[Study of New Amblyopia Diagnostic and Treatment Method and System Implementation]

Area of Science:

• Ophthalmology
• Neuroscience
• Biomedical Engineering

Background:

• Amblyopia, a prevalent childhood condition, presents significant challenges with conventional treatments.
• Existing methods often suffer from poor patient compliance and suboptimal recovery of binocular and stereoscopic vision.
• Traditional amblyopia therapies can also negatively impact the vision of the healthy eye.

Purpose of the Study:

• To develop a novel, individualized amblyopia treatment system addressing the shortcomings of current approaches.
• To enhance treatment efficacy by integrating pattern reversal visual evoked potential (P_VEP) feedback with dichoptic training principles.
• To improve binocular and stereoscopic vision recovery in children diagnosed with amblyopia.

Main Methods:

• Development of an EEG data acquisition and synchronized trigger circuit utilizing an I/O data collection card.
• Real-time sampling of raw EEG signals, followed by digital filtering, average superposition, and wavelet algorithms to extract P_VEP waveforms.
• Accurate measurement of P_VEP latency and peak.
• Implementation of an individualized treatment strategy based on a dichoptic training model, optimizing spatial frequency of training images and incorporating 3D display technology.

Main Results:

• Successful real-time sampling and processing of EEG signals to extract P_VEP.
• Accurate quantification of P_VEP parameters (latency and peak).
• Development of a personalized treatment approach combining P_VEP feedback and optimized dichoptic training.

Conclusions:

• The developed system offers a promising, individualized approach to amblyopia treatment.
• Integration of P_VEP feedback and dichoptic training enhances the potential for effective vision recovery.
• The system's ability to personalize treatment parameters may lead to improved patient outcomes and compliance.