| Conference | 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC), October 11-14, 2020, Toronto, ON, Canada |
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| Abstract | Cognitive decline in aging is a pressing issue that can lead to long term functional impairments, including dementia. Computer-based cognitive training applications have been shown to improve cognitive skills, however, they often lack ecological validity. Researchers have proposed the use of Brain-Machine interface (BMI) systems as cognitive training tools but still face the limitation that the user cannot move freely while performing the cognitive training. Previously, we reported the successful use of a BMI system with a physical robotic third arm that allowed users to do multitasking by doing two tasks simultaneously, thereby engaging multiple cognitive skills such as attention switching, mental focus, coordination, decision making and visual information processing. In this paper, we present a cognitive training platform based on our previous multitasking paradigm with a BMI enhanced with a virtual reality (VR) experience. We conducted an experiment to investigate the efficiency of the proposed platform and monitored the level of accuracy and processing speed of the attention switching skill and compared to the traditional Attention Switching Task (AST) cognitive training paradigm. Preliminary experimental results showed that mean difference in attention accuracy scores were 3.96 s faster for the BMI-VR group compared to the AST group. Although there was a high degree of intersubject variability making the result not statistically significant, preliminary evidence reflects a potential for the proposed training approach to improve attention switching speed. |
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