Clinically-Validated Innovative Mobile Application for Assessing Blinking and Eyelid Movements
It provides a portable and accessible tool for monitoring ocular health in clinical settings, though it is incremental as it applies existing methods to a new domain.
This study tackled the challenge of objectively assessing eyelid movements by clinically validating Bapp, a mobile application for real-time blink analysis, achieving 98.3% accuracy, 98.4% precision, and 96.9% recall.
Blinking is a vital physiological process that protects and maintains the health of the ocular surface. Objective assessment of eyelid movements remains challenging due to the complexity, cost, and limited clinical applicability of existing tools. This study presents the clinical validation of Bapp (Blink Application), a mobile application developed using the Flutter framework and integrated with Google ML Kit for on-device, real-time analysis of eyelid movements. The validation occurred using 45 videos from real patients, whose blinks were manually annotated by ophthalmology specialists from the Paulista School of Medicine of the Federal University of Sao Paulo (EPM-UNIFESP) to serve as the ground truth. Bapp's performance was evaluated using standard metrics, including Precision, Recall, and F1-Score, with results demonstrating 98.4% precision, 96.9% recall, and an overall accuracy of 98.3%. These outcomes confirm the reliability of Bapp as a portable, accessible, and objective tool for monitoring both normal and abnormal eyelid movements. The application offers a promising alternative to traditional manual blink counting, supporting continuous ocular health monitoring and postoperative evaluation in clinical environments.