@article {4144,
	title = {The performance of 9{\textendash}11-year-old children using an SSVEP-based BCI for target selection},
	journal = {Journal of Neural Engineering},
	volume = {15},
	year = {2018},
	pages = {056012},
	abstract = {Objective . In this paper, we report the performance of 9{\textendash}11-year-old children using a steady-state visual evoked potential (SSVEP)-based brain{\textendash}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.},
	url = {http://stacks.iop.org/1741-2552/15/i=5/a=056012},
	author = {James J S Norton and Jessica Mullins and Birgit E Alitz and Timothy Bretl}
}
