Biomechanical Simulation of Human Eye Movement

Wei, Qi; Sueda, Shinjiro; Pai, Dinesh K.

doi:10.1007/978-3-642-11615-5_12

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…Our simulator is sufficiently general to support other implementations of pulleys, for instance using elastic suspensions to incorporate transverse shifts (see simulation of coordinated pulleys in [Wei, 2010]).…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Physically-based modeling and simulation of extraocular muscles

Wei

Sueda

Pai

2010

Progress in Biophysics and Molecular Biology

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Dynamic simulation of human eye movements, with realistic physical models of extraocular muscles (EOMs), may greatly advance our understanding of the complexities of the oculomotor system and aid in treatment of visuomotor disorders. In this paper we describe the first three dimensional (3D) biomechanical model which can simulate the dynamics of ocular motility at interactive rates. We represent EOMs using "strands", which are physical primitives that can model an EOM's complex nonlinear anatomical and physiological properties. Contact between the EOMs, the globe, and orbital structures can be explicitly modeled.Several studies were performed to assess the validity and utility of the model. EOM deformation during smooth pursuit was simulated and compared with published experimental data; the model reproduces qualitative features of the observed non-uniformity. The model is able to reproduce realistic saccadic trajectories when the lateral rectus muscle was driven by published measurements of abducens neuron discharge. Finally, acute superior oblique palsy, a pathological condition, was simulated to further evaluate the system behavior; the predicted deviation patterns agree qualitatively with experimental observations. This example also demonstrates potential clinical applications of such a model.

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Section: Methodsmentioning

confidence: 99%

“…In a previous report [Wei et al, 2010], we have presented the structures of our biomechanical model of the orbital plant. In this paper, we focus on describing the detailed methodology and results of the extraocular muscles – the most important components of the whole orbital plant.…”

Section: Introductionmentioning

confidence: 99%

Physically-based modeling and simulation of extraocular muscles

Wei

Sueda

Pai

2010

Progress in Biophysics and Molecular Biology

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“…However, we employed a simple Hill-type muscle model and the pulleys (trochleae) were largely neglected. In future work, we plan to introduce a pulley model and potentially a more sophisticated muscle model, perhaps similar to the strand muscle model proposed by [Wei et al 2010].…”

Section: Discussionmentioning

confidence: 99%

“…For example, Buchberger [2004] implemented an anatomically accurate model of the eye, including a muscle-force prediction model and a quasi-static model that utilized optimization to balance the muscle forces. Wei et al [2010] developed the first fully dynamic biomechanical model of human eye movement for clinical applications, which accounted for the nonlinear kinematics of the oculomotor plant's geometry and extraocular muscle mechanics using strands.…”

Section: Related Workmentioning

confidence: 99%

Biomimetic eye modeling & deep neuromuscular oculomotor control

et al. 2019

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We present a novel, biomimetic model of the eye for realistic virtual human animation. We also introduce a deep learning approach to oculomotor control that is compatible with our biomechanical eye model. Our eye model consists of the following functional components: (i) submodels of the 6 extraocular muscles that actuate realistic eye movements, (ii) an iris submodel, actuated by pupillary muscles, that accommodates to incoming light intensity, (iii) a corneal submodel and a deformable, ciliary-muscle-actuated lens submodel, which refract incoming light rays for focal accommodation, and (iv) a retina with a multitude of photoreceptors arranged in a biomimetic, foveated distribution. The light intensity captured by the photoreceptors is computed using ray tracing from the photoreceptor positions through the finite aperture pupil into the 3D virtual environment, and the visual information from the retina is output via an optic nerve vector. Our oculomotor control system includes a foveation controller implemented as a locally-connected, irregular Deep Neural Network (DNN), or "LiNet", that conforms to the nonuniform retinal photoreceptor distribution, and a neuromuscular motor controller implemented as a fully-connected DNN, plus auxiliary Shallow Neural Networks (SNNs) that control the accommodation of the pupil and lens. The DNNs are trained offline through deep learning from data synthesized by the eye model itself. Once trained, the oculomotor control system operates robustly and efficiently online. It innervates the intraocular muscles to perform illumination and focal accommodation and the extraocular muscles to produce natural eye movements in order to foveate and pursue moving visual targets. We additionally demonstrate the operation of our eye model (binocularly) within our recently introduced sensorimotor control framework involving an anatomically-accurate biomechanical human musculoskeletal model.

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“…[Baran and Popović 2007] presented a method for automatic rigging of character skins without internal anatomy, except for automatically inferred animation skeleton. Musculoskeletal models have been proposed to animate muscle deformations [Wilhelms and Van Gelder 1997;Scheepers et al 1997;Aubel and Thalmann 2001], to perform facial animation [Waters 1987;Sifakis et al 2005], to study or improve the control [Lee and Terzopoulos 2006;Wei et al 2010;Wang et al 2012], or to increase the quality of the flesh and skin deformations [Lee et al 2009]. Beyond bones and muscles, [Sueda et al 2008] demonstrated an impressive model including detailed bones, joints, skin, and tendons.…”

Section: Related Workmentioning

confidence: 99%

Anatomy transfer

et al. 2013

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Figure 1: A reference anatomy (left) is automatically transferred to arbitrary humanoid characters. This is achieved by combining interpolated skin correspondences with anatomical rules. AbstractCharacters with precise internal anatomy are important in film and visual effects, as well as in medical applications. We propose the first semi-automatic method for creating anatomical structures, such as bones, muscles, viscera and fat tissues. This is done by transferring a reference anatomical model from an input template to an arbitrary target character, only defined by its boundary representation (skin). The fat distribution of the target character needs to be specified. We can either infer this information from MRI data, or allow the users to express their creative intent through a new editing tool. The rest of our method runs automatically: it first transfers the bones to the target character, while maintaining their structure as much as possible. The bone layer, along with the target skin eroded using the fat thickness information, are then used to define a volume where we map the internal anatomy of the source model using harmonic (Laplacian) deformation. This way, we are able to quickly generate anatomical models for a large range of target characters, while maintaining anatomical constraints.

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Biomechanical Simulation of Human Eye Movement

Cited by 10 publications

References 19 publications

Physically-based modeling and simulation of extraocular muscles

Physically-based modeling and simulation of extraocular muscles

Biomimetic eye modeling & deep neuromuscular oculomotor control

Anatomy transfer

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