Smartphone-Based Method for Detecting Periodontal Disease

Behnam Askarian, Fatemehsadat Tabei, Grace Anne Tipton, Jo Woon Chong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we propose a novel periodontal disease detection method using smartphones, image processing, and machine learning techniques. Periodontal disease is an inflammatory disease known to be the main cause of tooth loss. Here, a CIELAB color space is adopted for feature extraction and the support vector machine (SVM) is applied for distinguishing healthy gum from diseased gum. A gadget is designed to block ambient light and eliminate refraction effect as well. We recruited 30 subjects consisting of 15 gum-diseased and 15 healthy subjects. Experimental results show that our proposed method detects periodontal infection with 94.3% accuracy, 92.6% sensitivity, and 93% specificity, respectively.

Original languageEnglish
Title of host publication2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages53-55
Number of pages3
ISBN (Electronic)9781728138121
DOIs
StatePublished - Nov 2019
Event2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019 - Bethesda, United States
Duration: Nov 20 2019Nov 22 2019

Publication series

Name2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019

Conference

Conference2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019
CountryUnited States
CityBethesda
Period11/20/1911/22/19

Keywords

  • CIELAB
  • Color space
  • Mobile health
  • Periodontal disease
  • Smartphone
  • Support vector machine (SVM)

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  • Cite this

    Askarian, B., Tabei, F., Tipton, G. A., & Chong, J. W. (2019). Smartphone-Based Method for Detecting Periodontal Disease. In 2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019 (pp. 53-55). [8962844] (2019 IEEE Healthcare Innovations and Point of Care Technologies, HI-POCT 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HI-POCT45284.2019.8962844