The Turing Test is a method of testing whether a machine has human intelligence.A novel brain–computer interface(BCI)Turing Test was proposed in the BCI Controlled Robot Contest in World Robot Contest 2022.Contestant...The Turing Test is a method of testing whether a machine has human intelligence.A novel brain–computer interface(BCI)Turing Test was proposed in the BCI Controlled Robot Contest in World Robot Contest 2022.Contestants developed algorithms that can distinguish if an instruction is issued by a human.Participants collaborated with an electroencephalogram-based BCI to play a soccer game in a virtual scenario.Participants were asked to perform steady-state visual evoked potential(SSVEP)tasks or motor imagery(MI)tasks to control the robots or be in an idle state to mimic the system giving instructions on behalf of the participants.Several algorithms proposed in this competition are developed based on the concept that the idle state is a category in multiclass classification problems.This paper details the algorithms of the top five teams with the best performance in the final,lists the popular classification models and algorithms for MI and SSVEP,and discusses the effectiveness of each approach in improving classification performance and reducing the computation time.展开更多
基金supported by National Natural Science Foundation of China(Grant No.U20B2074)Key Research and Development Project of Zhejiang Province(Grant Nos.2023C03026,2021C03001,2021C03003)supported by Key Laboratory of Brain Machine Collaborative Intelligence of Zhejiang Province(Grant No.2020E10010)。
文摘The Turing Test is a method of testing whether a machine has human intelligence.A novel brain–computer interface(BCI)Turing Test was proposed in the BCI Controlled Robot Contest in World Robot Contest 2022.Contestants developed algorithms that can distinguish if an instruction is issued by a human.Participants collaborated with an electroencephalogram-based BCI to play a soccer game in a virtual scenario.Participants were asked to perform steady-state visual evoked potential(SSVEP)tasks or motor imagery(MI)tasks to control the robots or be in an idle state to mimic the system giving instructions on behalf of the participants.Several algorithms proposed in this competition are developed based on the concept that the idle state is a category in multiclass classification problems.This paper details the algorithms of the top five teams with the best performance in the final,lists the popular classification models and algorithms for MI and SSVEP,and discusses the effectiveness of each approach in improving classification performance and reducing the computation time.
