Facial Electromyography-based Adaptive Virtual Reality Gaming for Cognitive Training
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As life expectancy rises, age-related diseases causing dementia become more prevalent. In line with this, the health economic impact of dementia is escalating to unsustainable levels, with estimates that by 2050 dementia care will cost an annual 1 trillion in the US alone. The development of interventions capable of improving cognition therefore represents an issue of the highest priority for healthcare. There has been considerable focus on cognitive training (CT) in particular, but work to date has been limited by two main factors, namely (i) the lack of transferability of CT gains to real life activities, and (ii) the lack of adherence to CT programmes. This paper will outline a new CT paradigm designed to offset these two limitations. This is achieved by combining the benefits of gamification, virtual reality (VR), and affective adaptation in the development of an engaging, ecologically valid, CT task. Additionally, it incorporates facial electromyography (EMG) as a means of determining user emotional state while engaged in the CT task. This information is then utilised to dynamically adjust the game's difficulty in real-time as users play, with the aim of leading them into a state of flow. Emotion recognition rates of 64.1 were achieved by classifying a DWT-Haar approximation of the input signal using kNN. The affect-aware VR cognitive training intervention was then evaluated with a control group of older adults. The results obtained substantiated the notion that adaptation techniques can lead to greater feelings of competence thereby increasing intrinsic motivation for the activity, and a more appropriate challenge of the user's skills.
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