One-stop strabismus digital diagnosis via AI-integrated skin-like and wearable “Eyelectronics”

Read full text
Authors: Yong Yang, Xin Liu, Jiankai Tang, H. W. Guo, Jinsong Zhang, Yuntao Wang, Yonghong Jiao, Yihao Chen, Xue Feng
Cited by: 3
References: 38

Abstract

Strabismus, affecting ~4% of children, impairs vision and psychosocial health. However, clinical diagnosis requires multiple instruments and stepwise examinations of ocular alignment, extraocular muscle function, and deviation angle. It is limited by low diagnostic objectivity, poor pediatric compliance, and high cost. Here, we propose a strategy for one-stop strabismus digital diagnosis via artificial intelligence (AI)-integrated, skin-like, and wearable "Eyelectronics." The ultralightweight, imperceptible eye-wearable system features an ultrathin (~60 micrometers in thickness), breathable, and multidirectional (0°/45°/90°) strain-sensing array conformally adapted to the sensitive eyelid. It enables wireless, mild-restricted measurement of eyelid deformation during eye movements. Through biomechanical modeling validated by ocular magnetic resonance imaging simulations, we establish a prior correlation between eyelid deformation and eye movements. The Eyelectronics, powered by our physiology knowledge-driven end-to-end AI algorithm, achieves simultaneous measurement of strabismus angle and identification of paretic muscle. It delivers a 96.6% four-direction classification accuracy and a 1.2° measurement accuracy in ocular motility examinations. Clinical benchmarking against the clinical standard (Hess screen test) confirmed diagnostic agreement (intraclass correlation = 0.978). This system bridges quantitative biomechanical sensing with digital diagnosis, promoting a paradigm for future strabismus treatment.

Fields of Study & Subjects

Gaze Tracking and Assistive Technology Ophthalmology and Eye Disorders Vestibular and auditory disorders

Publication details

Journal / source
Science Advances
Publisher
American Association for the Advancement of Science (AAAS)
Volume
12
Issue
5
Pages
eaeb7242–eaeb7242
Publication date
28 January 2026
Language
EN