Short-Term Effects of the Serious Game "Fit, Food, Fun" on Nutritional Knowledge: A Pilot Study among Children and Adolescents

"Serious games" are a novel and entertaining approach for nutritional education. The aim of this pilot study was to evaluate the short-term effectiveness of "Fit, Food, Fun" (FFF), a serious game to impart nutritional knowledge among children and adolescents. Data collection was conducted at two secondary schools in Bavaria, Germany. The gameplay intervention (gameplay group; GG) consisted of a 15-minute FFF gameplay session during each of three consecutive days. The teaching intervention (teaching group; TG) was performed in a classic lecture format. Nutritional knowledge was evaluated via questionnaires at baseline and post-intervention. Statistical analyses were performed using R (R Core Team, 2018). In total, baseline data were available for 39 participants in the GG and 44 participants in the TG. The mean age was 13.5 +/- 0.7 years in the GG and 12.8 +/- 0.9 years in the TG. There was a significant (p-value < 0.001) improvement in nutritional knowledge in both intervention groups. Moreover, a between-group difference with a significantly (p-value = 0.01) higher increase in nutritional knowledge was detected for the TG. This pilot study provides evidence for the short-term effectiveness of both educational interventions on the improvement in nutritional knowledge. Finally, the FFF game might be an adequate educational tool for the transfer of nutritional knowledge among children and adolescents

Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP).1 At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project) and from the European Unions Horizon 2020 Research and Innovation Programme under Grant Agreement No. 720270 (HBP SGA1)

EnvSLAM: Combining SLAM Systems and Neural Networks to Improve the Environment Fusion in AR Applications

Augmented Reality (AR) has increasingly benefited from the use of Simultaneous Localization and Mapping (SLAM) systems. This technology has enabled developers to create AR markerless applications, but lack semantic understanding of their environment. The inclusion of this information would empower AR applications to better react to the surroundings more realistically. To gain semantic knowledge, in recent years, focus has shifted toward fusing SLAM systems with neural networks, giving birth to the field of Semantic SLAM. Building on existing research, this paper aimed to create a SLAM system that generates a 3D map using ORB-SLAM2 and enriches it with semantic knowledge originated from the Fast-SCNN network. The key novelty of our approach is a new method for improving the predictions of neural networks, employed to balance the loss of accuracy introduced by efficient real-time models. Exploiting sensor information provided by a smartphone, GPS coordinates are utilized to query the OpenStreetMap database. The returned information is used to understand which classes are currently absent in the environment, so that they can be removed from the network’s prediction with the goal of improving its accuracy. We achieved 87.40% Pixel Accuracy with Fast-SCNN on our custom version of COCO-Stuff and showed an improvement by involving GPS data for our self-made smartphone dataset resulting in 90.24% Pixel Accuracy. Having in mind the use on smartphones, the implementation aimed to find a trade-off between accuracy and efficiency, making the system achieve an unprecedented speed. To this end, the system was carefully designed and a strong focus on lightweight neural networks is also fundamental. This enabled the creation of an above real-time Semantic SLAM system that we called EnvSLAM (Environment SLAM). Our extensive evaluation reveals the efficiency of the system features and the operability in above real-time (48.1 frames per second with an input image resolution of 640 × 360 pixels). Moreover, the GPS integration indicates an effective improvement of the network’s prediction accuracy

Short-Term Effects of the Serious Game “Fit, Food, Fun” on Nutritional Knowledge: A Pilot Study among Children and Adolescents

&ldquo;Serious games&rdquo; are a novel and entertaining approach for nutritional education. The aim of this pilot study was to evaluate the short-term effectiveness of &ldquo;Fit, Food, Fun&rdquo; (FFF), a serious game to impart nutritional knowledge among children and adolescents. Data collection was conducted at two secondary schools in Bavaria, Germany. The gameplay intervention (gameplay group; GG) consisted of a 15-minute FFF gameplay session during each of three consecutive days. The teaching intervention (teaching group; TG) was performed in a classic lecture format. Nutritional knowledge was evaluated via questionnaires at baseline and post-intervention. Statistical analyses were performed using R (R Core Team, 2018). In total, baseline data were available for 39 participants in the GG and 44 participants in the TG. The mean age was 13.5 &plusmn; 0.7 years in the GG and 12.8 &plusmn; 0.9 years in the TG. There was a significant (p-value &lt; 0.001) improvement in nutritional knowledge in both intervention groups. Moreover, a between-group difference with a significantly (p-value = 0.01) higher increase in nutritional knowledge was detected for the TG. This pilot study provides evidence for the short-term effectiveness of both educational interventions on the improvement in nutritional knowledge. Finally, the FFF game might be an adequate educational tool for the transfer of nutritional knowledge among children and adolescents

Serious Games for Nutritional Education: Online Survey on Preferences, Motives, and Behaviors Among Young Adults at University

Background: Data on nutritional information and digital gameplay are limited among young adults in Germany. Objective: This survey aimed to gather data on nutritional information sources and digital games for nutritional education (preferences, motives, and behaviors) among young adults at both Munich universities in Germany. Methods: An online survey was developed by an multidisciplinary research group using EvaSys, an in-house survey software. The questionnaire (47 items) covered questions about baseline characteristics (eg, housing situation and weight), nutrition (eg, nutritional information sources), and digital (nutritional) gameplay (eg, preferences, motives, and behaviors). A feedback field was also provided. This publication is based on a selection of 20 questions (7 baseline characteristics, 2 nutrition, 11 gameplay). Young adults, primarily Munich university students aged from 18 to 24 years, were invited to participate by digital and nondigital communication channels between 2016 and 2017. Statistical analyses were performed using Excel 2013 (Microsoft Corp) and R version 3.1.3 (R Foundation for Statistical Computing). Results: In total, 468 young adults (342/468, 73.1% women; 379/468, 81.0% university students) participated. Most of the participants (269/468, 57.5%) were aged 18 to 24 years with a BMI in the normal weight range (346/447, 77.4%). Mean body weight was 65.5 [SD 14.0] kg. Most participants reported getting nutritional information from the internet (372/467, 79.7%) and printed media (298/467, 63.8%), less than 1.0% (2/467, 0.4%) named digital games. Apps (100/461, 21.7%) and university/workplace (146/461, 31.7%) were the most desired sources for additional information about nutrition, while 10.0% (46/461, 10.0%) of participants stated wanting digital games. Almost two-thirds (293/468, 62.6%) of participants played digital games, while one-fifth (97/456, 21.3%) played digital games daily using smartphones or tablets. Finally, most respondents (343/468, 73.3%), mainly women, expressed interest in obtaining nutritional information during digital gameplay. However, significant gender differences were shown for nutritional acquisition behaviors and digital gameplay preferences, motives, and behaviors. Conclusions: Our survey population reported playing digital games (especially men) and wanting nutritional information during digital gameplay (especially women). Furthermore, university or workplace are named as preferred settings for nutritional information. Therefore, a digital game app might have the potential to be a tool for nutritional education among young adults within the university or workplace environment

Serious Games for Nutritional Education: Online Survey on Preferences, Motives, and Behaviors Among Young Adults at University

Background: Data on nutritional information and digital gameplay are limited among young adults in Germany. Objective: This survey aimed to gather data on nutritional information sources and digital games for nutritional education (preferences, motives, and behaviors) among young adults at both Munich universities in Germany. Methods: An online survey was developed by an multidisciplinary research group using EvaSys, an in-house survey software. The questionnaire (47 items) covered questions about baseline characteristics (eg, housing situation and weight), nutrition (eg, nutritional information sources), and digital (nutritional) gameplay (eg, preferences, motives, and behaviors). A feedback field was also provided. This publication is based on a selection of 20 questions (7 baseline characteristics, 2 nutrition, 11 gameplay). Young adults, primarily Munich university students aged from 18 to 24 years, were invited to participate by digital and nondigital communication channels between 2016 and 2017. Statistical analyses were performed using Excel 2013 (Microsoft Corp) and R version 3.1.3 (R Foundation for Statistical Computing). Results: In total, 468 young adults (342/468, 73.1% women; 379/468, 81.0% university students) participated. Most of the participants (269/468, 57.5%) were aged 18 to 24 years with a BMI in the normal weight range (346/447, 77.4%). Mean body weight was 65.5 [SD 14.0] kg. Most participants reported getting nutritional information from the internet (372/467, 79.7%) and printed media (298/467, 63.8%), less than 1.0% (2/467, 0.4%) named digital games. Apps (100/461, 21.7%) and university/workplace (146/461, 31.7%) were the most desired sources for additional information about nutrition, while 10.0% (46/461, 10.0%) of participants stated wanting digital games. Almost two-thirds (293/468, 62.6%) of participants played digital games, while one-fifth (97/456, 21.3%) played digital games daily using smartphones or tablets. Finally, most respondents (343/468, 73.3%), mainly women, expressed interest in obtaining nutritional information during digital gameplay. However, significant gender differences were shown for nutritional acquisition behaviors and digital gameplay preferences, motives, and behaviors. Conclusions: Our survey population reported playing digital games (especially men) and wanting nutritional information during digital gameplay (especially women). Furthermore, university or workplace are named as preferred settings for nutritional information. Therefore, a digital game app might have the potential to be a tool for nutritional education among young adults within the university or workplace environment