Smartphone-based digital ruler for automated strabismus measurement in clinical and remote settings

Dear Editor, Strabismus, a prevalent ocular motility disorder, affects approximately 2%–4% of the global population and is characterized by misalignment of the visual axes due to neuromuscular imbalance or cranial nerve dysfunction. It can lead to diplopia, amblyopia, and impaired depth perception, particularly in pediatric patients, if not diagnosed early.[1] Traditional diagnostic methods, such as the Hirschberg test, cover–uncover test, and prism alternate cover test, require trained personnel and clinical infrastructure, limiting access in underserved or remote settings.[1] These limitations have prompted the development of automated, accessible tools to improve early detection and monitoring of strabismus. A recent innovation, a smartphone-based digital ruler (DRS), offers automated measurement of ocular deviation using deep learning and three-dimensional (3D) reconstruction algorithms. This tool analyzes short video recordings of cover tests to quantify horizontal and vertical strabismus angles with ophthalmologist-level accuracy, eliminating the need for manual prism bars. Beyond strabismus, this technology holds diagnostic potential for conditions such as thyroid eye disease, cranial nerve palsies, convergence insufficiency, and myasthenia gravis, where precise ocular alignment assessment is essential for clinical decision-making.[2,3] Recent multicenter validation studies have demonstrated strong translational promise. Wang et al. reported in NEJM AI that the DRS achieved 95% agreement with manual prism testing across pediatric and adult cohorts, including esotropia, exotropia, and paralytic strabismus.[4] Complementing this, Kurdthongmee et al. validated artificial intelligence (AI)-based strabismus detection in monocular eye images for telemedicine applications, confirming feasibility in resource-limited MDPI. Together, these findings illustrate complementary strengths: smartphone-based tools can reduce interobserver variability in clinics while enabling scalable screening in teleophthalmology programs.[5] Validated in a 2025 multicenter study (NEJM AI), the DRS achieved 95% concordance with prism alternate cover testing across pediatric and adult cohorts, including esotropia, exotropia, and paralytic strabismus.[4] Beyond strabismus, similar AI-based ocular alignment tools have shown promise in: Thyroid eye disease: Automated detection of ocular misalignment and activity scoring Cranial nerve palsies: Quantifying deviation angles for diagnosis and monitoring Convergence insufficiency and myasthenia gravis: Tracking subtle motility changes critical for treatment decisions. Yarkheir et al. demonstrated that deep learning analysis of facial images could classify strabismus with high accuracy, supporting telemedicine applications.[2] Shin et al. validated AIbased assessment of thyroid eye disease using facial images, reinforcing the broader applicability of ocular alignment algorithms.[3] Together, these studies highlight that smartphonebased tools can extend beyond strabismus, offering scalable diagnostics for multiple ocular motility disorders. The ubiquity of smartphones makes the DRS particularly feasible in low-resource settings. Unlike prism bars or synoptophores, which require specialized equipment and trained ophthalmologists, the DRS can be deployed by community health workers or school screening programs. Offline inference allows use in areas with limited internet connectivity, while teleophthalmology platforms enable remote specialist review. Despite its promise, limitations remain: accuracy may be affected by poor lighting, unstable fixation, or low-resolution video capture, and performance in complex strabismus patterns such as dissociated vertical deviation is still under investigation.[4] Nevertheless, feasibility in developing countries is strengthened by portability, cost-effectiveness, and integration with telemedicine platforms.[5] The smartphone-based digital ruler represents a significant advancement in accessible, AI-assisted strabismus diagnostics. Future directions should include algorithm refinement for complex motility patterns, integration with electronic health records, and deployment in school screening and primary care settings. Cost-effective implementation and clinician training will be essential for widespread adoption. Accurate strabismus diagnosis is well established as critical for preventing amblyopia and visual dysfunction.[1] What is new here is the introduction of a smartphone-based digital ruler that utilizes AI and 3D reconstruction to provide automated, ophthalmologist-level measurements of deviation. Recent validation shows high concordance with prism testing and reduced variability, supporting its role as a scalable, noninvasive tool to enhance early detection, teleophthalmology, and equitable access to care.[2–5] Author contribution statement E.H: Conceptualization, Methodology, Software, Data curation, Writing Original draft preparation, Reviewing and Editing; S.N.U.S: Writing Original draft preparation, Reviewing and Editing. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Use of generative AI and AI-assisted technologies No AI or AI-assisted technologies were used in the preparation of this manuscript. Consent for publication Consent for publication is not applicable as this study involves publicly available data. Provenance and peer review Not commissioned, externally peer-reviewed. Data availability statement The data are available for access. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.