@article{ART002795551},
author={Junho Kim and Ki-Hyun Park and Hoseok Kim and Siwoo Lee and Kim Sang-Hyuk},
title={Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center},
journal={Journal of Sasang Constitutional Medicine},
issn={1226-4075},
year={2021},
volume={33},
number={4},
pages={1-9},
doi={10.7730/JSCM.2021.33.4.1}
TY - JOUR
AU - Junho Kim
AU - Ki-Hyun Park
AU - Hoseok Kim
AU - Siwoo Lee
AU - Kim Sang-Hyuk
TI - Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center
JO - Journal of Sasang Constitutional Medicine
PY - 2021
VL - 33
IS - 4
PB - The Society Of Sasang Constitutional Medicine
SP - 1
EP - 9
SN - 1226-4075
AB - Objectives The purpose of this study was to check whether the classification of the individual’s Body Mass Index (BMI) could be predicted by analyzing the voice data constructed at the Korean medicine data center (KDC) using machine learning.
Methods In this study, we proposed a convolutional neural network (CNN)-based BMI classification model. The subjects of this study were Korean adults who had completed voice recording and BMI measurement in 2006-2015 among the data established at the Korean Medicine Data Center. Among them, 2,825 data were used for training to build the model, and 566 data were used to assess the performance of the model. As an input feature of CNN, Mel-frequency cepstral coefficient (MFCC) extracted from vowel utterances was used. A model was constructed to predict a total of four groups according to gender and BMI criteria: overweight male, normal male, overweight female, and normal female.
Results & Conclusions Performance evaluation was conducted using F1-score and Accuracy. As a result of the prediction for four groups, The average accuracy was 0.6016, and the average F1-score was 0.5922. Although it showed good performance in gender discrimination, it is judged that performance improvement through follow-up studies is necessary for distinguishing BMI within gender. As research on deep learning is active, performance improvement is expected through future research.
KW - Machine learning;Voice;Body Mass Index;Convolutional neural network
DO - 10.7730/JSCM.2021.33.4.1
ER -
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee and Kim Sang-Hyuk. (2021). Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center. Journal of Sasang Constitutional Medicine, 33(4), 1-9.
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee and Kim Sang-Hyuk. 2021, "Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center", Journal of Sasang Constitutional Medicine, vol.33, no.4 pp.1-9. Available from: doi:10.7730/JSCM.2021.33.4.1
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee, Kim Sang-Hyuk "Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center" Journal of Sasang Constitutional Medicine 33.4 pp.1-9 (2021) : 1.
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee, Kim Sang-Hyuk. Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center. 2021; 33(4), 1-9. Available from: doi:10.7730/JSCM.2021.33.4.1
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee and Kim Sang-Hyuk. "Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center" Journal of Sasang Constitutional Medicine 33, no.4 (2021) : 1-9.doi: 10.7730/JSCM.2021.33.4.1
Junho Kim; Ki-Hyun Park; Hoseok Kim; Siwoo Lee; Kim Sang-Hyuk. Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center. Journal of Sasang Constitutional Medicine, 33(4), 1-9. doi: 10.7730/JSCM.2021.33.4.1
Junho Kim; Ki-Hyun Park; Hoseok Kim; Siwoo Lee; Kim Sang-Hyuk. Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center. Journal of Sasang Constitutional Medicine. 2021; 33(4) 1-9. doi: 10.7730/JSCM.2021.33.4.1
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee, Kim Sang-Hyuk. Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center. 2021; 33(4), 1-9. Available from: doi:10.7730/JSCM.2021.33.4.1
Junho Kim, Ki-Hyun Park, Hoseok Kim, Siwoo Lee and Kim Sang-Hyuk. "Application of Machine Learning on Voice Signals to Classify Body Mass Index - Based on Korean Adults in the Korean Medicine Data Center" Journal of Sasang Constitutional Medicine 33, no.4 (2021) : 1-9.doi: 10.7730/JSCM.2021.33.4.1
