BackHand: Sensing Hand Gestures via Back of the Hand
summary
Prototype uses a reusable artificial-skin carrier with a two-row strain-gauge array mounted on the back of the hand, sensing tendon stretch and compression. Personalized classifiers reach 95.8% accuracy for 16 gestures (leave-one-out per user); a cross-user model averages 27.4%. Training for 16 gestures takes about 5 minutes per user. Best sensing location sits between the knuckles (MCP) and ulna head; system requires per-wear recalibration and can’t reconstruct continuous hand motion.
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chapters (6)
- 0:00Start
- 6:24Evaluation
- 7:06Gesture Set Popular Hand Gestures
- 11:05Confusion Matrix
- 12:07Limitations
- 12:44Conclusion
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