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Cardiac biomarkers are enzymes, proteins, and hormones released into the blood when cardiac cells are injured. They are powerful tools for triaging.
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Dried Blood Spot Collection of Health Biomarkers to Maximize Participation in Population Studies
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Biomarkers.

Yuting Song1, Bingjie Wu1, Menghan Zhou1

  • 1Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore, Singapore.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
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Summary
This summary is machine-generated.

This study shows artificial intelligence (AI) can detect behavioral impairment by analyzing facial and physiological responses. AI-derived heart rate (HR) correlated strongly with depression scores in seniors, aiding early detection.

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Area of Science:

  • Geriatric Medicine
  • Artificial Intelligence
  • Behavioral Science

Background:

  • Early detection of behavioral impairment is crucial for timely intervention.
  • Traditional assessment tools have limitations like practice effects and staffing shortages.
  • Behavioral symptoms are linked to physiological changes and facial expressions.

Purpose of the Study:

  • To develop a novel AI-based system for analyzing facial and physiological responses.
  • To facilitate early detection of behavioral impairment in at-risk community individuals.
  • To assess the correlation between AI-derived heart rate (HR) and Geriatric Depression Scale-15 (GDS-15) scores.

Main Methods:

  • Recruited 66 seniors (aged 60+) from a community cognitive screening program.
  • Collected facial video samples at rest and during GDS-15 assessments.
  • Developed AI algorithms to derive HR from facial videos and correlated it with GDS-15 scores.

Main Results:

  • AI-based HR detection achieved mean average errors of 10.1 (rest) and 13.9 (assessment) bpm.
  • In the depression group (GDS-15 ≥5), HR correlated highly with GDS-15 scores (0.87 resting, 0.98 during assessment).
  • In the normal group (GDS-15 0-4), correlations between HR and GDS-15 were negligible (0.13 resting, 0.06 during assessment).

Conclusions:

  • Preliminary findings support AI-derived HR from facial analysis as a promising tool for behavioral impairment screening.
  • Higher depressive symptoms were associated with higher HR in seniors.
  • Future work will integrate facial features and physiological measures for enhanced diagnostic accuracy.