Facial Landmark Activity Features for Depression Screening

Brian Sumali, Yasue Mitsukura, Yuuki Tazawa, Taishiro Kishimoto

研究成果: Conference contribution

抄録

Depression is the most common mood disorder in the world which is also the leading cause of suicide. Depression might be diagnosed using varying modalities, as it affects many aspects of the patient, not only the patient will appear melancholic, but the patient's sleep quality and life quality might also be disrupted. In this study, we aim to extract facial landmark features unique to depression patients and build a machine learning model to classify the depression severity. The facial landmark activities considered in this study include: speed statistics of the landmarks, the standard deviation of eye pupils, and statistical features of mouth area. We found several facial landmark activity features with significant differences between healthy volunteers and depressed patients. We also successfully built machine learning models for automatic depression severity prediction.

本文言語English
ホスト出版物のタイトル2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ページ1376-1381
ページ数6
ISBN(電子版)9784907764678
DOI
出版ステータスPublished - 2019 9
イベント58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019 - Hiroshima, Japan
継続期間: 2019 9 102019 9 13

出版物シリーズ

名前2019 58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019

Conference

Conference58th Annual Conference of the Society of Instrument and Control Engineers of Japan, SICE 2019
CountryJapan
CityHiroshima
Period19/9/1019/9/13

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization
  • Instrumentation

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