Presentation 2020-12-18
Investigation of the relationship between heart rate variability spectrogram and human preference using CNN
Shuhei Kishida, Yohei Ochiai, Koki Buyo, Yuya Okazaki, Yuuko Horita,
PDF Download Page PDF download Page Link
Abstract(in Japanese) (See Japanese page)
Abstract(in English) In order to provide products and services optimized for each user, biological signals such as heart rate variability and pulse waves, which can estimate values and preferences from the user's unconsciousness, are effective. Therefore, in this paper, we created a subject's heart rate variability spectrogram (HRVS) for still images using a trained convolutional neural network (CNN) and Support vector machine (SVM), and expressed the degree of change in the spectrogram as a difference. Using the difference spectrogram, we investigate whether people's preference can be discriminated. Specifically, transfer learning is performed on the trained models of VGG16, ResNet50, and Inception-V3. Using these models, we showed the images to the subjects and extracted the measured HRVS features, and confirmed whether the subjects' preferences could be discriminated using SVM.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) CNN / SVM / HRVS
Paper # IMQ2020-8
Date of Issue 2020-12-11 (IMQ)

Conference Information
Committee IMQ
Conference Date 2020/12/18(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Toshiya Nakaguchi(Chiba Univ.)
Vice Chair Mitsuru Maeda(Canon) / Kenya Uomori(Osaka Univ.)
Secretary Mitsuru Maeda(Shizuoka Univ.) / Kenya Uomori(Sony Semiconductor Solutions)
Assistant Hiroaki Kudo(Nagoya Univ.) / Masaru Tsuchida(NTT) / Keita Hirai(Chiba Univ.)

Paper Information
Registration To Technical Committee on Image Media Quality
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Investigation of the relationship between heart rate variability spectrogram and human preference using CNN
Sub Title (in English)
Keyword(1) CNN
Keyword(2) SVM
Keyword(3) HRVS
1st Author's Name Shuhei Kishida
1st Author's Affiliation University of Toyama(Univ. of Toyama)
2nd Author's Name Yohei Ochiai
2nd Author's Affiliation University of Toyama(Univ. of Toyama)
3rd Author's Name Koki Buyo
3rd Author's Affiliation University of Toyama(Univ. of Toyama)
4th Author's Name Yuya Okazaki
4th Author's Affiliation University of Toyama(Univ. of Toyama)
5th Author's Name Yuuko Horita
5th Author's Affiliation University of Toyama(Univ. of Toyama)
Date 2020-12-18
Paper # IMQ2020-8
Volume (vol) vol.120
Number (no) IMQ-303
Page pp.pp.5-8(IMQ),
#Pages 4
Date of Issue 2020-12-11 (IMQ)