Paper Reading #18: Biofeedback Game Design

References
Biofeedback Game Design: Using Direct and Indirect Physiological Control to Enhance Game Interaction by Lennart E. Nacke, Michael Kalyn, Calvin Lough, and Regan L. Mandryk.  Published in the CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems.


Author Bios

• Lennart E. Nacke is currently an Assistant Professor for HCI and Game Science at the Faculty of Business and Information Technology at UOIT.  He holds a PhD in game development.
• Michael Kalyn is currently a graduate student in Computer Engineering at the University of Saskatchewan.  He spent the summer working for Dr. Mandryk in areas related to interfacing sensors and affective feedback.
• Calvin Lough is currently a student in at the University of Saskatchewan.
• Regan L. Mandryk is currently an Assistant Professor in the Interaction Lab in the Department of Computer Science at the University of Saskatchewan.  

Summary

Hypothesis

• The authors propose a system of direct and indirect physiological sensor input to augment game control.

Methods

• The researchers wanted to answer two main questions: 1. How do users respond when physiological sensors are used to augment rather than replace game controllers?   And 2. Which types of physiological sensors (indirect versus direct) work best for which in-game tasks?      They designed a shooter game that uses a traditional game controller as the primary input and augmented it with physiological sensors.  In the actual study participants played with three combinations of physiological and traditional input. Two of the game conditions mapped two direct and two indirect sensors to the four game mechanics, while the third condition used no physiological input.  The physiological sensors used as direct control were respiration, EMG on the leg, and temperature. The indirectly controlled sensors included GSR and EKG.  All participants played all conditions and filled out a questionnaire.  They were also given instructions regarding how to control the physiological sensors.

Results

• The participants seemed to prefer when controls matched a natural input, such as flexing the legs for more jumping power.  Overall the subjects seemed to appreciate the added level of involvement, but there was some concern that it made gameplay more complicated.  When asked about the novelty, users agreed that it was a very novel idea and that some of the controls had a little bit of a learning curve.  However, once the curve was conquered the overall experience was more rewarding.  Regarding preferred sensors: For target size increases and  flamethrower length, players RESP to GSR. For speed and jump height they preferred EMG to EKG. For controlling the weather and speed of the yeti, players preferred TEMP to EKG. 

Contents

• This article delves into an area of gaming that has plenty of room to be explored.  Namely, physiological interaction.  The topics presented in this research focus on learning how people react to different types of sensors and which kinds are preferable in given situations.  It also explored the gap between traditional controls and learning to adapt to the new sensing controls.  The overall feedback was positive, but there were some areas that might have been a little un-intuitive or difficult to pick up on.

Discussion
I am very excited about this direction in the world of gaming and I think there will be a great market for it once some of the details are hammered out.  As for the paper itself, I think it did a reasonably good job of laying some foundation for future work, but I think they could have gone a little bit further.  For example, I would have liked to have seen a broader variety of sensors and perhaps a more diverse test group, although technically their target audience would probably (initially) be similar to the actual participants.