Visual disorders are one of the common side problems in Cerebral Palsy (CP) being reported with an incidence between 50% to 90% of the cases. These visual disorders may interfere with the developmental process and motor learning of these children. This work presents a robust method to spatio-temporally characterize the ocular motion in CP. Smooth pursuit and saccadic eye tasks were assessed by using simple visual stimuli and recording the eye trajectories during the task. A dense optical flow estimation of the ocular movement is modulated by a visual attention model which extracts relevant eye motion information. Analyses in time and frequency domain were performed suggesting statistical differences (p-value < 0.01) in Signal to Noise Ratio (SNR) and Wavelet coefficients for both saccadic and smooth pursuit tasks.
Cerebral palsy (CP) is a large group of motion and posture disorders caused during the fetal or infant brain development. Sensorial impairment is commonly found in children with CP, i.e., between 40-75 percent presents some form of vision problems or disabilities. An automatic characterization of the cerebral palsy is herein presented by estimating the ocular motion during a gaze pursuing task. Specifically, After automatically detecting the eye location, an optical flow algorithm tracks the eye motion following a pre-established visual assignment. Subsequently, the optical flow trajectories are characterized in the velocity-acceleration phase plane. Differences are quantified in a small set of patients between four to ten years.
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