Multiview child motor development dataset for AI-driven assessment of child development.

Journal: GigaScience
PMID: 37243520

Abstract

BACKGROUND: Children's motor development is a crucial tool for assessing developmental levels, identifying developmental disorders early, and taking appropriate action. Although the Korean Developmental Screening Test for Infants and Children (K-DST) can accurately assess childhood development, its dependence on parental surveys rather than reliable, professional observation limits it. This study constructed a dataset based on a skeleton of recordings of K-DST behaviors in children aged between 20 and 71 months, with and without developmental disorders. The dataset was validated using a child behavior artificial intelligence (AI) learning model to highlight its possibilities.

Authors

  • Hye Hyeon Kim
    Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, South Korea.
  • Jin Yong Kim
    Department of Radiology, Seoul National College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea (H.C., S.H.Y., S.J.P., C.M.P., J.H.L., H. Kim, E.J.H., S.J.Y., J.G.N., C.H.L., J.M.G.); CHESS Center, The First Hospital of Lanzhou University, Lanzhou, China (Q.X., J.L.); Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea (K.H.L.); Department of Internal Medicine, Incheon Medical Center, Incheon, Korea (J.Y.K.); Department of Radiology, Seoul Medical Center, Seoul, Korea (Y.K.L.); Department of Radiology, National Medical Center, Seoul, Korea (H. Ko); Department of Radiology, Myongji Hospital, Gyeonggi-do, Korea (K.H.K.); and Department of Radiology, Chonnam National University Hospital, Gwanju, Korea (Y.H.K.).
  • Bong Kyung Jang
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Joo Hyun Lee
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Jong Hyun Kim
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Dong Hoon Lee
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Hee Min Yang
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Young Jo Choi
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Myung Jun Sung
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Tae Jun Kang
    MISO Info Tech Co. Ltd., Seoul 06222, Republic of Korea.
  • Eunah Kim
    Maumdri Co. Ltd., Muan-gun, Jeollanam-do 58563, Republic of Korea.
  • Yang Seong Oh
    Maumdri Co. Ltd., Muan-gun, Jeollanam-do 58563, Republic of Korea.
  • Jaehyun Lim
    Lumanlab, Inc., Seoul 05836, Republic of Korea.
  • Soon-Beom Hong
    Division of Child and Adolescent Psychiatry, Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Republic of Korea.
  • Kiok Ahn
    GazziLabs, Inc., Anyang-si, Gyeonggi-do 14085, Republic of Korea.
  • Chan Lim Park
    Smart Safety Laboratory Co. Ltd., Seongnam-si, Gyeonggi-do 13494, Republic of Korea.
  • Soon Myeong Kwon
    Smart Safety Laboratory Co. Ltd., Seongnam-si, Gyeonggi-do 13494, Republic of Korea.
  • Yu Rang Park
    Asan Medical Center, Seoul, Republic of Korea.

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