Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ability of adapting to different users is considered key to maximize the impact and effectiveness of Serious Games (SGs). Advances in neurosciences are making it possible to continuously monitor the player status.  reports the research work on the monitoring of the player flow status with a simple (4 electrode) commercial electroencephalogram (EEG). In particular,  focus on three consequential research questions: is it possible to statistically distinguish a flow from a boredom condition? For which wavelengths? Can different levels of boredom and flow be identified? Results - even if limited because of the small size of the test, are promising and enable further research. Statistically significant differences could be observed for brainwaves under various conditions. A machine learning classifier (SVM) was successful in the 2-level distinction case, in particular with personalized training.
['Aleksandr Plotnikov', 'N. Stakheika', 'Alessandro De Gloria', 'Carlotta Schatten', 'Francesco Bellotti', 'Riccardo Berta', 'Cyril Fiorini', 'Flavio Ansovini']
I am writing a research paper on a idea Exploiting Real-Time EEG Analysis for Assessing Flow in Games
[{"from": "human", "value": "I am writing a research paper on a idea Exploiting Real-Time EEG Analysis for Assessing Flow in Games"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Ability of adapting to different users is considered key to maximize the impact and effectiveness of Serious Games (SGs). Advances in neurosciences are making it possible to continuously monitor the player status.  reports the research work on the monitoring of the player flow status with a simple (4 electrode) commercial electroencephalogram (EEG). In particular,  focus on three consequential research questions: is it possible to statistically distinguish a flow from a boredom condition? For which wavelengths? Can different levels of boredom and flow be identified? Results - even if limited because of the small size of the test, are promising and enable further research. Statistically significant differences could be observed for brainwaves under various conditions. A machine learning classifier (SVM) was successful in the 2-level distinction case, in particular with personalized training."}]