Automatic stimuli classification from ERP data for augmented communication via Brain–Computer Interfaces

作者：

Highlights：

• Automating the Event Related Potential classification ease the neuroscientist task.

• Data-driven analysis optimizes classifier’s accuracy.

• A tree structure of binary splits leads to transparent prediction models.

• 14 Event Related Potential elicited by stimuli of different nature are discerned.

摘要

•Automating the Event Related Potential classification ease the neuroscientist task.•Data-driven analysis optimizes classifier’s accuracy.•A tree structure of binary splits leads to transparent prediction models.•14 Event Related Potential elicited by stimuli of different nature are discerned.

论文关键词：Event-related potentials,Brain–computer interface,Time-series classification,Machine-learning,Features importance

论文评审过程：Received 27 March 2020, Revised 5 January 2021, Accepted 5 July 2021, Available online 10 July 2021, Version of Record 14 July 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115572