Discriminating cerebral palsy by quantifying ocular motion

Jully González; Santiago Silva; Gustavo Pineda; Eduardo Romero

doi:10.1117/12.2542576

3 January 2020 Discriminating cerebral palsy by quantifying ocular motion

Jully González, Santiago Silva, Gustavo Pineda, Eduardo Romero

Proceedings Volume 11330, 15th International Symposium on Medical Information Processing and Analysis; 1133013 (2020) https://doi.org/10.1117/12.2542576
Event: 15th International Symposium on Medical Information Processing and Analysis, 2019, Medelin, Colombia

Abstract

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.

Citation Download Citation

Jully González, Santiago Silva, Gustavo Pineda, and Eduardo Romero "Discriminating cerebral palsy by quantifying ocular motion", Proc. SPIE 11330, 15th International Symposium on Medical Information Processing and Analysis, 1133013 (3 January 2020); https://doi.org/10.1117/12.2542576

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