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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2511.14361 |
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| _version_ | 1866908753819860992 |
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| author | Bonesso, Gustavo Adolpho de Godoy, Carlos Marcelo Gurjão Osaki, Tammy Hentona Osaki, Midori Hentona Santos, Bárbara Moreira Ribeiro Trindade dos Washiya, Juliana Yuka Coelho, Regina Célia |
| author_facet | Bonesso, Gustavo Adolpho de Godoy, Carlos Marcelo Gurjão Osaki, Tammy Hentona Osaki, Midori Hentona Santos, Bárbara Moreira Ribeiro Trindade dos Washiya, Juliana Yuka Coelho, Regina Célia |
| contents | 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 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, and its clinical validation. The validation was performed using 45 videos from patients, whose blinks were manually annotated by an ophthalmology specialist as the ground truth. The Bapp's performance was evaluated using standard metrics, with results demonstrating 98.4% precision, 96.9% recall, and an overall accuracy of 98.3%. These outcomes confirm the reliability of the Bapp as a portable, accessible, and objective tool for monitoring eyelid movements. The application offers a promising alternative to traditional manual blink counting, supporting continuous ocular health monitoring and postoperative evaluation in clinical environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_14361 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Clinically-Validated Innovative Mobile Application for Assessing Blinking and Eyelid Movements Bonesso, Gustavo Adolpho de Godoy, Carlos Marcelo Gurjão Osaki, Tammy Hentona Osaki, Midori Hentona Santos, Bárbara Moreira Ribeiro Trindade dos Washiya, Juliana Yuka Coelho, Regina Célia Computer Vision and Pattern Recognition Artificial Intelligence 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 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, and its clinical validation. The validation was performed using 45 videos from patients, whose blinks were manually annotated by an ophthalmology specialist as the ground truth. The Bapp's performance was evaluated using standard metrics, with results demonstrating 98.4% precision, 96.9% recall, and an overall accuracy of 98.3%. These outcomes confirm the reliability of the Bapp as a portable, accessible, and objective tool for monitoring eyelid movements. The application offers a promising alternative to traditional manual blink counting, supporting continuous ocular health monitoring and postoperative evaluation in clinical environments. |
| title | Clinically-Validated Innovative Mobile Application for Assessing Blinking and Eyelid Movements |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence |
| url | https://arxiv.org/abs/2511.14361 |