musculoskeletal simulation from motion capture … · m. usculoskeletal simulation tutorial –...
TRANSCRIPT
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TUTORIAL
MUSCULOSKELETAL SIMULATION :
FROM MOTION CAPTURE TO MUSCULAR ACTIVITYIN LOWER LIMB MODELS
Nicolas Pronost and Anders Sandholm
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What is it ?
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What is it ? Musculo
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Musculoskeletal simulation ?
What is it ? Musculo
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Human anatomy Musculoskeletal representation
Sylv
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Musculoskeletal simulation ?
What is it ? Musculo
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Human anatomy Musculoskeletalrepresentation
Action lines
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Musculoskeletal simulation ?
What is it ? Musculo Skeletal
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Musculoskeletal simulation ?
What is it ? Musculo Skeletal
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Musculoskeletal simulation ?
What is it ? Musculo Skeletal
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l_mid_foot
r_hand
pelvis
l_hip
l_knee
l_ankle
l_subtalar
l_toe
r_hip
r_knee
r_ankle
r_subtalar
r_mid_foot
r_toe
vl2
vl3
vt4
vt5
vt6
head_top
r_clav
l_hand
Segments connected by
joints and hierarchically
organized
Rigid bodies with mass,
inertia matrix and CoM
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What is it ? Musculo Skeletal Simulation
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Musculoskeletal simulation ?
What is it ? Musculo Skeletal Simulation means analysis
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Musculoskeletal simulation ?
What for ? Analyze athletic performance
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3DAH
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What for ? Analyze athletic performance Design ergonomically safe environments
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What for ? Analyze athletic performance Design ergonomically safe environments Understand and/or treat movement disorders
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3DAH
Mar
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Pro
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Musculoskeletal simulation ?
What you do with ? Visualize complex movement patterns Test “what if” scenario Estimate data difficult to measure Identify cause-effect relationships
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Outlines of the tutorial
Objective : To perform a musculoskeletal simulation from A to … V Acquisition of the data Definition of the model Inverse Kinematics solving Muscular activation estimation Validation of the simulation
Extra features How to create a model ? Interactions with medical imaging Towards more visualizations Simulating tendon transfer surgery
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Context
Tools OpenSim
Open-source musculoskeletal simulation platform Based on SimTK (biological dynamics) Performs SCALE, IK, ID, RRA, CMC and FD Provided with validated musculoskeletal models GUI and command line based
Subject specific data Motion capture (crouch) with ground reaction forces EMG signals
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STEP 1 : ACQUISITION OF THE DATA
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Acquisition of the data ( 1 / 3 )
Motion capture 3D position of anatomical landmarks over time Skin markers vs. clusters vs. bone pins
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Acquisition of the data ( 1 / 3 )
Motion capture 3D position of anatomical landmarks over time Skin markers vs. clusters vs. bone pins
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3DAH
Mar
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urie
Pro
ject
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Acquisition of the data ( 2 / 3 )
Ground reaction forces 6D (force + moment) kinetics reaction of the body To solve the inverse dynamics analysis (through the
Newton’s laws of motion)
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AMTI
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Acquisition of the data ( 3 / 3 )
Electromyography (EMG) signals As muscles contract, volt level electrical signals are
created within the muscle that may be measured from the surface of the body
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STEP 2 : DEFINING A MODEL
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Loading a model
Start OpenSim Menu FILE >> Open Model… Select /TutorialData/GenericModel.osim Manipulate Menu bar, 3D view, Coordinates and
Navigator panels
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Scaling the model – Step 1
Scale factors are applied from ratios between markers distances in model and in mocap
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Original model Standing pose Scaled model
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Scaling the model – Step 2
The virtual markers are moved to match the positions of the experimental markers
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Standing poseScaled model Subject model
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Scaling the model
Menu Tools >> Scale Model… Settings >> Load Settings… Select /TutorialData/Setup_SCALE.xml Run then Close
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STEP 3 : INVERSE KINEMATICS
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Inverse Kinematics
Goal : to find the joint angles of the model that best reproduce the experimental kinematics of the subject’s motion Weighted least squares optimization solver with the goal
of minimizing marker errors
q = joint angles , xiexp = experimental position of marker ixi(q) = virtual position of marker i
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Inverse Kinematics
Menu Tools >> Inverse Kinematics… Settings >> Load Settings… Select /TutorialData/Setup_IK.xml Run then Close
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STEP 4 : MUSCULAR ACTIVATION ESTIMATION
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Muscular activation estimation
Residual Reduction Algorithm (RRA) Dynamics inconsistency due to errors in kinematics and
kinetics measurements and in rigid body modeling Additional “residual” forces and moments are added
F + Fresidual = m . a Modification of the kinematics and the CoM to reduce
Fresidual without significantly altering the simulation
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Effect of reducing residuals
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Muscular activation estimation
Computed Muscle Control (CMC) To compute a set of muscle excitations tracking the
desired kinematics PD control law defines the desired accelerations Static optimization distributes the loads across actuators Forward dynamics conducts the simulation advancing in time Repeated until time is advanced to dt
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Muscular activation estimation
Menu Tools >> Computed Muscle Control… Settings >> Load Settings… Select /TutorialData/Setup_RRA.xml Run then Close
Menu Tools >> Computed Muscle Control… Settings >> Load Settings… Select /TutorialData/Setup_CMC.xml Run then Close
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STEP 5 : VALIDATION OF THE SIMULATION
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Validation of the simulation
Comparison against experimental data : EMG
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right vastus medialiscrouch motion
right soleuscrouch motion
muscle activationfrom simulation raw EMG
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Post processing of EMG
Electrical potential generated by muscle cells Measured in volt, about 90mV Signal need to be post–processed Noise Cross reading from other muscles Rectified
Filtering Box filtering
Can cancel out “real” signal Kalman filter/smoother
More computational intense
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Post processing of EMG
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Simulation vs. EMG
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HOW TO CREATE A MODEL ?
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How to create a model ?
We need Palpable bony landmarks
3D position (from mocap), definition of a coordinate system
Body parts Moment of inertia, mass, position of center of mass
The joints DoF, axis and center of rotation
Muscle and ligament attachment sites Origin and insertion (and via points) positions, fiber and tendon
lengths, mass, pennation angle…
Bony constraints Warping points and bony contours
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Example
Klein Horsman dataset University of Twente, The Netherland [Klein Horsman, Koopman, Van der Helm, Poliacu
Prosé, Veeger. Morphological muscle and joint parameters for musculoskeletal modelling of the lower limb, Clinical Biomechanics (22), pp 239-247, 2007]
Measurements performed on a right lower extremity of a male cadaver (age 77, height 1.74m, weight 105kg)
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Datasets
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Datasets
21 markers 4 body parts pelvis, femur, tibia, foot
58 muscles from 163 action lines 5 joints hip, knee, femur-patella, ankle
subtalar 2 wrapping constraints Gastrocnemius around femur condyle Iliopsoas around the pelvis
104 via points
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Validation of the model
For musculoskeletal simulation use Technical part of formatting the data Compare simulation results with
same motion and previous models experimental data (EMG)
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INTERACTION WITH MEDICAL IMAGING
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Interaction with medical imaging
Benefit from the intensive use of medical images to create and validate models
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DT-MRI + fiber tracking
High resolution of joints
Cross sectional long-leg
Dynamic MRI
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Interaction with medical imaging
Benefit from the intensive use of medical images to create and validate models and simulations
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DT-MRI + fiber tracking
High resolution of joints
Cross sectional long-leg
Dynamic MRI
Fiber directions in model
Attachment points andFE simulations
Attachment points and scaling validation
validation of kinematics
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MUSCULOSKELETAL SIMULATION TUTORIAL – 3DPH WORKSHOP – 2009.11.29
Interaction with medical imaging
MRI viewer in OpenSim Alignment using common markers Comparisons between tendon areas and action lines
extremities
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TOWARDSSCIENTIFIC VISUALIZATIONS
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Towards more visualizations
To help estimating results and tuning settings Scale
Variation in factors, displacements in second inner step
IK Error over time or time-independent
CMC Magnitude of activation, reserve or residual forces
Validation Difference between activation and EMG patterns
To integrate external results Nodal displacements or pressure from FE simulations
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Towards more visualizations
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Thank you for your attention
References
3DAH Marie Curie Project http://3dah.miralab.unige.ch EPFL – VRLAB http://vrlab.epfl.ch Aalborg University – SMI http://www.smi.hst.aau.dk OpenSim https://simtk.org/home/opensim
[email protected] [email protected]
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Diapositive numéro 1Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Musculoskeletal simulation ?Outlines of the tutorialContextDiapositive numéro 17Acquisition of the data ( 1 / 3 )Acquisition of the data ( 1 / 3 )Acquisition of the data ( 2 / 3 )Acquisition of the data ( 3 / 3 )Diapositive numéro 22Diapositive numéro 23Loading a modelScaling the model – Step 1Scaling the model – Step 2Scaling the modelDiapositive numéro 28Inverse KinematicsInverse KinematicsDiapositive numéro 31Muscular activation estimationEffect of reducing residualsMuscular activation estimationMuscular activation estimationDiapositive numéro 36Validation of the simulationPost processing of EMGPost processing of EMGSimulation vs. EMGDiapositive numéro 41How to create a model ?ExampleDatasetsDatasetsValidation of the modelDiapositive numéro 47Interaction with medical imagingInteraction with medical imagingInteraction with medical imagingDiapositive numéro 51Towards more visualizationsTowards more visualizationsThank you for your attention