Author:
Endo Hiroshi, ,Kaneko Hidekazu,Ino Shuichi,Fujisaki Waka
Abstract
Improving the texture of foods provided during nursing care is necessary to improve the appetite of elderly individuals. We developed a system to vary perceived food texture using pseudo-chewing sounds generated from electromyogram (EMG) signals. However, this previous system could not provide chewing sounds that were sufficiently congruous with foods. Because food/sound combinations that seem unnatural cause individuals to feel uncomfortable with pseudo-chewing sounds, food/sound congruity is important. This research aims to improve the derivation and presentation of pseudo-chewing sounds so as to be able to provide various kinds of chewing sounds. The developed system adjusts the volume of pseudo-chewing sounds that are stored in a digital audio player based on the amplitude of the EMG signal envelope. Using this system, food/sound congruity was examined with two kinds of softened Japanese pickles. Six kinds of pseudo-chewing sounds were tested (noisy chewing sound, EMG chewing sound, and four kinds of actual chewing sounds: rice cracker, cookie, and two kinds of Japanese pickles). Participants reported that food/sound combinations were unnatural with the noisy and EMG chewing sounds, whereas the combinations felt more natural with the pseudo-chewing sounds of Japanese pickles. We concluded that the newly developed system could effectively reduce the unnatural feeling of food/sound incongruity.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
Cited by
4 articles.
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