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Related Experiment Video

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Noninvasive Blood Glucose Monitoring Systems Using Near-Infrared Technology-A Review.

Aminah Hina1, Wala Saadeh1

  • 1Department of Electrical Engineering, Lahore University of Management and Sciences, Lahore 54792, Pakistan.

Sensors (Basel, Switzerland)
|July 9, 2022
PubMed
Summary

Developing noninvasive continuous glucose monitoring (CGM) is crucial for diabetes management, especially in low-income countries. This review explores optical, transdermal, and enzymatic methods, focusing on Near Infrared Photoplethysmography (NIR PPG) for cost-effective glucose prediction.

Keywords:
Photoplethysmography (PPG)machine learning (ML) methodsnear-infrared (NIR)noninvasive glucose monitoring

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Area of Science:

  • Biomedical Engineering
  • Medical Devices
  • Optical Sensing

Background:

  • Conventional finger-prick glucose monitoring is painful and costly for frequent use.
  • Existing continuous glucose monitoring (CGM) systems are expensive and require calibration.
  • Rising diabetes prevalence in low- and middle-income countries necessitates affordable monitoring solutions.

Purpose of the Study:

  • To review noninvasive glucose monitoring technologies.
  • To focus on Near Infrared (NIR) and Photoplethysmography (PPG) for blood glucose prediction.
  • To explore machine learning applications in PPG-based glucose monitoring.

Main Methods:

  • Review of optical, transdermal, and enzymatic noninvasive glucose measurement techniques.
  • Focus on Near Infrared (NIR) technology and Photoplethysmography (PPG) signal analysis.
  • Discussion of feature extraction from PPG signals and machine learning for glucose prediction.

Main Results:

  • Optical, transdermal, and enzymatic methods show potential for noninvasive glucose monitoring.
  • NIR-based PPG demonstrates promise for blood glucose prediction.
  • Machine learning enhances accuracy in predicting glucose levels from PPG signals.

Conclusions:

  • Noninvasive glucose monitoring is essential for widespread diabetes management.
  • NIR-PPG technology offers a cost-effective pathway for future glucose monitoring devices.
  • Further research in PPG signal processing and machine learning is key for clinical translation.