Research On The Brain-computer Interface For Brain-hands Cooperative Control In Multi-tasking

Brain-computer interface(BCI),which can interact with the external environment by detecting the brain’s nerve signals without using muscle tissue and peripheral nerves.As a new type of human-computer interaction method,most of the current BCI research focuses on how to use BCI to improve the external interaction ability of patients or disabled people.The value of BCI for healthy people remains to be explored.When healthy people perform a task,his hands are constantly occupied with operations to complete external interaction,and BCI can provide an additional “hand” to cope with more tasks for operators under multitasking to improve the efficiency of external interaction.Regarding the challenges above,the following studies were carried out in this paper.First,the feasibility of using steady-state visual evoked potential-based BCI(SSVEP-BCI)to provide additional “hands” for operators with hands fully occupied was explored.Multi-Attribute Task Battery II(MATB)was used as multi-tasking,and the influences between multitasking and SSVEP-BCI were analyzed.10 healthy subjects participated in this experiment.The result showed that there was no significant interaction between the multitasking and SSVEP-BCI,which indicated that the feasibility of using SSVEP-BCI combined with multi-tasking.Secondly,in order to achieve the BCI method which can respond to random events,this paper designed a method of stimulus coding and decoding,which named continuous-flashing SSVEP-BCI(c SSVEP-BCI).And we explored the performance of c SSVEP-BCI under multi-tasking.At the same time,we explored the effects of training on the use of the system by subjects.18 healthy subjects participated in this experiment.c SSVEP-BCI was used under multi-tasking,the average recognition accuracy rate of93.44% was achieved when EEG data length was 1 s,and the effectiveness of this method was verified.In addition,the average recognition accuracy rate of BCI in c SSVEP-BCI combined with multi-tasking was increased by 15.43% after training.This result showed that the training can improve the recognition accuracy of c SSVEPBCI,thus improving the efficiency of joint multi-tasking.Finally,an online game task of brain-hands cooperative control was designed to simulate the situation that both hands were occupied with continuous tasks while using SSVEP-BCI for auxiliary operation.10 healthy subjects participated in this experiment.When a random event is encountered in the game,more instructions are implemented without affecting the two-handed task by using c SSVEP-BCI.The effectiveness of the c SSVEP-BCI combined with the hands was verified.This paper studied the BCI for brain-hands cooperative control in multi-tasking and analyzed the interaction between two-handed tasks and SSVEP-BCI by exploring the implementation method of SSVEP-BCI combined with the two-handed multi-task operation.Further verifying the feasibility of using SSVEP-BCI to achieve brain-hands cooperative control in multi-tasking.The results of this study provide new ideas for BCI application in health.