Li, Tianyi, Park, Seo-Hyun, Lee, Changwoo et al. · Advanced sensor research · 2025 · DOI
Researchers developed a pair of smart glasses that can measure fatigue by tracking how often and how long you blink, without any contact with your eyes. The glasses use specially designed sensors made from carbon nanotubes to detect these eye movements in real-time. In a 15-minute test involving focused tasks and noise exposure, the system was able to distinguish between normal tiredness and chronic fatigue using artificial intelligence.
ME/CFS patients often struggle to objectively document their fatigue severity to healthcare providers, as current assessments rely heavily on subjective self-reporting. A real-time, wearable monitoring device could provide objective, continuous data to help clinicians diagnose and track disease progression. This technology may eventually enable better understanding of fatigue patterns in ME/CFS and support treatment evaluation.
This study does not prove the device can reliably diagnose ME/CFS in real-world clinical settings or patient populations. It is a technical validation in a controlled laboratory environment and does not establish whether blink rate changes are specific to ME/CFS versus other fatigue-causing conditions. The study also does not yet demonstrate long-term wearability, user acceptance, or practical clinical utility.
About the PEM badge: “PEM required” means post-exertional malaise was an explicit required diagnostic criterion for participant inclusion in this study — not that PEM was studied, observed, or discussed. Studies using criteria that do not require PEM (e.g. Fukuda, Oxford) are tagged “PEM not required”. How the atlas works →
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Primary citation
Li, Tianyi, Park, Seo-Hyun, Lee, Changwoo, Kim, Shawn, Kwon, Younghoon, Kim, Hojun, et al. (2025). Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment.. Advanced sensor research. https://doi.org/10.1002/adsr.202500027
BibTeX
@article{mecfsatlas-li-2025-intelligent-eye,
author = {Li, Tianyi and Park, Seo-Hyun and Lee, Changwoo and Kim, Shawn and Kwon, Younghoon and Kim, Hojun and Chung, Jae-Hyun},
title = {Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment.},
journal = {Advanced sensor research},
year = {2025},
doi = {10.1002/adsr.202500027},
note = {PubMed: 40662140},
url = {https://www.mecfsatlas.com/evidence/li-2025-intelligent-eye},
}Atlas snapshot reference
ME/CFS Atlas. Generator v1 / Scanner v1.4 / policy v0.1. Accessed 2026-05-29. https://www.mecfsatlas.com/evidence/li-2025-intelligent-eye
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