Evidence map›Paper›PMID 41604478›Full record

ArticleScience advances2026

One-stop strabismus digital diagnosis via AI-integrated skin-like and wearable "Eyelectronics".

Yong Yang, Xin Liu, Jiankai Tang, Hengyi Guo, Jinsong Zhang, Yuntao Wang, Yonghong Jiao, Yihao Chen, Xue Feng

Abstract read
In one paragraph

Article in Science advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Yong YangState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-1499-7978
Xin LiuState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0009-0004-5920-0450
Jiankai TangDepartment of Computer Science and Technology, Tsinghua University, Beijing 100084, China.ORCID 0009-0009-5388-4552
Hengyi GuoState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.
Jinsong ZhangState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0009-0000-6419-0331
Yuntao WangDepartment of Computer Science and Technology, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-4249-8893
Yonghong JiaoBeijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.ORCID 0000-0001-6332-457X
Yihao ChenState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0000-0002-1213-5792
Xue FengState Key Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing 100084, China.ORCID 0000-0001-9242-8474

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceStrabismusWearable Electronic DevicesAlgorithmsBiomechanical PhenomenaDigital HealthEye MovementsHumansMagnetic Resonance Imaging

Identifiers

PMID41604478
PMCPMC12851036

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.