Model-Based Separation, Detection, and Classification of Eye Movements.

Objective: We present a physiologically motivated eye movement analysis framework for model-based separation, detection, and classification (MBSDC) of eye movements. By estimating kinematic and neural controller signals for saccades, smooth pursuit, and fixational eye movements in a mechanistic model of the oculomotor system we are able to separate and analyze these eye movements independently.

Methods: We extended an established oculomotor model for horizontal eye movements by neural controller signals and by a blink artifact model.

Estimation of Neural Inputs and Detection of Saccades and Smooth Pursuit Eye Movements by Sparse Bayesian Learning.

Eye movements reveal a great wealth of information about the visual system and the brain. Therefore, eye movements can serve as diagnostic markers for various neurological disorders. For an objective analysis, it is crucial to have an automatic and robust procedure to extract relevant eye movement parameters.