PERCLOS‑Based Drowsiness Detection: Relevance to Post‑Night‑Shift Driving

PERCLOS‑Based Drowsiness Detection: Relevance to Post‑Night‑Shift Driving

Registration: PMCID: PMC10108649

Status: Published

Tags: Commute safety, Review, Wearables & digital health

External URL: https://pmc.ncbi.nlm.nih.gov/articles/PMC10108649/

Summary

This narrative review looked at PERCLOS (the percentage of time your eyes are mostly closed) as a way to detect drowsiness. Research shows PERCLOS rises with sleep loss, sleep restriction, and during nighttime hours, making it one of the most validated measures of fatigue across lab studies, driving simulators, and real driving. Still, it isn’t perfect—PERCLOS can miss moderate drowsiness, may be less reliable in certain groups (like older adults), and definitions vary across devices. The review recommends further standardization and combining PERCLOS with other signals (like blinks or brain activity) to improve accuracy in real-world use.

Why It Matters For Night Shift Workers and Night Owls

For night-shift workers, fatigue can creep in before you even realize it. Because PERCLOS measures subtle eyelid changes linked to drowsiness, it could power tools like wearables or in-car monitors that warn you when your alertness is slipping. While the technology still needs refining, the idea is clear: your eyes can reveal sleepiness before your brain catches up, offering an extra safety net during high-risk times like late-night tasks or commutes home.

Tags

  • Commute safety
  • Review
  • Wearables & digital health

Notes

Method/tech review with night‑shift examples.

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