Log Who’s Playing:
Psychophysiological Game Analysis
Made Easy Through Event Logging
Lennart Nacke, Craig Lindley, Sophie Stellmach
Blekinge Institute of Technology, Sweden
Department of Interaction and System Design
Game and Media Arts Laboratory

Outline
 Motivation for our work
 Conceptual design
 Automated game event logging
– Details
– A word about gaze logging
 Conclusion and future work

Motivation
 Understand user behavior by decoding events
 Evaluation data accompanied by video
– Qualitative data
– Behavioral data
 Improvement by adding even-related physiological data
– Specific phasic response in event context
 What makes gameplay fun?

Conceptual design
 Meaningful events
– In-game events
 User-created
 Pre-defined and triggered
– Real-world events
 Sensors (physiological, positional, etc.)
 Video
 Record at run-time speed of 3d game engine
 Interface with physiological recording hardware
– Parallel port (200 ms accuracy)
 Easy integration into editing tools

IMPLEMENTED IN
SOURCE SDK

Types of logging

Event-code examples
105:
Pressing
red button
55:
Player fires
a gun
21:
Damage to smiling
opposing NPC

Automated game logging
 Transmission component
– Interfacing class
– Communication with physiological recording hardware
 Event component
– Common (level-independent)
 Enemy is killed, etc.
– Unique (level-dependent)
 Player enters area, etc.
 Dynamically assign unique events in editing tool
CBaseEntity
Event_Log Logging_Entity
Private
Input Output
Data
Functions Functions
Members

Dynamically assigning events
Screenshot showing the logging entities and manually defined output
codes inside the Hammer editing tool for the Half-Life 2 Source SDK.

Correlation of Physiological Data to Events
Physiological data is recorded together with real-time game events,
allowing for automatic data clustering and analysis

Main benefit: time reduction for researcher
 Data correlation is fully automated
Experiment Data Analysis
Preparation
Correlation

A word about gaze logging
 Automatically logs and identifies
– Game objects
– Graphical assets
 Tobii 1750 (SDK)
– Video-based
– Corneal-reflection tracking
 Logs
– Object ID
– Event ID
– Time stamp
– L+R gaze points (x,y)

Dissecting player experience
 Surveys
– Pre-game
– (In-game)
– Post-game
 Physiological responses
– Emotion
– Cognition
– Arousal
 Visual attention
– Gaze tracking
 Game Metrics

Conclusion and future work
 Event-logging enables detailed understanding
– of game experience
 Automatic data correlation saves analysis time
 Studies using the system are ongoing
 First results will be coming in shortly

Thank you kindly for listening!
me Craig Sophie
cld@bth.se slm@bth.se
Lennart Nacke
Find me at…
Blekinge Institute of Technology
Game and Media Arts Laboratory
Karlshamn, Sweden
Lennart.Nacke@bth.se
http://gamescience.bth.se
http://www.acagamic.com
Download papers from: http://gamescience.bth.se/research/publications