Monitoring eyelid blinking and movement is crucial for patients with facial dystonia. This work presents a novel mobile application approach to assess eyelid movement of eye-opening and closing over time obtained from patients’ videos. The application analyzes the frequency and amplitude of altered eye movements in patients with blepharospasm who received Botox treatment. The application used the Flutter platform, offering cross-platform compatibility for Android and iOS devices, ensuring widespread accessibility. The chosen architectural framework, clean architecture, enhances maintainability, reduces complexity, and improves codebase modifications, contributing to robust, easily upgradable applications. Hive, a NoSQL database solution for Flutter applications, managed local databases. Its integration offers robust storage and retrieval, aiding data analysis. As for the machine learning used, the eyelid opening states were analyzed using the Google ML Kit’s Face« Detection API, which is optimized for mobile devices and capable of discerning specific facial contours. The application collected data from videos of subjects with blepharospasm before and after Botox treatment, calculating eye-opening probabilities to track clinical progression accurately. Results demonstrated significant improvements in eye-opening probability post-treatment, confirming its effectiveness in capturing changes in eyelid movement. Further analysis using graphical representation and data export to Excel facilitated detailed comparisons and enhanced clinical understanding. The application’s usability extends beyond clinical settings, enabling patients to monitor their progress at home. This accessibility, coupled with its effectiveness in assessing eyelid movement disorders and treatment outcomes, underscores the utility of mobile technology in healthcare, benefiting both professionals and patients. Overall, this study showcases the potential of mobile applications in tracking and evaluating complex physiological parameters, offering a convenient and effective tool for advancing medical diagnostics and patient care, especially to aid public health services, such as The Brazilian Unified Health System (SUS).