%0 Journal Article %J Journal of Neural Engineering %D 2018 %T The performance of 9–11-year-old children using an SSVEP-based BCI for target selection %A James J S Norton %A Jessica Mullins %A Birgit E Alitz %A Timothy Bretl %X Objective . In this paper, we report the performance of 9–11-year-old children using a steady-state visual evoked potential (SSVEP)-based brain–computer interface (BCI) and provide control data collected from adults for comparison. Children in our study achieved a much higher performance (79% accuracy; average age 9.64 years old) than the only previous investigation of children using an SSVEP-based BCI (∼50% accuracy; average age 9.86 years old). Approach . Experiments were conducted in two phases, a short calibration phase and a longer experimental phase. An offline analysis of the data collected during the calibration phase was used to set two parameters for a classifier and to screen participants who did not achieve a minimum accuracy of 85%. Main results . Eleven of the 14 children and all 11 of the adults who completed the calibration phase met the minimum accuracy requirement. During the experimental phase, children selected targets with a similar accuracy (79% for children versus 78% for adults), latency (2.1 s for children versus 1.9 s for adults), and bitrate (0.50 bits s −1 for children and 0.56 bits s −1 for adults) as adults. Significance . This study shows that children can use an SSVEP-based BCI with higher performance than previously believed and is the first to report the performance of children using an SSVEP-based BCI in terms of latency and bitrate. The results of this study imply that children with severe motor disabilities (such as locked-in syndrome) may use an SSVEP-based BCI to restore/replace the ability to communicate. %B Journal of Neural Engineering %V 15 %P 056012 %G eng %U http://stacks.iop.org/1741-2552/15/i=5/a=056012