Eye C Better Corp

New, Non-invasive (no-puff, No-touch), Tonometry Method: Remote Photonic Iop Biomonitoring Using the Damping Factor of Transitional Oscillations After Terminating Its Stimulation by a Sound Wave. - Project Summary/abstract Glaucoma Is a Major Source of Irreversible Blindness Affecting More Than 5 Million Americans and Costing the U.s. Economy $2.86 Billion/year. Current Glaucoma Treatments Include Frequent Eye-contacting Intraocular Pressure (IOP) Measurements Requiring Anesthetic Eye Drops and Interpretation by Trained Healthcare Professionals Which Introduces Bias. Our Methodology, Photonic Iop Biomonitoring (pib), Allows High- Precision, Non-contact, Non-air Puff, Reproducible and Semi-continuous Iop Monitoring Without Clinician Interpretation. Pib Measures Sound Wave Induced Scleral Oscillations by Monitoring Laser Speckle Patterns. Physical Modelling With Machine Learning (ML) Algorithms Deduce Iop. Ultimately, Our Goal Is Miniaturization Into Monoculars or Eyeglasses Allowing Patients to Take Real-time Iop Measurements Relayed to Physicians for Treatment Recommendations and Medication Dispensing Through a Smart Phone-based System. Aim 1: Develop a Physical Model to Seed ML Algorithms for Iop Resolution, Accuracy and Repeatability. ML Is Seeded With a Random Initial State When No Test Subject Knowledge Is Available. in Contrast, a Physical Model Based on Newton’s Equations of Motion Indicates the Value of a Continuous Variable (IOP) Given Physical Parameter Values Characteristic of the Test Subject. Ultimately, a Physical Model Would Identify Iop Without Further ML Class Regression. Pib Free From ML Optimization Eliminates the Need for Calibration and Physician Interpretation. Output of This Physical Model Will Seed Simpler ML Algorithms to Achieve Better Resolution, Accuracy and Repeatability. Hypothesis 1A: Porcine Eye Pib Measurements Can Achieve Resolution of ≤1 MMHG. Hypothesis 1B: Porcine Eye Pib Iop Measurements Will Yield Accuracy and Repeatability of 2 MMHG Standard Deviation or Less. These Hypotheses Will Be Tested by Measuring Porcine Eyes With Iop Within the Range of 5 MMHG Up to 60 MMHG. Aim 2: Implement Pupil Monitoring: an Eye Position Monitoring System Will Aid Subjects in Keeping Their Pupil Directed at the Pupil Monitor. Deviations From This Nominal Position Will Turn Off the Laser and Pause Data Acquisition. Hypothesis 2A: Monitoring Eye Position Will Improve Patient Safety. Hypothesis 2B: Temporal Filtering of Large Deviations Will Improve Measurement Accuracy and Repeatability. Feasibility Will Be Assessed by 1) Showing That Light Entering the Porcine Pupil Cannot Exceed a Threshold Below the Standard Safety Criteria of 0.6MW, and 2) by Showing That Iop Prediction Accuracy, Precision and Repeatability Improves in Pig Eye Tests by Incorporating Eye Position Data. Aim 3: Assess Pib Repeatability in Human Eyes: Pib Tests of 30 Healthy Human Eyes (15 Healthy Human Subjects) in Phase I Will Inform the Development Roadmap in a Subsequent Phase Ii Trial. Hypothesis 3A: Pib Repeatability in Human Eyes Is Equal to That of a Comparable Set of Pig Eyes Aim 4: Safety and Comfort: We Will Monitor for Patient Comfort and Signs of Corneal Superficial Punctate Epithelial Erosions or Dryness. Hypothesis 3B: Pib Will Be Found Innocuous as Evaluated by Comparable or Fewer Adverse Events Than Gat and Comparable or Greater Comfort.