Evidence map›Paper›PMID 42890905›Full record

ArticleFrontiers in cell and developmental biology2026

Research on an elderly low-vision field-aid system based on augmented reality.

Xi Chen, Xu Jing, Tinglong Liu, Pin Ju, Yige Zhang, Raymond Liu, Wenlong Liu, Like Xie, Xiaofeng Hao

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xi Chen *Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xu Jing *Eye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Tinglong Liu *Center for Information Technology, Dalian Polytechnic University, Dalian, China.
Pin JuEye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Yige ZhangEye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Raymond LiuUniversity of Cambridge, Cambridge, United Kingdom.
Wenlong LiuSchool of Information and Communication Engineering, Dalian University of Technology, Dalian, China.
Like XieEye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Xiaofeng HaoEye Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The global population is aging rapidly. Low vision among the elderly has become increasingly common. This condition seriously affects their quality of life. This study aims to develop a low-vision field-aid system for the elderly. The system is based on augmented reality (AR). It is designed to address visual field deficiency in this population. Methods: The proposed system integrates several key technologies. These include clinical field diagnosis assistance. Other components are AR-based field expansion, precise field detection, personalized field compensation, and intelligent environmental perception. The research encompasses system design, implementation of core technologies, experimental verification, and performance evaluation. Results: Experimental verification and performance evaluation were conducted. The results demonstrate that the system effectively expands the visual field. It also enhances environmental perception. Moreover, it improves mobility safety for elderly low-vision users. The system achieves personalized field compensation. This is based on individual field defect maps. It also shows stable performance under various environmental conditions. Conclusion: This AR-based field-aid system provides an innovative technical solution. It is designed for elderly low-vision rehabilitation. The system has the potential to significantly improve visual function. It can also enhance daily living safety.

Indexed as

augmented realityelderly low visionquality of liferehabilitation medicinevisual aid

Identifiers

PMID42890905
PMCPMC13672509

What OpenQuestion holds

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Registered trials

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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.