DocumentCode :
3753553
Title :
HANDIO: A Wireless Hand Gesture Recognizer Based on Muscle-Tension and Inertial Sensing
Author :
Jun Luan;Ting-Chou Chien;Seungjae Lee;Pai H. Chou
Author_Institution :
Center for Embedded Cyber-Phys. Syst., Univ. of California, Irvine, Irvine, CA, USA
fYear :
2015
Firstpage :
1
Lastpage :
7
Abstract :
This paper describes a miniature, wearable wireless hand- gesture recognition (HGR) system called HANDIO. It obtains its input from not only traditional inertial sensors but also a muscle tension sensor (MTS). The addition of MTS enables recognition of a much broader range of intuitive hand gestures, particularly those involving the wrist, that would otherwise be difficult to distinguish by traditional inertial-only HGRs. Among MTSs, we choose an optical MTS over the conventional surface electromyography(sEMG) for the small size, low power consumption, wearing comfort, and good detection rate. This novel miniaturized design enables the whole system to be easily patched on the wrist area or integrated into a wearable device such as a wristband or watch without extra wiring. Experimental results show that a total of 8 hand gestures involving the wrist can be recognized with a detection rate over 93%. The average power consumption of the optical sensor is only around 258μW. This versatile system can also be used to detect other joint activities such as the elbow and knee joint.
Keywords :
"Optical sensors","Muscles","Heuristic algorithms","Acceleration","Wrist","Optical pulses"
Publisher :
ieee
Conference_Titel :
Global Communications Conference (GLOBECOM), 2015 IEEE
Type :
conf
DOI :
10.1109/GLOCOM.2015.7417448
Filename :
7417448
Link To Document :
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