Title :
Recognition of hand action using body-conducted sounds
Author :
Katsushi Miura;Shan Jiang;Yoshiro Hada;Keiju Okabayashi
Author_Institution :
FUJITSU LABORATORIES LTD., Kanagawa, Japan
fDate :
7/1/2015 12:00:00 AM
Abstract :
Several methods of recognizing hand actions by examining the vibrations conducted through the body from muscular activity (we call them “body-conducted sounds” in this paper) were proposed in previous works. However, they did not consider the transfer characteristic of body-conducted sounds. In this paper, we propose a method for hand action recognition that extracts the main frequency elements of body-conducted sounds using the Mel-Frequency Cepstrum Coefficient (MFCC) and divides the hidden states of Hidden Markov Models (HMMs) based on the MFCC. The results of experiments show that our method makes it possible to correctly recognize 95% of hand actions on average.
Keywords :
"Mel frequency cepstral coefficient","Hidden Markov models","Accuracy","Thumb","Wrist","Sensors"
Conference_Titel :
Society of Instrument and Control Engineers of Japan (SICE), 2015 54th Annual Conference of the
DOI :
10.1109/SICE.2015.7285315