Blog #10: Sensing Foot Gestures from the Pocket

Sensing Foot Gestures from the pocket


Authors: Jeremy Scott, David Dearman, Koji Tatani, and Khai N. Truong

Jeremy Scott received his B.Sc., M.Sc. and PhD. in Pharamcology and Toxicology from the University of Western Ontario. He is currently an Assistant Professor and a Research Scientist at the University of Toronto.

David Dearman is a Ph.D. student at the University of Toronto. His research attempts to bridge the fields of Human-Computer Interaction, Ubiquitous Computing and Mobile Computing.

Koji Tatani is a Ph.D. student at the University of Toronto. His research interests lie in Human-Computer Interaction and ubiquitous computing with an emphasis on hardware and sensing technologies.

Khai N. Truong is an Associate Professor in the Department of Computer Science at the University of Toronto. His research interests lie in Human-Computer Interaction and Ubiquitous Computing.

Presented at UIST '10 Proceedings of the 23rd annual ACM symposium on User interface software and technology in New York.

Hypotheses:
The researchers discuss a way to use foot gestures to perform tasks in a mobile environment and develop a system that supports this. They made a study about the human capability with performing foot-based interactions which involve lifting and rotation of the foot when pivoting on the toe and heel. The researchers hope to find over time from users to recognize more accurately in addition to the primary goal of allowing users to perform tasks without having to focus on visual input and visual feedback.

Methods:

The researchers sudtied 4 various motions of the foot: dorsiflexion, Plantar flexion, heel rotation, and toe rotation. Participants were asked to hold down a button on a mouse and perform one of these gestures rotating to a specified angle from the start position and releasing to indicate completion. Six motion cameras recorded the moment. The Participants were to click the left mouse button to began the experiment, and do 156 gestures with visual feedback, then 468 non visual feedback gestures to simulate an eyes-free interaction.


Results: In the first study, they found that smaller angles were generally more accurate in the target selection. The interviews after this study also revealed that rotations of the heel were the most comfortable movement to perform. They found out that the phone in the side pocket, in general, gave much higher success rates. Over all gestures, they found that the side pocket placement of the iPhone gave an accuracy rate of 85.7%.


Contents/Discussion:

The researchers successfully developed a program to recognize foot gestures using data collected with a phone's accelerometer. The foot gesterues were properly recognized. They found 34 features that could be used in gesture recognition and implemented them into an initial application that was used in the second study. I think the researchers achieved their goal of proving the viability of using foot gestures as input and they mostly convinced me of this in their testing. But personally I don't like the idea of using my foot to open or use applications on the phone. It makes sense that i may be able to switch the song im licensing on the phone with the movement of my foot of twitch of my toe, i just don't think it would be useful otherwise. It can prove to be useful to people who are blind. Implementation of this program using the hands may prove to be a better product.