Summary:
Harling and Edwards describe a way to segment hand gestures based on hand tension. The basic idea is that as a user dynamically moves between static postures a and b, their hand will reach a "relaxed", low-tension minimum position c that is less tense than either a or b.
Smaller details:
- To find the tension for each finger, the authors use Hooke's Law and treat a finger as if it were a spring
- The total hand tension is the sum of the finger tensions
- They used a Mattel PowerGlove
Discussion:
The idea behind the paper was actually quite good for recognizing between static postures. I have a feeling that the hand tension will not work well for moving gestures since there would be small segmentations within the gesture.
I'm disappointed at their lack of results. I can forgive other papers that were user studies, but I cannot forgive a paper that does not report easily obtainable results when they spent 8 pages discussing a topic that I summarized in one sentence. Segmentation is rather simple to gather data for, and a published paper should at least attempt to find an accuracy number.
On a technical note, I'm curious as to how hand tension is affected by the type of glove worn. I have a feeling that my "hand relaxed" position is going to be different for a P5 glove than it will be for a CyberGlove or even a CyberGlove with a Flock of Birds attached. All the extra weight will most likely force my hand into resting upon the equipment for support.
4 comments:
you're probably right - you're hand's "relax" state will probably be different based on which device you are using. also, the "relax" state will probably be different across different users. if tension was used in a practical application then there would probably need to be some calibration process the occurs at startup.
You brought up a good point concerning the type of device. From the sound of it, it seems like tension would not be a good metric if we take a device-independent approach.
Concerning the length of the paper with lacking results, I found it disappointing, too. For the points concerning problems with various other methods, this paper was quite informative. I'll give it that.
I can't help but think that this is a case when multiple devices will be useful on a hand. What about doing tracking as normal - but using an EMG device only to recognize relaxation. As an EMG device would be excellent at recognizing relaxation - but bad (or rather hard to get working) for determining precise finger location - and it would probably be easy to do. Maybe we can get Josh to see if this is possible. (Tracy Hammond)
I think if you incorporated a statistical measure to look at when tension is 'low', rather than just looking for minima or thresholds (perhaps the change in tension?) you could get good accuracy for multiple users and multiple gesture domains.
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