes at multiple scales, with a first application in the Province of Flevoland, the Netherlands

Enhanced esports: Community perspectives on performance enhancers in competitive gaming

This work explores perceptions of performance enhancer usage in esports. Specifically, we explored the perception of: food and food supplements; non-medical use of prescription drugs; drugs with some social acceptance (e.g. alcohol, nicotine, cannabis); drugs with lower social acceptance (e.g., psychedelics, opioids); and non-invasive brain stimulation (e.g. transcranial direct current stimulation). A mixed-methods approach was used to triangulate findings around three data sets, including both prompted and unprompted online forum comments, as well as survey data. The studies evidence that players are willing to use or are already using enhancers to increase their in-game performance, and that players are generally concerned about the use of enhancers in professional esports contexts. Furthermore, the community perceives that a substantial number of e-athletes use enhancers. The core contribution of this work is a comprehensive investigation into perspectives of esports performance enhancement, which highlights the urgent need for further research, as well as regulation by esports leagues

Multi-score Learning for Affect Recognition: the Case of Body Postures

An important challenge in building automatic affective state recognition systems is establishing the ground truth. When the groundtruth is not available, observers are often used to label training and testing sets. Unfortunately, inter-rater reliability between observers tends to vary from fair to moderate when dealing with naturalistic expressions. Nevertheless, the most common approach used is to label each expression with the most frequent label assigned by the observers to that expression. In this paper, we propose a general pattern recognition framework that takes into account the variability between observers for automatic affect recognition. This leads to what we term a multi-score learning problem in which a single expression is associated with multiple values representing the scores of each available emotion label. We also propose several performance measurements and pattern recognition methods for this framework, and report the experimental results obtained when testing and comparing these methods on two affective posture datasets

Future projections of biodiversity and ecosystem services in Europe with two integrated assessment models

Projections of future changes in biodiversity and ecosystem services (BES) are of increasing importance to inform policy and decision-making on options for conservation and sustainable use of BES. Scenario-based modelling is a powerful tool to assess these future changes. This study assesses the consequences for BES in Europe under four socio-environmental scenarios designed from a BES perspective. We evaluated these scenarios using two integrated assessment models (IMAGE-GLOBIO and CLIMSAVE IAP, respectively). Our results showed that (i) climate and land use change will continue to pose significant threats to biodiversity and some ecosystem services, even in the most optimistic scenario; (ii) none of the four scenarios achieved overall preservation of BES in Europe; and (iii) targeted policies (e.g. on climate change, biodiversity conservation and sustainable land management) and behavioural change (e.g. reducing meat consumption, water-saving behaviour) reduced the magnitude of BES loss. These findings stress the necessity of more ambitious policies and actions if BES in Europe are to be safeguarded. We further found that the multi-modelling approach was critical to account for complementary BES dimensions and highlighted different sources of uncertainties (e.g. related to land use allocation, driving forces behind BES changes, trade assumptions), which facilitated nuanced and contextualised insights with respect to possible BES futures

Exploring adaptation strategies for climate change in the Netherlands: a bio-economic farm level analysis

PowerPoint presentation given at the European meeting of the international Microsimulation Association, Dublin, 17-19 May 2012

Design of a fuzzy affective agent based on typicality degrees of physiological signals

Conference paper presented at International Conference on Information Processing and Management in July 2014Physiology-based emotionally intelligent paradigms provide an opportunity to enhance human computer interactions by continuously evoking and adapting to the user experiences in real-time. However , there are unresolved questions on how to model real- time emotionally intelligent applications through mapping of physiological patterns to users ' affective states. In ·this study, we consider an approach for design of fuzzy affective agent based on the concept of typicality. We propose the use of typicality degrees of physiological patterns to construct the fuzzy rules representing the continuous transitions of user 's affective states. The approach was tested· on experimental data in which physiological measures were recorded on players involved in an action game to characterize various gaming experiences . We show that , in addition to exploitation of the results to characterize users ' affective states through .typicality degrees, this approach is a systematic way to automatically define fuzzy rules from experimental data for an affective agent to be used in real -time continuous assessment of user's affective states.Physiology-based emotionally intelligent paradigms provide an opportunity to enhance human computer interactions by continuously evoking and adapting to the user experiences in real-time. However , there are unresolved questions on how to model real- time emotionally intelligent applications through mapping of physiological patterns to users ' affective states. In ·this study, we consider an approach for design of fuzzy affective agent based on the concept of typicality. We propose the use of typicality degrees of physiological patterns to construct the fuzzy rules representing the continuous transitions of user 's affective states. The approach was tested· on experimental data in which physiological measures were recorded on players involved in an action game to characterize various gaming experiences . We show that , in addition to exploitation of the results to characterize users ' affective states through .typicality degrees, this approach is a systematic way to automatically define fuzzy rules from experimental data for an affective agent to be used in real -time continuous assessment of user's affective states