A Comparison of cVEP-Based BCI-Performance Between Different Age Groups

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Abstract

Persons who need assistive technologies to communicate with the relatives, for example amyotrophic lateral sclerosis (ALS) patients, could benefit from Brain-Computer Interface (BCI) technology if it is used alternatively or in addition to established communication tools. BCIs based on visual evoked potentials (VEPs) have shown high system speeds in many studies. However, some major issues need to be addressed: On the one hand, the strength of VEP responses varies across subjects. Especially age-related performance differences have been covered in several studies and need to be investigated further. On the other hand, the stimuli used to evoke the VEP response, are considered annoying for many people. This paper investigates the subjective level of annoyance in different age groups for different flickering rates as well as age-related performance differences in cVEP based BCIs. In this regard, the cVEP-based eight target spelling interface was tested with two age groups (13 subjects each, ranging from 20 to 28 years and 62 to 83 years). Typically, 60 Hz monitor refresh rate is used to generate the cVEP stimuli. Here, three different flickering speeds were tested (m-sequences generated using refresh rates of 30, 60 and 120 Hz for stimuli presentation). The mean ITR of the elderly age group was 42.03, 45.32 and 45.75 bits per minute (bpm) while the young group achieved an ITR of 53.09, 64.01 and 72.92 bpm for the 30, 60 and 120 Hz setups. The difference was significant for the faster flickering setups (60 and 120 Hz), respectively. Hence, our results show that elderly people have slightly worse BCI performance in terms of information transfer rate (ITR). Regarding the level of annoyance, subjects from both age groups preferred the 120 Hz setup which offered a more subtle visual stimulation.

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APA

Gembler, F., Stawicki, P., Rezeika, A., & Volosyak, I. (2019). A Comparison of cVEP-Based BCI-Performance Between Different Age Groups. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11506 LNCS, pp. 394–405). Springer Verlag. https://doi.org/10.1007/978-3-030-20521-8_33

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