Visual acuity classification using single trial visual evoked potentials.

Several researches have been done to identify visual system characteristics. Some of them are based on the processing of the brain signal recordings. Visual evoked potentials (VEPs) are electrical signals which are produced in response to the visual stimuli and recorded by means of electrodes placed on the head. These signals are usually characterized by the amplitude and latency of their peaks. Different types of visual stimuli and visual system characteristics can affect the shape and hence the characteristics of VEPs. In this paper, proper visual stimuli were used and VEPs were recorded in order to classify visual acuity. To achieve this goal, visual evoked potentials were recorded and processed in time, frequency and time-frequency domains. In order to preserve dynamics of the recorded signals, two algorithms for single-trial VEP extraction were used. The results of the classification of visual acuity in both average and single-trial VEPs are acceptable.