https://matteocampagna.com/en/registry/mind/automatic-quiet-eye-measurement-eog Changes to this claim in Matteo Campagna's evidence registry: its status, its year-by-year history, revisions of the page. en-gb https://matteocampagna.com/en/registry/mind/automatic-quiet-eye-measurement-eogOnly one group has tried, at the University of Mersin. Ten club archers, six arrows each, recorded with electro-oculography, the electrical potential measured around the eye; an expert marked the start and end of the quiet eye by hand in the sixty stretches of signal, and five neural networks learned to reproduce those annotations. The two with temporal memory reach an accuracy of about 93 and 92 per cent, against 51 to 68 for a traditional classifier, and in the best conditions they miss the onset by 7 to 9 milliseconds and the end by 4 to 6. The result depends on cleaning the signal, though: on the raw trace the best network drops to 84 per cent. Three serious limits remain: ten archers from a single club, whose discipline and competitive level the paper does not give, a validation that may have mixed arrows from the same archer between training and testing, and a reference that is one expert's annotation rather than the video measure the quiet eye literature usually relies on.claim:quiet-eye-misura-automatica:revision:2026-08-01:2Sat, 01 Aug 2026 08:00:00 GMT https://matteocampagna.com/en/registry/mind/automatic-quiet-eye-measurement-eogclaim:quiet-eye-misura-automatica:new_claim:2026-06-17:riportatoWed, 17 Jun 2026 08:00:00 GMT