Characterizing player's experience from physiological signals using fuzzy decision trees

Being enjoyably challenged is the key to an enjoyable gaming experience: an experimental approach in a first-person shooter game

“…As Nacke and Lindley [26] who established a correlation between objective and self-reported measures, it could be interesting to examine whether physiological measures validate this causal model, and confirm both the typology of the players’ experiences and their link with enjoyment-based challenge mapping. This work should be done in the first place with physiological data from Levillain et al [25] which were collected during this very same experiment.…”

“…However, the common feature of the studies mentioned so far is that they share a narrow view of game enjoyment, which is mostly based on the pleasure gained from the game as measured through self-reported assessment, 3 GEQ questionnaires [24], or physiological measures [2,18,25,26]. Two drawbacks can also be mentioned here when using questionnaires.…”

A taxonomy and state of the art revision on affective games

“…Scheirer et al [14] Skin conductivity, blood pressure and mouse patterns for affective analysis Sakurazawa et al [15] Skin conductance response as emotional state detector Mandryk et al [16][17][18][19] Efficiency of several physiological measures Hazlett and L. [20] Facial electromyography Nacke and Lindley [21], Nacke et al [22,23] Multiple measures and flow between affective states Perez Martínez et al [24] Generality of physiological features Ravaja et al [25], Drachen et al [26], Levillain et al [27], Wu and Lin [28], Gualeni et al [29], Vachiratamporn et al [30], Martey et al [31], Abhishek and Suma [32], Landowska and Wróbel [33], Li et al [34] Applications of physiological measures Giakoumis et al [35] Automated boredom detection Chanel et al [36,37], Nogueira et al [38] Machine-learning classifiers for emotional states Jones and Sutherland [39] Emotion detection from player's voice Garner and Grimshaw [40], Nacke et al [41], Nacke and Grimshaw [42] Effect of the sound in players' fear level Christy and Kuncheva [43] Computer mouse with affective detection Going a step further, Nacke and Lindley [21], Nacke et al [22,23] studied how to measure the global player experience while playing a game analysing the same physiological metrics as before: electromyography, electrodermal activity and so on. Regarding the player experience, the authors measured the flow between varied affective states, such as anxiety, apathy and boredom.…”

Predicting skill from gameplay input to a first-person shooter

“…While objective and quantifiable measurements of a player's emotions is preferred for prediction, use of physiological data is still an emerging field [16] and equipment is expensive. Therefore, self-assessment is a typical form of capture for player experience [3], [17], as in this study.…”