Using Reaction Time, P300 and Multimodal Information to Assess "Guilty Knowledge"

Current lie detection methods, based on the polygraph technique, rely upon the measurement of several physiological characteristics to discriminate whether a truth or a lie is expressed. P300-based GKT (guilty knowledge test) has been suggested as an alternative approach for conventional polygraph technique. The purpose of this study is to evaluate RT (response time) analysis and combination of RT and ERP to identify participants possessing specific guilty knowledge. For the analysis, several previous methods were implemented and results of RT analysis and fusion ERP and RT analysis were compared which other. The accuracy of RT analysis (bootstrapped analysis of reaction time method) is 81% and AUC (area under curve) of correct detection in guilty and innocent subjects is 0.85 which are comparable to 80% accuracy of ERP analysis (Wavelet classifier method) and AUC=0.86 in previous study. Between the many fusion methods, fusion of BART and BAD method has the better accuracy and best AUC, this is superior result compared to results of previous methods from McNemar’s test point of view. These results show that brain response and behavioral response have complement information. The Fusion of BART and BAD method is combination of brain and behavioral response, therefore this proposed as best approach for Assess "Guilty Knowledge".