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심장 소리 분류를 위한 Inverted Residuals 기반 경량화 모델A Lightweight Model for Heart Sound Classification Based on Inverted Residuals

Other Titles
A Lightweight Model for Heart Sound Classification Based on Inverted Residuals
Authors
박두서이민영김기현이홍철
Issue Date
2021
Publisher
대한산업공학회
Keywords
Heart Sound Classification; Inverted Residuals; Lightweight Model Architecture; PASCAL Classifying Heart Sounds Challenge
Citation
대한산업공학회지, v.47, no.6, pp.514 - 528
Indexed
KCI
Journal Title
대한산업공학회지
Volume
47
Number
6
Start Page
514
End Page
528
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/139596
ISSN
1225-0988
Abstract
For the treatment and prevention of heart diseases, which is the leading cause of high mortality rate globally, the need for healthcare devices equipped with artificial intelligence(AI) model that can monitor in real-time and analyze heart conditions is increasing. Therefore, in this study, we propose a light CNN that can be applied to healthcare devices, using the PASCAL data. The proposed model used MFCC feature extraction method suitable for heart sound range, The light CNN was designed with the inverted residuals used in MobileNetV2. The experiments showed that the proposed model with fewer 82.5% of the learnable parameters, achieved similar performance in accuracy within the range of 1 to 2% compared to the previous studies. It was confirmed that the proposed light CNN can be feasibly incorporated on mobile devices by means of comparative experiments in a reasonable amount of computation.
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공과대학 (산업경영공학부)
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