Lie detection based EEG-P300 signal classified by ANFIS method

In this paper,the differences in brain signal activity (eeg-p300 component) which detects whether a person is telling the truth or lying is explored. brain signal activity is monitored when they are first respond to a given experiment stimulus. in the experiment,twelve subjects whose age are around 19 ± 1 years old were involved. in the signal processing,the recorded brain signals were filtered and extracted using bandpass filter and independent component analysis,respectively. furthermore,the extracted signals were classified with adaptive neuro-fuzzy inference system method. the results show that a huge spike of the eeg-p300 amplitude on a lying subject correspond to the appeared stimuli is achieved. the findings of these experiments have been promising in testing the validity of using an eeg-p300 as a lie detector.