Coupling Interaction and Physiological Metrics for Interaction Adaptation

Abstract

Abstract. We present an adaptation system whose goal is to provide users with interaction experiences tailored to their current physiological status and performance. The system captures emotion, motion and application related metrics to proactively adjust the available interaction patterns. Interacting in different environments -stationary/mobile -or under different emotional status -relaxed/stressed-can affect performance, engagement and enjoyment. This contribution describes the initial design steps in the creation of an interaction adaptation engine.Keywords: Physiological Signals, Adaptation, User Performance. MotivationPhysiological user interfaces are typically employed to perceive real body signals from users, while utilizing that information during the interaction period [7]. These interfaces are mainly used to determine motion [2] (through muscle tension detection, video capture or accelerometers) or emotion [6] (through skin conductivity or heart rate variance). Human beings are capable of expressing both observable (e.g. blushing, frowning, etc.) and concealed (e.g. increasing heart beat rate, altering body temperature, etc.) reactions to certain events. While analysts and the most recurrently used mechanisms are able to retrieve a significant amount of data with traditional assessment techniques (e.g. camera recording, ethnography, questionnaires, etc.), these are considered highly subjective and possess an interesting negative effect for the former [3]: they typically fail to address complex interaction patterns. On the other hand, Rowe [5] states that some of the advantages of these interfaces are linked with being multi-dimensional, proving to be capable of providing alternative views on different issues. Lastly, physiological signals are typically continuously gathered, enabling a faster and more accurate detection of emotional or workload shifts.However, one domain in which physiological interaction mechanisms have failed to prosper in is mobile environments. There are multiple examples of studies on the use of such interaction mechanisms in desktop or stationary settings in a diversity of areas, ranging from entertainment to healthcare. The most recent examples of the use of physiological mechanisms in mobile settings stem from the NikeRunning [4] program and from a system which collects physiological data from users with the aim of improving positive emotions in their daily lives [8]. Nevertheless, neither of these

Beats Down: Using Heart Rate for Game Interaction in Mobile Settings

“…shader effects, volume of the environment and movement speed. An Adaptation engine, described in [9], uses physiological data for evaluation of user performance. Based on the user performance and several other parameters, like e.g.…”