Stretchable e-Skin Patch for Gesture Recognition on the Back of the Hand

Gesture recognition is important for human-computer interaction and a variety of emerging research and commercial areas including virtual and augmented reality. Current approaches typically require sensors to be placed on the forearm, wrist, or directly across finger joints; however, they can be cum...

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Veröffentlicht in:IEEE transactions on industrial electronics (1982) 2020-01, Vol.67 (1), p.647-657
Hauptverfasser: Jiang, Shuo, Li, Ling, Xu, Haipeng, Xu, Junkai, Gu, Guoying, Shull, Peter B.
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container_issue 1
container_start_page 647
container_title IEEE transactions on industrial electronics (1982)
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creator Jiang, Shuo
Li, Ling
Xu, Haipeng
Xu, Junkai
Gu, Guoying
Shull, Peter B.
description Gesture recognition is important for human-computer interaction and a variety of emerging research and commercial areas including virtual and augmented reality. Current approaches typically require sensors to be placed on the forearm, wrist, or directly across finger joints; however, they can be cumbersome or hinder human movement and sensation. In this paper, we introduce a novel approach to recognize hand gestures by estimating skin strain with multiple soft sensors optimally placed across the back of the hand. A pilot study was first conducted by covering the back of the hand with 40 small 2.5 mm reflective markers and using a high-precision camera system to measure skin strain patterns for individual finger movements. Optimal strain locations are then determined and used for sensor placement in a stretchable e-skin patch prototype. Experimental testing is performed to evaluate the stretchable e-skin patch performance in classifying individual finger gestures and American Sign Language 0-9 number gestures. Results showed classification accuracies of 95.3% and 94.4% for finger gestures and American Sign Language 0-9 gestures, respectively. These results demonstrate the feasibility of a stretchable e-skin patch on the back of the hand for hand gesture recognition and their potential to significantly enhance human-computer interaction.
doi_str_mv 10.1109/TIE.2019.2914621
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Current approaches typically require sensors to be placed on the forearm, wrist, or directly across finger joints; however, they can be cumbersome or hinder human movement and sensation. In this paper, we introduce a novel approach to recognize hand gestures by estimating skin strain with multiple soft sensors optimally placed across the back of the hand. A pilot study was first conducted by covering the back of the hand with 40 small 2.5 mm reflective markers and using a high-precision camera system to measure skin strain patterns for individual finger movements. Optimal strain locations are then determined and used for sensor placement in a stretchable e-skin patch prototype. Experimental testing is performed to evaluate the stretchable e-skin patch performance in classifying individual finger gestures and American Sign Language 0-9 number gestures. Results showed classification accuracies of 95.3% and 94.4% for finger gestures and American Sign Language 0-9 gestures, respectively. 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subjects Augmented reality
Classification
Feature selection
Finger jointing
Forearm
Gesture recognition
Human motion
human–computer interaction
Muscles
Optimization
Recognition
Sensor phenomena and characterization
Sensors
Sign language
Skin
skin stretch
soft sensing
Strain
Transdermal medication
Virtual reality
Wrist
title Stretchable e-Skin Patch for Gesture Recognition on the Back of the Hand
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