Paper Reading #18: Biofeedback Game Design

Authors

Lennart E. Nacke, Michael Kalyn, Calvin Lough, and Regan L. Mandryk

Occupation
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.  

Location
CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems at NYC

Summary
Hypothesis
The authors proposed a physiological sensor input to augment game control using both direct and indirect manners

Method
There were two main fields that the researchers wanted to question. How do users respond when physiological senors are used to augment the game (not replace controllers). And which type of physiological senors work best for in game tasks? (direct / indirect) In order to test these questions the researchers designed a shooter game using a traditional controller as the main input while augmented with physiological sensors. The participants played with three different combinations of sensors while using the game controller as the main input. The first two combinations of the game was done with two direct and two indirect sensors. The last combination had no sensors on the game. The direct sensors applied were based on respiration, EMG on leg, and temperature. The indirect sensors were based on GSR and EKG. The participants filled out a survey after they had played the game.

result
The participants referred the sensors over non sensors as long as the input of the sensors matched the inputs in the game. Examples would include moving legs to boost jump power. The added involvement from the sensors had an overall positive feedback from the users in general. Although there was a concern of making the game more complicated the users commented that the learning curve was a bit high due to learning some of the extra movement one had to do. Despite the learning curve the participants believed the whole gaming experience was more rewarding. Examples of preference include EMG for speed and jump boosts, Temp for controlling the weather and speed of yeti etc.

Content
This paper talks about a field of gaming that still has much room for improvement as it focuses on possibilities based on physiological interactions. This research focused on how people would react to different types of physiological sensors and what were preferred by the users in different situations in a game. There was also a research in seeing the different between sensor augmented game and the tradition controller based inputs. Although the users enjoyed the concept they believe the learning curve was higher due to some non intuitive sensor inputs.

discussion
I was generally very excited about this whole paper since i do game on occasion. I believe that games that would utilize such technology can be very possible in the near future and i believe that it can add another interest element of game play when playing first person shooter. I think it would take games with interactions such as the wii to a whole new level of interaction.