Advanced systems for precision diagnosis and therapy of visual disorders

The objective of this thesis was to design, develop, and validate a novel noncontact method for measuring intraocular pressure (IOP) through the analysis of corneal dynamics induced by natural blinking. The proposed method leverages high-speed ocular imaging and image processing techniques to quantify corneal rebound, associated with IOP, following eyelid-induced deformation, thus eliminating the need for contact-based tonometry. An acquisition system was developed, consisting of a modified ophthalmic chin rest and a high–frame rate camera, to capture the lateral corneal profile during blinking. From the acquired images, ocular masks were generated by applying a deep learning–based segmentation model. Subsequently, a geometry-based approach was applied to extract the corneal profile from these masks. The longitudinal displacement of this profile was analyzed during the eye-opening phase of the blink. The temporal behavior of the displacement followed an exponential curve, from which two biomechanical metrics describing corneal dynamics were derived: the time constant (τ), representing the speed of corneal rebound, and the displacement amplitude (A), quantifying the extent of corneal profile movement. These metrics were first evaluated in terms of intra-subject repeatability on healthy participants, providing reference variability ranges for future clinical studies. The method was then applied to assess corneal dynamics under baseline and elevated IOP conditions, the latter induced through the Valsalva maneuver and confirmed with a portable tonometer. Results obtained from healthy volunteers showed a statistically significant reduction in τ under elevated IOP, indicating a faster corneal rebound, while A remained unchanged. This suggests that τ is a promising parameter for detecting relative IOP variations, whereas A is less sensitive to pressure changes. By enabling continuous, non-invasive, and home-based IOP monitoring, this approach has the potential to complement or partially replace traditional tonometry, thereby improving early glaucoma detection and follow-up. In addition, the thesis explores complementary developments, including noise-robust blink detection algorithms and complete ECG waveform segmentation, broadening the scope of non-contact biomedical measurement systems.