Automated tongue diagnosis on the smartphone and its applications

Min Chun Hu, Kun Chan Lan, Wen Chieh Fang, Yu Chia Huang, Tsung Jung Ho, Chun Pang Lin, Ming Hsien Yeh, Paweeya Raknim, Ying Hsiu Lin, Ming Hsun Cheng, Yi Ting He, Kuo Chih Tseng

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Tongue features are important objective basis for clinical diagnosis and treatment in both western medicine and Chinese medicine. The need for continuous monitoring of health conditions inspires us to develop an automatic tongue diagnosis system based on built-in sensors of smartphones. However, tongue images taken by smartphone are quite different in color due to various lighting conditions, and it consequently affects the diagnosis especially when we use the appearance of tongue fur to infer health conditions. In this paper, we captured paired tongue images with and without flash, and the color difference between the paired images is used to estimate the lighting condition based on the Support Vector Machine (SVM). The color correction matrices for three kinds of common lights (i.e., fluorescent, halogen and incandescent) are pre-trained by using a ColorChecker-based method, and the corresponding pre-trained matrix for the estimated lighting is then applied to eliminate the effect of color distortion. We further use tongue fur detection as an example to discuss the effect of different model parameters and ColorCheckers for training the tongue color correction matrix under different lighting conditions. Finally, in order to demonstrate the potential use of our proposed system, we recruited 246 patients over a period of 2.5 years from a local hospital in Taiwan and examined the correlations between the captured tongue features and alanine aminotransferase (ALT)/aspartate aminotransferase (AST), which are important bio-markers for liver diseases. We found that some tongue features have strong correlation with AST or ALT, which suggests the possible use of these tongue features captured on a smartphone to provide an early warning of liver diseases.

Original languageEnglish
Pages (from-to)51-64
Number of pages14
JournalComputer Methods and Programs in Biomedicine
Volume174
DOIs
Publication statusPublished - 2019 Jun

Fingerprint

Smartphones
Tongue
Color
Lighting
Liver
Medicine
Health
Aspartate Aminotransferases
Alanine Transaminase
Support vector machines
Liver Diseases
Smartphone
Halogens
Monitoring
Sensors
Taiwan
Light

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications
  • Health Informatics

Cite this

Hu, Min Chun ; Lan, Kun Chan ; Fang, Wen Chieh ; Huang, Yu Chia ; Ho, Tsung Jung ; Lin, Chun Pang ; Yeh, Ming Hsien ; Raknim, Paweeya ; Lin, Ying Hsiu ; Cheng, Ming Hsun ; He, Yi Ting ; Tseng, Kuo Chih. / Automated tongue diagnosis on the smartphone and its applications. In: Computer Methods and Programs in Biomedicine. 2019 ; Vol. 174. pp. 51-64.
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Hu, MC, Lan, KC, Fang, WC, Huang, YC, Ho, TJ, Lin, CP, Yeh, MH, Raknim, P, Lin, YH, Cheng, MH, He, YT & Tseng, KC 2019, 'Automated tongue diagnosis on the smartphone and its applications', Computer Methods and Programs in Biomedicine, vol. 174, pp. 51-64. https://doi.org/10.1016/j.cmpb.2017.12.029

Automated tongue diagnosis on the smartphone and its applications. / Hu, Min Chun; Lan, Kun Chan; Fang, Wen Chieh; Huang, Yu Chia; Ho, Tsung Jung; Lin, Chun Pang; Yeh, Ming Hsien; Raknim, Paweeya; Lin, Ying Hsiu; Cheng, Ming Hsun; He, Yi Ting; Tseng, Kuo Chih.

In: Computer Methods and Programs in Biomedicine, Vol. 174, 06.2019, p. 51-64.

Research output: Contribution to journalArticle

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AU - Hu, Min Chun

AU - Lan, Kun Chan

AU - Fang, Wen Chieh

AU - Huang, Yu Chia

AU - Ho, Tsung Jung

AU - Lin, Chun Pang

AU - Yeh, Ming Hsien

AU - Raknim, Paweeya

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