Research On Parallel Mental Workload Task And Hybrid Brain-Computer Interface And Interactions Between Them

Brain–computer interfaces(BCIs),which allow individuals to communicate independently of the brain's normal output pathways of peripheral nerves and muscles.The current BCI technology has been able to achieve reliable decoding and transformation of mental information,and has gradually entered clinical application.However,as a new interactive tool,there are many factors affecting the system efficiency and user experience,which put forward new requirements for the development of BCI technology.This paper aimed at the parallel mental workload task and hybrid BCI system,investigated the influence of parallel task on steady-state visual evoked potential(SSVEP)-based BCIs,designed the asynchronous strategy on hybrid BCIs,and further discussed the influence of parallel tasks on the hybrid BCIs.In this study,we firstly explored the effects of parallel mental workload on SSVEP-BCIs,with 15 subjects completed SSVEP-BCI and parallel n-back mental workload tasks.Results revealed that the recognition accuracy of SSVEP-BCI was significantly impaired by the parallel task,and the average accuracy across all subjects dropped by 8.67% at most from 1-to 4-back.The subjects whose accuracy was clearly influenced by mental workload also exhibited a clear decline in SSVEP features under mental workload conditions.Moreover,results indicated that the influence of parallel task on SSVEP-BCIs was weaker than that on traditional P300-BCIs.The study designed an asynchronous strategy for P300 and SSVEP blocking(SSVEP-B)-based hybrid BCI.Through the establishment of control and idle state models and twice discriminations,the strategy realized the estimation of post probability and asynchronous discrimination by decision confidence on multiple rounds of EEG data.The online 36-character-set hybrid BCI experiments were developed on 10 subjects,and the average accuracy of asynchronous classification was 83.8%,the average information transfer rate reached 43.2bit/min.Results suggested that the proposed strategy was effective.Finally,experiments were developed to investigate the influence of parallel mental workload task on hybrid BCIs.14 subjects parallelly completed n-back tasks and hybrid P300+SSVEP-B BCIs,which output set involved 36 characteristics.Results showed that the accuracy of hybrid BCIs reduced significantly when subjects under high level parallel task conditions.But the accuracy difference between 1-and 3-back tasks was only 2%,lower than that on traditional P300-BCI.It proved that the hybrid BCI system has stronger robustness to the parallel mental task.In this paper,the parallel task and hybrid BCIs were studied.The results of the study improved stability of the BCI system and laid a solid technical foundation for user experience on BCIs.