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Bioelectric signals can improve assessment in videogames by helping to better understand user experience, evaluate attention, or study the cognitive and physical effects of games. Use of signals is therefore relevant to better evaluate and understand the impact and effects of videogames on players, and specially so in the field of serious games, such as educational or training games, to gain insights into the learning processes; or in games for health to better evaluate non-conscious effects on the player's body. We examine how biological signals (bioelectric + eye-tracking) are being used and collected in the field of video games, including the choice of signals, the devices used to collect them (e.g., wearables), the purposes for which they are collected, and the results reported from their use. As a result of this systematic literature review, 81 articles have been analyzed, finding that electrocardiograms and encephalograms are the most frequently used signals. The main use of these bioelectrical signals is to evaluate player engagement, level of difficulty, and stress during the gameplay. But there are also examples where signals are used to detect health problems, or as evidence to compare educational games with other learning activities. This review informs researchers interested in better understanding the benefits and limitations of biological signals for video games, providing an overview of studies conducted in recent years and the associated devices described in those studies. Limitations in this field include signal noise issues as well as the amount of time required to calibrate the devices during experiments, adding to the complexity of user testing. It is necessary to work on tools that facilitate experiments with large groups of users in parallel as well as to work on open software and low-cost devices that allow the emergence of a greater number of studies in this field, given for example their potential in the field of educational games to better understand the learning processes of users.
Bioelectric signals can improve assessment in videogames by helping to better understand user experience, evaluate attention, or study the cognitive and physical effects of games. Use of signals is therefore relevant to better evaluate and understand the impact and effects of videogames on players, and specially so in the field of serious games, such as educational or training games, to gain insights into the learning processes; or in games for health to better evaluate non-conscious effects on the player's body. We examine how biological signals (bioelectric + eye-tracking) are being used and collected in the field of video games, including the choice of signals, the devices used to collect them (e.g., wearables), the purposes for which they are collected, and the results reported from their use. As a result of this systematic literature review, 81 articles have been analyzed, finding that electrocardiograms and encephalograms are the most frequently used signals. The main use of these bioelectrical signals is to evaluate player engagement, level of difficulty, and stress during the gameplay. But there are also examples where signals are used to detect health problems, or as evidence to compare educational games with other learning activities. This review informs researchers interested in better understanding the benefits and limitations of biological signals for video games, providing an overview of studies conducted in recent years and the associated devices described in those studies. Limitations in this field include signal noise issues as well as the amount of time required to calibrate the devices during experiments, adding to the complexity of user testing. It is necessary to work on tools that facilitate experiments with large groups of users in parallel as well as to work on open software and low-cost devices that allow the emergence of a greater number of studies in this field, given for example their potential in the field of educational games to better understand the learning processes of users.
Global refugee crisis around the world has displaced millions of people from their homes. Although some of them adjust well, many suffer from significant psychological distress, such as post-traumatic stress disorder (PTSD), owing to exposure to traumatic events and hardships. Here, diagnosis and access to psychological health care present particular challenges for various human-centered design issues. Therefore, analyzing the case of Rohingya refugees in Bangladesh, we propose a two-way diagnosis of PTSD using (i) short inexpensive questionnaire to determine its prevalence, and (ii) low-cost portable EEG headset to identify potential neurobiological markers of PTSD. To the best of our knowledge, this study is the first to use consumer-grade EEG devices in the scarce-resource settings of refugees. Moreover, we explored the underlying structure of PTSD and its symptoms via developing various hybrid models based on Bayesian inference by combining aspects from both reflective and formative models of PTSD, which is also the first of its kind. Our findings revealed several key components of PTSD and its neurobiological abnormality. Moreover, challenges faced during our study would inform design processes of screening tools and treatments of PTSD to incorporate refugee experience in a more meaningful way during contemporary and future humanitarian crisis.
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