Dassault Systemes Americas Corp.

Polyvalor, Societe En Commandite

Other

Ecole De Technologie Superieure

Socovar, Societe En Commandite

Val-Chum, Limted Partnership

Centre Hospitalier De L'université De Montréal (Chum)

Emovi Inc.

Nicola Hagemeister

Rachid Aissaoui

Pierre-Olivier Lemieux

Jacques De Guise

L'Hocine Yahia

Eric Szmutny

Ismail El Maach

Gérald Parent

Annick Koller

Nicolas Duval

Arnaud Barré

Marwan Sati

Jacques A De Guise

Éric Szmutny

Alexandre Fuentes

Ali Zeighami

Neila Mezghani

Thierry Cresson

Guy Grimard

Pierre Ranger

Julien Clément

Nancy St-Onge

Borislav Anguelov

Benoît Godbout

Quentin Bourret

Julie Charland

Matthieu Cauffiez

Julien Clement

Julien CLÉMENT

A computer-implemented method and system determine an initial or starting position of a manikin for use in simulation. The method automatically analyzes environment data to determine a highest ranking type of data from among the environment data. In response, a guiding vector and a sweep mode are determined based upon the determined highest ranking type of data. The determined guiding vector and sweep mode are used to automatically analyze free space between a manikin and a target object in a simulated real-world environment to determine an initial position for and pre-position of the manikin in a simulation of the real-world environment.

Environment-aware prepositioning of digital models in an environment

Embodiments determine positioning of a mannequin. One such embodiment begins by determining a frame of a grasping element of a mannequin represented by a computer-aided design (CAD) model and determining a frame of an object to be grasped, where is object is also represented by a CAD model. To continue, degrees of freedom of the mannequin are specified and limits on the specified degrees of freedom are set. In turn, using an inverse kinematic solver, positioning of the mannequin grasping the object is determined based upon: (i) the determined frame of the grasping element, (ii) the determined frame of the object, (iii) the specified degrees of freedom, and (iv) the set limits on the specified degrees of freedom.

Systems and methods for determining digital model positioning for grasping

The present disclosure is directed to a method and corresponding system that improves accuracy of a computer simulation of an original posture of a digital human model (DHM) relative to a target object. The method and system may obtain information associated with the original DHM posture. The obtained DHM posture information may include a position of a head of the DHM. The method and system may obtain information associated with the target object. The obtained target object information may include a size of the target object and an orientation of the target object. The method and system method may obtain a distance from the head of the DHM to the target object. In some embodiments, the system and method may generate a measure of vision (i.e., vision measure) of the DHM of the target object that the DHM is visually targeting. The system and method may generate the measure of vision based on one or more parameters which may include any of the obtained DHM posture information, the obtained target object information, and the obtained head-target (HT) distance. Based on the measure of vision, the system and method may generate a constraint of vision (i.e., vision constraint) of the DHM to the target object. Based on the vision constraint, the system and method may generate an updated DHM posture.

Method and system for vision measure for digital human models

An upper limb model of a virtual manikin includes a data conversion engine configured to produce converted data based on one or more data sets. Each data set represents dependencies between elements of the kinematic model. The upper limb model further includes a kinematic chain model configured to generate one or more constraints based on the converted data. The upper limb model also includes a posturing engine configured to determine, based on the one or more constraints, a trajectory from a first position to a second position. The kinematic model may further include a rendering engine configured to render a posture corresponding to the second posture. The elements of the kinematic model may include one or more of a clavicle, a scapula, a humerus, a forearm and a hand.

Method and system of constraint-based optimization of digital human upper limb models

The present document describes a method for producing a knee joint treatment plan and/or surgery plan for a patient, the method comprising: obtaining 3D kinematic data of the knee joint in movement; determining, from the 3D kinematic data, scores characterizing the joint function of the patient, the one or more scores being relative to one or more criteria; and comparing the scores to data in a database which characterize a plurality of treatment plans and/or surgery plans to generate the list of one or more treatment plans and/or surgery plans which match the scores.

Method and system for human joint treatment plan and personalized surgery planning using 3-D kinematics, fusion imaging and simulation

A method for creating a frame of reference of a leg of a subject for subsequent 3-D kinematic analysis of the leg with non-invasive trackable references secured to the femur and the tibia of the leg. The method comprises the steps of: i) obtaining tibial and femoral axes with respect to the trackable references by tracking points and motions of the leg; ii) registering a known posture of the subject with respect to the trackable references; iii) obtaining a desired posture of the subject with respect to the trackable references as a function of the known posture by tracking a predetermined motion of the leg; and iv) setting a frame of reference to said tibial and femoral axes of the leg in the desired posture of the subject with respect to the trackable references.

Method of calibration for the representation of knee kinematics and harness for use therewith

A harness for attachment about a knee femur and comprised of a rigid and non-flexible frame support two resiliently mounted clamping means and sensors is described for the non-invasive measurement of knee motion and its analysis in 3-D is described. The clamping means elements are urged under pressure outwardly for application against a skin outer surface at predetermined medial and lateral sites relative to a femur. A non-resilient adjustable stabilizing element is connected to the rigid frame and disposed at a predetermined location with respect to the medial clamping element in spaced relationship therewith and adjustable for clamping contact on a skin outer surface and in alignment with the center of a medial condyle of the femur whereby to stabilize the rigid frame about a knee. An attachment rod is secured to the harness and has straps for securing the rod above the knee.

System for the analysis of 3D kinematic of the knee

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Montreal, Canada

Nicola Hagemeister