Physics-based modeling and dynamic simulation of human eye movements has significant implications for improving our understanding of the oculomotor system and treating various visuomotor disorders. We introduce an open-source biomechanical model of the human eye that can be used for kinematics and dynamics analysis. This model is based on the passive pulley hypothesis, constructed based on the data reported in literature regarding physiological measurements of the human eye and made publicly available. The model is implemented in OpenSim, which is an open-source framework for modeling and simulation of musculoskeletal systems. The model incorporates an eye globe, orbital suspension tissues and six extraocular muscles. The excitation and activation patterns for a variety of targets can be calculated using the proposed closed-loop fixation controller that drives the model to perform saccadic movements in a forward dynamics manner. The controller minimizes the error between the desired saccadic trajectory and the predicted movement. Consequently, this model enables the investigation muscle activation patterns during static fixation and analyze the dynamics of eye movements.
Physics-based modeling and dynamic simulation of human eye movements has significant implications for improving our understanding of the oculomotor system and treating various visuomotor disorders. We introduce an open-source biomechanical model of the human eye that can be used for kinematics and dynamics analysis. This model is based on the passive pulley hypothesis, constructed based on the data reported in literature regarding physiological measurements of the human eye and made publicly available. The model is implemented in OpenSim, which is an open-source framework for modeling and simulation of musculoskeletal systems. The model incorporates an eye globe, orbital suspension tissues and six extraocular muscles. The excitation and activation patterns for a variety of targets can be calculated using the proposed closed-loop fixation controller that drives the model to perform saccadic movements in a forward dynamics manner. The controller minimizes the error between the desired saccadic trajectory and the predicted movement. Consequently, this model enables the investigation muscle activation patterns during static fixation and analyze the dynamics of eye movements.