Mobile-based Clock Drawing Test for Detecting Early Signs of Dementia

Authors

  • Hongchao Jiang Alibaba-NTU Singapore Joint Research Institute (JRI), Nanyang Technological University (NTU), Singapore
  • Yanci Zhang School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore
  • Zhiwei Zeng Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University (NTU), Singapore
  • Jun Ji Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University (NTU), Singapore
  • Yu Wang Alibaba Group
  • Ying Chi Alibaba Group
  • Chunyan Miao Alibaba-NTU Singapore Joint Research Institute (JRI), Nanyang Technological University (NTU), Singapore School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly (LILY), Nanyang Technological University (NTU), Singapore

DOI:

https://doi.org/10.1609/aaai.v35i18.18008

Keywords:

Dementia, Automated Clock Drawing Test, Computer Vision

Abstract

Dementia is one of the major causes of disability and dependency among older people. Early detection is the key for preserving the quality of life of the patients and reducing caring costs. The Clock Drawing Test (CDT) is commonly used by clinicians to screen for early signs of dementia. We build an automated CDT that runs on mobile platforms, enabling convenient and frequent self-monitoring and testing at minimal costs. Our system combines both a spatial-temporal approach and a purely image-based deep learning approach to analyze and evaluate the hand-drawn clocks based on established clinical criteria. Our system produces scores that are highly correlated with expert human raters.

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Published

2021-05-18

How to Cite

Jiang, H., Zhang, Y., Zeng, Z., Ji, J., Wang, Y., Chi, Y., & Miao, C. (2021). Mobile-based Clock Drawing Test for Detecting Early Signs of Dementia. Proceedings of the AAAI Conference on Artificial Intelligence, 35(18), 16048-16050. https://doi.org/10.1609/aaai.v35i18.18008