Yin Tao, Jia Chen, Xiaoli Liu, Zhen Fang, Dalong Zhang, Qinwu Zhou, and Bo Zhang
Amblyopia, Pattern Visual Evoked Potential(P_VEP), Best spatial frequency, Wavelet decomposition, Average superposition
Amblyopia is a common visual related eye disease in childhood. Although traditional treatment to amblyopia is effective, there are still some disadvantages, such as poor compliance, easily leading to the healthy eyesight problem, the poor recovery of binocular and stereoscopy vision，the lack of objective parameter guidance, etc. Therefore, a new personalized amblyopia treatment solution is put forward to solve these problems combined with Pattern Visual Evoked Potential (P_VEP). A complete software system is built, including diagnosis module, treatment module, data management module and expert module. The EEG data acquisition and synchronized trigger circuit are designed using ADS1299 EEG Front-End and IO data collecting card to collect the raw EEG signal. Digital filtering algorithm, average superposition algorithm and wavelet algorithm are used to extract P_VEP from the raw EEG data acquired by the hardware circuit. The latency and peak of P_VEP wave is measured. The best spatial frequency is searched and obtained from the treatment training curve. It is updated automatically as treatment continues.