Analysis Of Multiple Physiological Sensor Data

Physiological measures offer many benefits to psychological research including objective, non-intrusive assessment of affective and cognitive states. However, this utility is limited by analysis techniques available for testing data recorded by multiple physiological sensors. The present paper presents one set of data that was attained from a repeated measures design with a nominal independent variable for analysis. Specifically, the International Affective Picture System (IAPS; Lang, Bradley, & Cuthbert, 2008), a series of images known to convey seven different emotions, was presented to participants while measures of their neurological activity (Electroencephalogram; EEG), heart rate (Electrocardiogram; ECG), skin conductance (Galvanic Skin Respond; GSR), and pupillary response were taken. Subsequently, a discussion of statistics available for analyzing responses attained from the various sensors is presented. Such statistics include correlation, ANOVA, MANOVA, regression, and discriminant function analysis. The details on design limitations are addressed and recommendations are given for employing each statistical option. © 2011 Springer-Verlag