Analysis of galvanic skin responses with principal components and clustering techniques

An advanced method for analyzing the patterning of successive galvanic skin responses (GSR) is presented. The proposed method is based on principal component analysis in which the vector containing the measured signal is presented as a weighted sum of orthogonal basis vectors. The method is tested using measurements from 20 healthy controls and 13 psychotic patients. For each subject, 11 surprising auditory stimuli were delivered to right ear at irregular intervals and evoked GSRs were recorded from the hand. For most of the healthy controls, there was a clear pattern in successive GSRs, whereas within psychotic patients the lack of time-locking of GSRs seemed to be characteristical. These between group differences can be revealed by the proposed method. With application to clustering a significant discrimination, with overall correct ratings of 82%, of healthy controls and psychotic patients is achieved. A significant fact is that all patients were ranked correctly giving the proposed method a sensitivity of 100%.