A computer-implemented solution developed by the UB that uses binocular eye-tracking and pupillometry to identify signs of early Alzheimer\u2019s Disease (AD) linked to neurodegenerationassociated protein biomarkers and offers an early intervention approach to reduce taupathology and improve cognition. It provides a non-invasive and accessible platform for early diagnosis, monitoring, and intervention.<\/p>\n
AD is the leading cause of dementia, accounting for 60\u201380% of cases. The condition is biologically defined by amyloid-\u03b2 and tau accumulation (A+T+) with neurodegeneration under the AT(N) framework. The locus coeruleus (LC), affected early by tau pathology, regulates attention, arousal, pupil size, and eye movements. Current diagnostic methods, such as PET and CSF analysis, are accurate but invasive, costly, and difficult to scale.<\/p>\n
UB researchers have identified distinct oculomotor and pupillary patterns in individuals with a biomarker-positive profile for AD, proposing their use as non-invasive marker of LC-mediated attentional integrity and intervention response. The technology consists of a digital eye-tracking software that offers a non-invasive early AD assessment. The program analyses binocular eye movements, cognitive vergence, and pupil responses during\u00a0 visual tasks to estimate AT(N)related neurodegenerative profiles. Aditionally, a digital intervention is proposed through interactive tasks, using 40 Hz visual stimulation, targeting the LC to reduce tau pathology and improve cognitive performance, within a critical therapeutic window.<\/p>\n
A functional prototype has been developed, demonstrating technical feasibility and initial usability in older adults. The next step is to optimize the algorithm and prepare the system for clinical validation. Remaining work includes improving the algorithm\u2019s robustness with additional data, and further refining usability to ensure adoption in real-world settings.<\/p>\n","protected":false},"excerpt":{"rendered":"
Executive summary A computer-implemented solution developed by the UB that uses binocular eye-tracking and pupillometry to identify signs of early…<\/p>\n","protected":false},"author":2,"featured_media":24955,"parent":1399,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"page-tecnologies.php","meta":{"_acf_changed":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"class_list":["post-24958","page","type-page","status-publish","has-post-thumbnail","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/pages\/24958","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/comments?post=24958"}],"version-history":[{"count":3,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/pages\/24958\/revisions"}],"predecessor-version":[{"id":24964,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/pages\/24958\/revisions\/24964"}],"up":[{"embeddable":true,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/pages\/1399"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/media\/24955"}],"wp:attachment":[{"href":"https:\/\/www.fbg.ub.edu\/es\/wp-json\/wp\/v2\/media?parent=24958"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}