BlinkAlarm - Prevent eyestrain, dryness with real-time computer vision!

Hacker News

I often struggle with dry, strained eyes from long duration computer usage. It turns out when focusing intently, human blink rates decline from a healthy 15-20 per minute to 3-4 (or even fewer in some cases). I wrote a quick script that calculates facial landmarks on your webcam feed in realtime and plays a sound if you fail to blink for a configurable number of seconds. I use the common way of detecting a blink, which is to calculate the ratio between the height and width of the visible portion of the eye. This can be done with just 6 landmarks -- two on the upper eyelid, two on the lower eyelid, and one on either side of the eye. I found that this doesn't work well in all angles / postural positions, so I also augment this with another metric that corrects for head tilt. It's not perfect (if you tilt your head such that your ear is brought closer to your shoulder, it may over-detect blinks) but it's extremely good in normal scenarios where I don't knot myself into a pretzel. It runs significantly faster than realtime on my M2, and I leave it on all day when I work from home.

Visit product View on Hacker NewsMar 25, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, using · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: ios, way · Missing: mobile apps, personal, entrepreneurs

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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