Two Dimensional Oculomotor Plant Mechanical Model (2DOPMM)
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This research study builds a two dimensional Oculomotor Plant Mechanical Model (2DOPMM) that is capable of generating eye movement trace and also simulating fixation and saccade eye movement signal on a two dimensional plane. The key difference between the proposed model and the models presented previously is a design that is geared towards linearity and capability of integration into a real-time Human Computer Interaction system while providing force output for each extraocular muscle with values close to physiological measurements. The model is represented as a twelve order system created by a set of linear mechanical components representing major anatomical properties of extraocular muscles and the eye globe: muscle location, elasticity, viscosity, eye-globe rotational inertia, muscle active state tension, length tension and force velocity relationships. The model is driven by a neuronal control signal and consists of four extraocular muscles (medial, lateral, superior and inferior recti) and an eye globe. Linearity is a key point ensuring a real-time performance in an online implementation of the model with twelve order representation providing close match to the eye anatomical structure.
The goal of the model is to provide an accurate eye position trace during saccades with the duration and main sequence relationships within the physiological capabilities of a normal human. The accuracy of the model is verified against three types of independent eye movement recordings, employing various setups and eye tracker equipment, and 49 subjects. Results indicate that the positional error between the actual and the simulated trajectories is two times smaller than the positional difference between left and right eyes. Practical application of the model lies in the areas requiring the analysis of the eye position trace and properties of the neuronal control signal. Preliminary studies indicate the potential applicability of these types of models in biometrics and in the design of the novel human-computer interaction techniques. A further application of the proposed model exists in the area of extraocular muscle effort estimation and Human Computer Interaction.