The application of psychophysiology in human-computer interaction is a growing field with significant potential for future smart personalised systems. Working in this emerging field requires comprehension of an array of physiological signals and analysis techniques. This paper focuses on the aggregation of multiple physiological measurements, obtained from one or more sensors. This approach requires the classification of relatively large samples of multidimensional data, which must be associated to specific cognitive or affective states. Researchers generally attempt to solve this problem by utilising machine learning techniques. We present a short review to serve as a primer for the novice, enabling rapid familiarisation with the latest core concepts. We put special emphasis on work-related human-computer interface applications to distinguish from the more common clinical or sports uses of psychophysiology. This paper is an extract from a comprehensive review of the entire field of ambulatory psychophysiology, including 12 similar chapters, plus application guidelines and systematic review. Thus any citation should be made using the following reference: B. Cowley, M. Filetti, K. Lukander, J. Torniainen, A. Henelius, L. Ahonen, O. Barral, I. Kosunen, T. Valtonen, M. Huotilainen, N. Ravaja, G. Jacucci. The Psychophysiology Primer: a guide to methods and a broad review with a focus on human-computer interaction. Foundations and Trends in Human-Computer Interaction, vol. 9, no. 3-4, pp. 150--307, 2016.