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PupilHeart: Heart Rate Variability Monitoring via Pupillary Fluctuations on Mobile Devices

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  • C. Sruneethi
  • K Chandana

Abstract

Heart Rate Variability (HRV) is a key physiological indicator associated with autonomic nervous system activity, stress, and cardiovascular health. Traditional HRV measurement techniques, such as electrocardiography (ECG) or photoplethysmography (PPG), require dedicated sensors and contact-based setups. This paper presents PupilHeart, a novel, contactless system that estimates HRV through the analysis of pupillary fluctuations captured by mobile device cameras. Leveraging recent advances in computer vision and physiological computing, PupilHeart extracts micro-variations in pupil diameter from video streams in real-time and correlates these fluctuations with heart rate patterns. The system uses machine learning models to map visual pupil data to HRV metrics such as RMSSD and SDNN. We validate the approach through controlled experiments comparing pupil-derived HRV with standard ECG measurements. Results show a promising correlation, suggesting that pupillary dynamics can serve as a non-invasive proxy for HRV monitoring. PupilHeart offers a scalable and accessible method for physiological monitoring on everyday mobile devices.

Suggested Citation

  • C. Sruneethi & K Chandana, 2025. "PupilHeart: Heart Rate Variability Monitoring via Pupillary Fluctuations on Mobile Devices," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 12(3), pages 339-342, June.
    • Handle: RePEc:etm:ijsrst:v12:y2025:i3:id:847
    DOI: 10.32628/IJSRST2512339
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