š§ šļø WearEyeļ¼ Eyelectronics for Strabismus Diagnosis
š Overview
Strabismus affects millions of patients worldwide, yet traditional diagnostic tools are subjective and inconvenient. We propose Eyelectronics, a lightweight, imperceptible, AI-embedded wearable device that digitizes strabismus diagnosis via eyelid strain analysis.

šÆ Key Features
⢠Multidirectional Strain-Sensing: A 60μm ultrathin HMS array (0°/45°/90°) measures eyelid deformation caused by eye movements.
⢠Wireless & Comfortable: The system includes a flexible sensing patch, compact signal circuit, and Bluetooth transmissionāoptimized for clinical use.
⢠MRI-based Validation: 3D FEA confirms eyelid deformation correlates with eye position.
š§ AI Models
⢠InceptionTime-Tiny: A lightweight deep learning model classifies eye movement direction with 96.6% accuracy.
⢠Regression MLP: Predicts eye movement angles with 1.2° mean absolute error.
⢠Code includes both training and evaluation scripts with sample data and pretrained models.
š§Ŗ Clinical Validation
Our system achieves high agreement (ICC = 0.998) with gold-standard Hess screen test in real patient trials, offering a one-stop digital solution for strabismus angle measurement and EOM evaluation.
š Contents
š classification_code (train.ipynb)
š regression_code (train_regression.ipynb)
š data (X_test.npy, y_test.npy)
š README.md
𧬠Authors
Yong Yang, Xin Liu, Jiankai Tang, Yihao Chen, Xue Feng, et al.