Assessing Elevated Blood Glucose Levels Through Blood Glucose Evaluation and Monitoring Using Machine Learning and Wearable Photoplethysmography Sensors: Algorithm Development and Validation.

Journal: JMIR AI
Published Date:

Abstract

BACKGROUND: Diabetes mellitus is the most challenging and fastest-growing global public health concern. Approximately 10.5% of the global adult population is affected by diabetes, and almost half of them are undiagnosed. The growing at-risk population exacerbates the shortage of health resources, with an estimated 10.6% and 6.2% of adults worldwide having impaired glucose tolerance and impaired fasting glycemia, respectively. All current diabetes screening methods are invasive and opportunistic and must be conducted in a hospital or laboratory by trained professionals. At-risk participants might remain undetected for years and miss the precious time window for early intervention to prevent or delay the onset of diabetes and its complications.

Authors

  • Bohan Shi
    Actxa Pte Ltd, Singapore, Singapore.
  • Satvinder Singh Dhaliwal
    Curtin Health Innovation Research Institute, Curtin University, Perth, Australia.
  • Marcus Soo
    Actxa Pte Ltd, Singapore, Singapore.
  • Cheri Chan
    KK Women's and Children's Hospital, Singapore, Singapore.
  • Jocelin Wong
    Actxa Pte Ltd, Singapore, Singapore.
  • Natalie W C Lam
    Activate Interactive Pte Ltd, Singapore, Singapore.
  • Entong Zhou
    Activate Interactive Pte Ltd, Singapore, Singapore.
  • Vivien Paitimusa
    Activate Interactive Pte Ltd, Singapore, Singapore.
  • Kum Yin Loke
    Activate Interactive Pte Ltd, Singapore, Singapore.
  • Joel Chin
    Activate Interactive Pte Ltd, Singapore, Singapore.
  • Mei Tuan Chua
    KK Women's and Children's Hospital, Singapore, Singapore.
  • Kathy Chiew Suan Liaw
    KK Women's and Children's Hospital, Singapore, Singapore.
  • Amos W H Lim
    Actxa Pte Ltd, Singapore, Singapore.
  • Fadil Fatin Insyirah
    KK Women's and Children's Hospital, Singapore, Singapore.
  • Shih-Cheng Yen
    Innovation and Design Programme, Faculty of Engineering, National University of Singapore, Singapore, Singapore.
  • Arthur Tay
    Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore.
  • Seng Bin Ang
    Family Medicine Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore.

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