2020/04/27 by Lorcan Reidy, Reidy, Lorcan, Dennis Chan +5 · 1 citation
Medicine · Neuroscience · #EEG and Brain-Computer Interfaces #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #I.2 #K.8 #Machine Learning (cs.LG) #Neurobiology of Language and Bilingualism #Technology and Human Factors in Education and Health
paper · pdf · doi:10.48550/arxiv.2005.05023
openalex publication_date 2020/04/27 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28
Cognitive training has shown promising results for delivering improvements in\nhuman cognition related to attention, problem solving, reading comprehension\nand information retrieval. However, two frequently cited problems in cognitive\ntraining literature are a lack of user engagement with the training programme,\nand a failure of developed skills to generalise to daily life. This paper\nintroduces a new cognitive training (CT) paradigm designed to address these two\nlimitations by combining the benefits of gamification, virtual reality (VR),\nand affective adaptation in the development of an engaging, ecologically valid,\nCT task. Additionally, it incorporates facial electromyography (EMG) as a means\nof determining user affect while engaged in the CT task. This information is\nthen utilised to dynamically adjust the game's difficulty in real-time as users\nplay, with the aim of leading them into a state of flow. Affect recognition\nrates of 64.1% and 76.2%, for valence and arousal respectively, were achieved\nby classifying a DWT-Haar approximation of the input signal using kNN. The\naffect-aware VR cognitive training intervention was then evaluated with a\ncontrol group of older adults. The results obtained substantiate the notion\nthat adaptation techniques can lead to greater feelings of competence and a\nmore appropriate challenge of the user's skills.\n