Affective Game Computing: A Survey

TL;DR

This survey reviews the state of affective game computing, covering affect elicitation, sensing, detection, and adaptation, and discusses methods, tools, and future research directions in this emerging field.

Contribution

It provides a comprehensive taxonomy and review of affective data collection methods, sensors, and annotation protocols in affective game computing.

Findings

Taxonomy of affective game computing methods

Overview of affect data collection techniques

Discussion of future research challenges

Abstract

This paper surveys the current state of the art in affective computing principles, methods and tools as applied to games. We review this emerging field, namely affective game computing, through the lens of the four core phases of the affective loop: game affect elicitation, game affect sensing, game affect detection and game affect adaptation. In addition, we provide a taxonomy of terms, methods and approaches used across the four phases of the affective game loop and situate the field within this taxonomy. We continue with a comprehensive review of available affect data collection methods with regards to gaming interfaces, sensors, annotation protocols, and available corpora. The paper concludes with a discussion on the current limitations of affective game computing and our vision for the most promising future research directions in the field.