Purpose

To evaluate an artificial intelligence-enabled virtual reality (VR) eye-tracking system (BulbiCAM) for automated measurement of eyelid position in blepharoptosis assessment.

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Methods

101 patients with suspected blepharoptosis underwent clinician (standard of care) and VR (BulbiCAM) measurements of MRD1 and MRD2.The BulbiCAM device employs high-speed infrared video-oculography with convolutional neural network algorithms to automatically detect the pupil centre, corneal glint reflex, and eyelid margins. Agreement between the two methods was analysed using Pearson correlation and Bland–Altman plots. A predefined subset of participants were invited for a second visit >2 weeks after first assessment, to assess test–retest repeatability of the automated VR measurements. Feasibility was evaluated using both operator-recorded metrics and participant-reported experience measures.

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Results

Automated measurements showed high agreement with standard clinical assessment, with mean differences of +0.29 mm for upper eyelid position and +0.01 mm for lower eyelid position. Strong correlations were observed between methods. Test-retest repeatability in 36 patients demonstrated mean differences of -0.03 mm and +0.27 mm between visits. Successful acquisition was achieved in all participants with a median of one attempt, and 98% reported the device as comfortable and easy to use.

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Conclusion

This study demonstrates that AI-enabled VR eye-tracking provides automated eyelid measurements with excellent agreement to clinical standards, good repeatability, and high feasibility, supporting its potential role in enhancing objectivity and efficiency of ptosis assessment in both clinical practice and research settings.

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Additional Authors

First name	Last name	Base Hospital / Institution
Reenette	Savant	University of Leicester
Agni	Mokka	Leicester Royal Infirmary
Mario Frank	Farrugia	Leicester Royal Infirmary
Mary	Awad	Leicester Royal Infirmary
Joyce	Burns	Leicester Royal Infirmary
Antonella	Berry-Brincat	Leicester Royal Infirmary
Raghavan	Sampath	Leicester Royal Infirmary
Mervyn	Thomas	Leicester Royal Infirmary

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