model based head & neck injury criteria · introduction • critical issue with current head...
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Model basedHead & Neck injury criteria
Deck C, Meyer F, Bourdet N, Willinger R.Strasbourg University
Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (Icube)
Equipe Matériaux multi-échelles et Biomécanique (MMB)
Rémy [email protected]
Menschmodelle- DynamoreStuttgart June 2016
INTRODUCTION
• Critical issue with current head injury criteria
• State of the Art head FE modelling and validation
• Focus on head trauma database and accident reconstruction
• Tissue level head injury criteria and risk assessment tool
• Neck FE modelling and validation
• Whiplash injury criteria based on modelling
2
HUMAN SEGMENTS
Gz
Gx
Gy
PROTECTIVE SYSTEMS
HEAD TOLERANCE LIMITS AND HEAD INJURY CRITERIA
Part I : tests on cadavers, skull failure considered as head injury.
Part II : intracranial pressure recorded on anatomical subjects and animals, head injury : commotion.
Part III : tests on human volunteers, no head impact, head kinematics recorded during sled tests.
Head tolerance curve proposed by Wayne State University given linear head accelerations versus time : WSUTC (1966). Head injuries occur in the part upper the curve.
HEAD INJURY CRITERION (1972) : HIC DEFINITION
0
10
20
30
40
50
60
70
80
90
100
0 500 1000 1500 2000 2500
HIC
AIS
3 inju
ry r
isk
(%)
Head mass = 4.58 kg; HIC = 1000
5.2
12
12),(
2
1
21
)(1
)(max
t
ttt
dttatt
ttHIC
CONTEXT OF HEAD PROTECTION STANDARDS
• Inside a car (1970)
- Dummy head; HIC 1000
• Outside – pedestrian (2005)
- Headform; V=11 m/s ;e = 7 cm ; HIC 1000 à 1700
• Motorcyclist (2002)
- Headform; V = 7.5 m/s ;
e = 5 cm ; HIC 2400 ; G= 275G
• Cyclist
- Headform; V = 5.42 m/s ;
e = 2.5 cm ; G= 250G
… for a same human head !
LIMITATIONS OF EXISTING STANDARDS
• Poor correlation with real world observation
• HIC was defined for a frontal impact…and is not direction
dependent
• Not injury mechanism related
• No consideration of rotational acceleration
• No criteria for children (6 YOC, 3 YOC…)
9
It is well known that brain is sensitive to rotational accelerationsince Holbourn (1943)
This phenomenon has essentially been addressed qualitatively with animal or physical models.
Ommaya et al. (1967, 1968), Unterharnscheidt (1971), Ono et al. (1980), Gennarelli et al. (1982), Newman et al. (1999,2000)…..
By using Finite Element Head Models it was expressed quantitatively how dramatic the influence of the rotational acceleration is on intra-
cerebral loading.Deck et al. (2007), Kleiven et al. (2007), Zhang et al. (2001)...
CRITICAL ASPECT OF ROTATIONAL LOADING
9
A number of experimental in vivo investigations emphasized that
axonal strain was the most realistic mechanism of DAI (Bain and Meaney, 2000, Meythaler et al., 2001, Morrison et al., 2003)
GLOBAL PARAMETERS (ROTATION)
Authors Global parameters
Gennarelli, Thibault, Ommaya
(1972)25 Monkeys alive
1800 rad/s² à 7500 rad/s²
60 rad/s à 70 rad/s
Pincemaille et al.
(1989)Boxers training
13600 rad/s² à 16000 rad/s²
28 rad/s à 48 rad/s
Gennarelli et al.
(1982)More than 100 primates alive
15000 rad/s²
150 rad/s
Margulies et al.
(1989)
Based on Gennarelli et al.
(1982)
16000 rad/s²
46.5 rad/s
No agreement
Global parameters-Combined
HIP:
G(t) =a(t)
ac
æ
èç
ö
ø÷
m
+a(t)
ac
æ
èç
ö
ø÷
né
ë
êê
ù
û
úú
1
s
GAMBIT:
n = m = s = 2.5, ac=250g, c = 25.000 rad/s²
PRHIC:
HIP = max ax dt +ò may ay dt +ò maz az dt +ò
I xxax ax dt +ò I yyay ay dt +ò I zzaz az dtò
Newman et al 1986
Newman et al 2000
Kimpara et al. (2011)
Global parameters - Rotation
RIC:
BrIC:
Takhounts et al. 2013
Takhounts et al. 2011
Kimpara et al. (2011)
BRAIN INJURY CRITERIA
• There is no relevant combined, time and direction
dependent brain injury criteria in terms of global head
acceleration
• A number of tentatives exist
• There is a need to set properly :
• A tissue level brain injury criteria
• A measure of the quality of an injury criteria
STATE OF THE ART
FE HEAD MODELS AND
VALIDATION
14
HEAD FE MODELS AROUND THE WORLD
SUFEHMKang et al. 1997
SIMonTakhounst et al. 2003Takhounst et al. 2008
EindhovenClaessens et al. 1997
Brands 2002
StockholmKleiven et al. 2002Kleiven et al. 2007
TurinBelingardi et al. 2005
DublinHorgan et al. 2003Gilchrist et al. 2004
THUMSIwamoto et al. 2001
WSUBIMZhou et al. 1995
Zhang et al. 2001King et al. 2003
Nahum & Trosseille
(1977) (1992)Impact area : front
Impactor : Cylinder with padding
Impact velocity : 6.3 m/s
Duration : 6.2 ms
Yoganandan
(1994)Impact area : vertex
Impactor : Rigid sphere
Impact velocity : 7.3 m/s
Duration : 2 ms
Sarron
(1999)
Back face effect Under Balistic conditions
Hardy
(2001)Impact area : occipital
Impactor : Cylinder
Impact velocity : 2 m/s
Duration : 20 ms
Skull
validation
Intra-cranial
behaviour
validation
VALIDATION DATA
16
Input :
•A 5.6 kg cylindrical impactor (with padding).•An initial velocity about 6.3 m/s•Boundary conditions : Head free
Interaction force between the head and the impactor
BENCHMARK PROCEDURE : NAHUM INPUT
[Nahum et al., 1977]
0 2 4 6 8 10 12 14 16
0
1000
2000
3000
4000
5000
6000
7000
Experimental
Imp
act F
orc
e (
N)
Time (ms)
6 m/s
IMPACTOR
MASS 5.6Kg
E=13.6 Mpa
=0.16
NAHUM IMPACT NUMERICAL RESULTS
0 2 4 6 8 10 12 14
0
500
1000
1500
2000
2500
He
ad
Acce
lera
tio
n [
m/s
²]
Time (ms)
EXPERIMENTAL DATA
ULP
TURIN
THUMS
STOCKHOLM
TUE
0 2 4 6 8 10 12 14-1000
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
EXPERIMENTAL DATA
ULP
TURIN
THUMS
STOCKHOLM
TUE
Inte
r-a
ctio
n F
orc
e [
N]
Time (ms)
•Impact force, head acceleration
Some oscillations can appear in head acceleration results
NAHUM IMPACT NUMERICAL RESULTS
STATISTICAL ANALYSIS WITH ADVISER
STATISTICAL ANALYSIS : RESULTS
STATE OF THE ART NUMERICAL HEAD MODEL
Brain acceleration and pressure- THUMS, SUFEHM and KTH models provided a comparable level of accuracyfor brain acceleration
- Pressure prediction was at similar level of accuracy for all models
Brain displacement- THUMS, SUFEHM and KTH presented best accuracy
- NHTSA and TUE were less accurate
Skull deflection- Only THUMS and SUFEHM models predicted an accurate skull deflection aswell as skull rupture
22
Skull Model Improvement
• Refined meshing
• Skull thickness variation
• Inclusion of reinforced beams
• Improvement of non-linear
material characteristics
50th percentile
adult skull
Digitalisation
SUFEHM 98
Accident reconstructions
Tolerance limits
STRASBOURG UNIVERSITY FE HEAD MODEL
[Kang, 1997]
[Deck, 2004]
SUFEHM PRESENTATION
Membranes(Elastic E=31.5MPa, =0.23)
CSF(Elastic E=12kPa, =0.49)
Face(rigid)
Brain(Viscoelastic G0=49kPa, G=16.7kPa, β=145s-1)
Brainstem(Viscoelastic G0=49kPa, G=16.7kPa,
β=145s-1)
Skull(Shell elements, composite
law with failure criterion)
Scalp(Elastic E=16.7MPa, =0.42)
Identification of Skull mechanical parameters
25
Skull was modelled by a three layered composite shell and damage
mechanism based on Tsai and Wu criterion (Tsai and Wu ,1971).
Brain mechanical properties
26
Rheometry
• 0.004 to 8000Hz
MRE
• Mean values for the whole brain• 20 to 200Hz
Indentation
• 1 to 1000Hz
High discrepancy of values for shear modulus Confirms the stiffest in vitro results (shear modulus ~10KPa at 100Hz)
27
RECENT DEVLOPMENTS
• Marjoux, D., Bourdet, N., and Willinger, R. 2009 . Computation of axonal elongations: towards a new brain injury criterion. International Journal of Vehicle Safety, Vol.4 No 4, 271
• Chatelin S., Deck C., Renard F., Kremer S., Heinrich C., Armspach JP, Willinger R : 2011Computation of axonal elongation in head trauma finite element simulation. J of Mech. Behavior of Biomed Material, V4, 1905-1919.
• Cloots, R.J.H., van Dommelen, J.A., Nyberg, T., Kleiven, S., Geers, M.G., 2011. Micromechanics of diffuse axonal injury: influence of axonal orientation and anisotropy. Biomechanics and Modeling in Mechanobiology. 10, 3, 413-422.
• Wright R, K Ramesh : 2011, An axonal strain injury criterion for traumatic brain injury, Biomechanics and Modeling in Mechanobiology, , 1-16.
• Cloots RJH, van Dommelen JAW, Kleiven S, Geers M, 2013. Multi-scale mechanics of traumatic brain injury: predicting axonal strains from head loads. Biomechanics and Modeling in Mechanobiology, 12(1):137-150.
• Giordano, C, Kleiven, S, 2014. Evaluation of Axonal Strain as a Predictor for Mild TraumaticBrain Injuries Using Finite Element Modeling. Stapp Car Crash Journal, Vol. 58
• Sahoo D., Deck C., Willinger R.:2014 Development and validation of an advanced anisotropic visco-hyperelastic human brain FE model. Journal of the Mechanical Behavior of Biomedical Materials, 2014, vol.33, 24-42
• Sahoo D., Deck C., Willinger R.:2015 Axonal strain as brain injury predictor based on real world head trauma simulation. IRCOBI 2015 and AAP 2016
DTI OF THE BRAIN
28FRACTIONAL ANISOTROPY
DIFFUSION TENSOR IMAGING
ISOTROPIC DIFFUSION
ANISOTROPIC DIFFUSION
12
HEALTHY PERSONS
COUPLING OF DTI DATA
1( ( ))²3 3
2 ( )²
ii
ii
tr DFA
Fibers orientationFractional Anisotropy
| max( )j ijl FA e
[Papadakis et al., 1999; LeBihan et al. , 2001]
Diffusion Parameters
Anisotropy vector
Fractional Anisotropy
1
1
i e
i e
ND L
i
i
NelD L
i
FAe
FA
e
1
1
i e
i e
ND L
i
i
Nel
D L
i
l e
l
e
Rigid transformation between mask of in vivo diffusion data (in red) and brain FEM (in blue)
Voxel selection
Assign Weighting function
NEW ENHANCED BRAIN MODEL
30
l
Longitudinal superior
fascius
Cingulum
Cerebellum
Anisotropic visco-hyperelastic brain model (Chatelin et al. 2012)Matrix stress Fibers stress
, ,e vS C t S C S C t
0
, 2 ( )( )
tv W
S C t G t s dsC s
2 0110
12e C
C
4 1
3
0 0 1
1 1C
C e
DTI
Coupling between anisotropy information and brain FEM meshing
Heterogeneous and anisotropicbrain model
Sagittal view
Axial view Frontal view
MODEL BASED HEAD
INJURY CRITERIA
REAL WORLD HEAD TRAUMA
SIMULATION
31
PUBLISHED
TISSUE LEVEL
INJURY CRITERIA
32
Local Parameters (FE)
Local tissue level brain injury criteria are based on SIMon, KTH, WSU,
THUMS and SUFEHM finite element head models:
• MPS Max principal strain
• SCC Strain in Corpus Callosum
• VM strain Max VM strain
• SSR Strain*Strain rate
• Pmax Max pressure
• VM stress Max VM stress
• CSDM Cumulative Strain Damage Measure
• MAS Maximum axonal strain
INJURY CRITERIA FROM THE LITERATURE
ACCIDENTS RECONSTRUCTIONS
35
• METHODOLOGY
Database (125 cases)
36
HEAD TRAUMA DATABASE
Experimental Skull fracture tests
38
86 drop tests
were conducted
from 17 PMHS
specimens
17 PMHS’ heads are tested.
Accelerometer packages are attached to the skull using screws.
Drop techniques for impact with successively increasing input energies until fracture.
Identification of skull constitutive law
39
Parameters Cortical bone Diploe Bone
Mass density (Kg/m3) 1900 1500
Young’s Modulus (Mpa) 15000 4665
Poisson’s ratio 0.21 0.05
Longitudinal and transverse compressive strength (Mpa) 132 24.8
Longitudinal and transverse Tensile strength (Mpa) 90 34.8
0 2 4 6 8 100
2000
4000
6000
8000
10000 Force UC
Force mean
Force LC
Simulation
V=6.47m/sF
orc
e (
N)
Time (ms)
15 impact
conditions
[Gent et al., 1958][Gray et al., 1991][Pampush et al., 2011]
Parameters 40D Flat 90D Flat 90D Cylindrical
Mass density (Kg/m3) 4230 4930 4930Young’s Modulus (MPa) 9 12 12
Poisson’s ratio 0.43 0.43 0.43
Xc
Xt
Sc
Yc
Yt
DETAILED ACCIDENT
RECONSTRUCTION
MODELING OF THE ACCIDENTS
Unistra modeling
0 20 40 60 80 100 120 140 1600
5
10
15
20
25
30
Fo
rce
[kN
]
Deflection [mm]
(a)
0 20 40 60 80 1000.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
(b)
Fo
rce
[kN
]
Deflection [mm]
0 20 40 60 80 1000
2
4
6
8
10
(d)
Fo
rce
[kN
]
Deflection [mm]
The scalable TNO Pedestrian
model implemented in
Madymo® package
The contact force functions used on
each part of the car are extracted from
the study of Martinez et al.,2007
The Unistra bicycle model
EXAMPLE : DESCRIPTION OF ACCIDENT CASE
Impact Conditions
Car velocity 45 km/h
Cycle Velocity 5.5 km/h
Cycle/Car angle 6°
Vehicle deceleration 6,5 m/s²
Victim
Man, 91 years old,
Failure parieto-occipito-temporal
Coma with a Glasgow score of 5
Unistra modeling
EXAMPLE : KINEMATICS RECONSTRUCTION
Vresultant = 10.9 m/s
Vnormal = 10.0 m/s
Vtangential = 4.4 m/s
Two impacts
• on windshield with the left shoulder,
• on pillar with head area occipito-parieto-temporal.
Projection distance of 16.3 m
WAD of 2.10 m
Unistra modeling
Ped. moving direction
Impact point
Rest points
From IVAC database
- Victim information: 49-year-old female, 158cm and 58kg
- Vehicle information: BMW 318
- Impact speed: about 62.9 km/h
Injury details:- Cerebral contusion (AIS3), Hematoma (AIS2), Fatal
head injuries (AIS6)
- Right tibia (AIS3) and fibula (AIS3) fracture
Exemple pedestrian case (2)
ACCIDENT DATA COLLECTION AND RECONSTRUCTION
Reconstruction results
Example 1 Example 2
Example 1 Example 2
Accident Simulation Accident Simulation
Throw distance (m) 12.4 11.3 18 17.5
WAD (mm) 2000 2030 1980 1940
Velocity (km/h) 60 54 60 62.9
ACCIDENT DATA COLLECTION AND RECONSTRUCTION
Windscreen FEM
46
Perpendicular to the windshield at 40 km/h [Lex van Rooij et al, 2001]
Material Parameters
Glass E=74GPa; ρ=2500kg/m3; μ=0.227; EFG=0.001
PVB E=2.6GPa; ρ=1100kg/m3; μ=0.435
Windscreen Mechanical properties
Adult headform
Masse : 4.8 kg
Constraint
A
B
A
B
Case 2
ACCIDENT CASE
MODEL BASED HEAD
INJURY CRITERIA
48
HEAD TRAUMA SIMULATIONS
EXTRACTION OF CRITERIA
Binary logistic regression (SPSS v14.0)
we compared
the Nagelkerke R-sq statistics
)(1
1bxae
0
10
20
30
40
50
60
70
80
90
100
0 500 1000 1500Pro
bab
ility
of
sku
ll fr
actu
re (
%)
Skull internal energy (mJ)
Skull fracture criteria
51
0200400600800
1000120014001600
SG1
0050
6
SG1
0045
6
P38
SG1
0047
5
VIR
GIN
IA33
SG1
0045
7
P36
SG1
0046
3
VIR
GIN
IA27
GID
AS1
3
GID
AS1
4
GID
AS7
IVA
C7
GID
AS2
IVA
C3
P37
IVA
C4
case
A1
VIR
GIN
IA30
P34
GID
AS8
GID
AS3
GID
AS1
1
case
A3
GID
AS1
6
IVA
C1
0
GID
AS2
3
GID
AS9
case
B1
GID
AS2
4
case
B2
SG1
1019
7
IVA
C1
2
P31
GID
AS2
8
VIR
GIN
IA 2
3
IVA
C1
5
case
B3
IVA
C1
4
case
B4
GID
AS2
6
case
B5Sk
ull
inte
rnal
en
erg
y (m
J)
448
RobustnessR2=0.633
Brain Injury criteria DAI (AIS 2+)
52
0
0,05
0,1
0,15
0,2
0,25
0,3
0,35
0,4
0,45
GID
AS4
GID
AS1
1
GID
AS1
SG1
0045
6
GID
AS2
6
S00
9
GID
AS1
6
GID
AS2
1
IVA
C3
GID
AS1
5
GID
AS1
0
IVA
C7
GID
AS1
8
GID
AS1
3
VIR
GIN
IA30
S015
GID
AS1
4
S01
7
VIR
GIN
IA 2
3
S01
1
S00
1
FIA
4
M0
10
S014
M0
08
P32
S013
M0
01
P34
P37
P31
M0
11
S01
6
S02
2
S00
2
IVA
C8
Axo
nal
elo
nga
tio
n
0.1465
RobustnessR2=0.876
0
10
20
30
40
50
60
70
80
90
100
0 0,05 0,1 0,15 0,2 0,25 0,3
Pro
bab
ility
of
DA
I (%
)
Axonal strain
Evaluation of existing Head Injury Criteria
53
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1
HIC FORCE SKULLINTERNALENERGY
HIC FirstPrincipal
Strain
Von MisesStrain
FirstPrincipal
Stress
Von MisesStress
AxonalStrain
Nag
elke
rke
R²
valu
e
Skull Fracture
DAI
AXON STRAIN IN THE LITTERATURE
0
5
10
15
20
25
30
Haftek et al.,(1970)(rabbit)
Galbraith etal., (1993)
(squid)
Bain andMeaney(2000)
(guinea pig)
Morrison etal., (2003)
(cell culture)
Singh et al.,(2006) (cell
culture)
Nakadate etal., (2014)
(cell culture)
Present Study
Thre
sho
ld S
trai
n %
15%
Proposed tolerance limit is in accordance with various studied reported in literature.
HEAD INJURY
PREDICTION TOOL FOR
END USERS
HEAD INJURY PREDICTION TOOL
• COUPLED EXPERIMENTAL VS NUMERICAL TEST METHODS
• FULL FE APPROACH
FROM RESEARCH TO END USERS
57
• PRE-POST-PROCESSING USER INTERFACES :
3
4
SUFEHM IRA TOOL
INJURY RISK ASSESSMENT
COMPUTATION OF SUFEHM CRITERIA
VIA WEB SIMULATION
TEST HOUSE
6D acceleration curves
STR
ASB
OU
RG
U
NIV
ERSI
TY
60
STEP 1. IMPLEMENTATION OF LOADING CURVES
61
STEP 4. INJURY RISK ASSESSMENT
HEAD PROTECTIVE SYSTEMS
EVALUATION & OPTIMISATION
HELMET CONSUMER TESTS:
TOWARDS NEW HELMET
STANDARDS
64
TANGENTIAL TEST METHOD (CEN TC158)
64
Three tangential impacts at 6.5 m/s
65
TANGENTIAL TEST METHOD (CEN TC158)
65
66
HELMET CONSUMER TESTS IN FRANCE
66
Journal title:
60 Millions de consomateurs (F)August 2015
12 moto helmets evaluatedbased on SUFEHM criteria
67
HELMET CONSUMER TESTS IN GERMANY
67
Journal title:
Stiftung WarentestAugust 2015
18 bicy. helmets evaluatedbased on SUFEHM criteria
PEDESTRIAN AND PASSAGER
PROTECTION
VIRTUAL TESTING IN AUTOMOTIVE ENVIRONMENT
Safe-EV projectPedestrian Passive Safety
RESULTS OF PEDESTRIAN SIMULATIONS
OVERVIEW OF ASSESSMENTS
• Assessment of head injury risk
(using SUFEHM –IRA tool under VPS)
• Further possible injury risk indicators (based on max. pl. strain analysis)
– ribs
pelvis
• tibia/fibula and femur
2 enclumes
ECE R022 standardDevelopment of helmet FEM and coupling with SUFEHM
Injury riks evaluationwith SUFEHM
BICYCLE HELMET
v=5.42 m/s
Validation Head injury risks3 4
Helmet optimisation againstbiomechanical criteria
5
0 10 20 30 40 50 60 70 80
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
Pro
bab
ilit
y (
DA
I)
Brain Von Mises stress [kPa]
LESS-THAN-LETHAL WEAPONS
74
CAD
Meshing Mechanical properties definition
Validation againstexperimental data :
Experiments on rigid wall
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
0
1
2
3
4
5
6
str
ess [M
Pa
]
strain [-]
Foamdescription
Evaluation of head injury risks1
2 3
45
0 10 20 30 40 50 60 70 80
0,0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
0,8
0,9
1,0
Pro
bab
ilit
y (
DA
I)
Brain Von Mises stress [kPa]
Linear and depressive skull failuresprediction
BACK EFFECT : MILITARY HELMET
VALIDATION
A LEGAL MEDICINE CASE
Head injury risks calculated with SUFEHM
77
CONCLUSION-HEAD
• Advanced brain FE models, Computation of axon strain
• Consolidated head trauma database with 125 cases.
• Very high Nagelkerke R² value (R²=0.876) for brain injury
• Best candidate parameter for brain injury is axon strain
• The model based head injury criteria are:
• Axon strain for brain AIS2+ (ea= 15%)
• Skull strain energy for fracture (0.5 J)
• Head injury prediction tool for end users
77
NECK MODELLING AND
WHIPLASH INJURY CRITERIA
Millimetric scanner sections
Surface reconstruction
Meshing criteria
1 2
4
Stereolithographic format
METHODS
Height : 1m72 Weight : 72 Kg Age : 33 Years (50th)
Criterion Values
Length min 2.25 mm
Length max 3 mm
Aspect ratio [1-2]
Warpage [0-5]
Angle quad(°) [70-110]
Angle Tria [50-80]
Jacobien [0.7-1]
% of tria 6
FE NECK MODEL : GEOMETRY
FEM OF THE HEAD-NECK SYSTEM
Intervertebral Discs
Atlas
Axis
C3
C4
C5
C6
C7
T1
Capsularligament
Ligament commun anterior
Interspinalligament
Flavumligament
Ligament commun posterior
Brain
CSF
Falx
Tentorium Skull
Scalp
Face
Number of elements25 661
NECK FINITE ELEMENT MODEL (UNISTRA)
81
NECK FINITE ELEMENT MODEL (UNISTRA)
82
HEAD-NECK UNISTRA COUPLING
83
Coupling to THUMS Model (LS-Dyna)…..TUC !
Moment at the OccipitalCondyles calculated with theTHUMS/Unistra-Head-Neck FEMsuperposed the corridor defineby Patrick and Chou 1971
Force at the Occipital Condylescalculated with theTHUMS/Unistra-Head-NeckFEM
Lateral Impact (N.B.D.L) Ewing et al. 1977
FOLKSAM DATABASE : 87 REAR IMPACTS ACCIDENTS
No neck injury Initial symptoms Symptoms > 1 month0
10
20
30
40
50
60
Nu
mbe
r of occup
an
t
Driver
Front Seat Passenger
=
122 accident cases :
• 77 no neck injury• 30 initial symtoms• 15 symptoms over than 1 month
No neck injury
Initial symptoms
Symptoms > 1 month
Delta V of pulses versus injury severity.
Average age of 46 year old
METHODOLOGY
(FOLKSAM)Linear and Angular Accelerations (T1 & headrest)
Ω(t)
UdS MEF
Injury risk curves/R² score
0 50 100 150 200
0
10
20
30
40
50
60
Acc
ele
ratio
n [m
/s²]
Time [ms]
0 50 100 150 200
-40
-20
0
20
40
60
80
100
Acce
lera
tio
n [m
/s²]
Time [ms]
Ax
Ay
Az
0 50 100 150 200-150
-100
-50
0
50
100
150
Ang
ula
r acce
lera
tio
n [R
ad/s
²]
Time [ms]
Arx
Ary
Arz
V(t)Ω(t)
V(t)NIC, Nkm, MY, Fx,Fz
0
50
100
150
200
250
300
Head a
cc M
ax
2971
630
004
2968
730
005
2960
129
971
3014
930
236
2992
430
237
3015
729
795
2984
929
966
3016
929
911
2967
730
115
2997
530
196
2949
129
880
2977
330
068
3025
129
908
3027
930
318
3031
630
063
2977
829
976
2978
129
951
3032
129
706
2965
230
232
3017
030
024
2996
529
732
3032
630
360
2961
430
029
3024
430
078
2996
830
075
3026
330
278
3015
329
807
3025
330
334
3013
0
3001
629
945
3000
730
001
3016
030
097
2978
029
974
2966
430
125
2973
729
733
3005
230
111
2969
329
967
3003
230
259
3004
9
2997
229
533
2973
930
082
2987
6
2972
729
577
2952
129
602
3001
3
Symptom 0 Symptom 1 Symptom 2 Symptom 3
0
10
20
30
40
50
60
HIC
3000
429
716
2968
730
005
2997
129
601
3014
930
236
2992
430
237
2996
630
157
2979
529
849
3016
929
911
2967
730
196
2997
529
773
3011
529
491
2988
030
068
3025
129
908
3027
930
318
2977
829
976
3031
630
063
2995
129
781
2970
630
321
2965
230
232
3017
030
024
2973
229
965
3036
030
326
2961
430
029
3007
829
968
3024
430
263
3007
530
278
3015
329
807
3025
330
334
3013
0
3001
629
945
3000
730
001
3016
029
780
2997
430
097
2966
430
125
2973
730
052
2973
330
111
2969
329
967
3003
230
259
3004
9
2997
229
739
2953
330
082
2987
6
2957
729
727
2952
129
602
3001
3
Symptom 0 Symptom 1 Symptom 2 Symptom 3
0
5
10
15
20
25
NIC
2949
130
251
2960
129
614
3026
329
652
2967
729
924
2997
530
004
3000
530
024
3006
330
115
3014
930
157
3027
830
236
3031
830
237
3032
130
279
3031
630
360
2968
729
706
2980
729
716
2973
229
880
2996
629
773
2977
829
781
2979
530
170
2984
929
911
2995
130
029
2996
529
971
3032
629
976
3023
230
244
3007
530
334
3025
330
078
3006
830
130
2990
830
153
3016
930
196
2996
8
2994
530
097
2966
429
693
3000
129
733
2973
729
780
2996
729
974
3001
630
049
3003
230
052
3011
130
125
3016
030
259
3000
7
2953
329
972
2973
929
876
3008
2
2952
129
577
2972
729
602
3001
3
Symptom 0 Symptom 1 Symptom 2 Symptom 3
HIC, HEAD Max Acceleration, NIC
6
RESULTS
R² Stade 1 R² Stade 2 R² Stade 3
NIC 0.017 0.073 0.109
Nkm 0.086 0.324 0.266
Fx upper 0.108 0.363 0.361
Fz upper 0.071 0.076 0.047
My upper 0.127 0.433 0.495
Abs (C1-C7) 0.223 0.545 0.842
6
R² WAD1 R² WAD2 R² WAD3
Abs (C1-C7) 0.223 0.545 0.842
Meyer et al.2012 , ‘Development and Validation of a Coupled Head-neck FEM – Application to Whiplash Injury Criteria Investigation’, International Journal of Crashworthiness, 2012, 1–24
NECK INJURY CRITERIA BASED ON FE NECK MODEL AND REAL
WHIPLASH ACCIDENT RECONSTRUCTION
CONCLUSION-NECK
• Full validated neck model (time & frequency)
• Model based neck injury criteria (F,L,R,V)
• SUFEHM_onNeck coupled to THUMS-v3
• Transferred in automotive industry
• Injury Risk Assessment tool
89
Model basedHead & Neck injury criteria
Deck C, Meyer F, Bourdet N, Willinger R.Strasbourg University
Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (Icube)
Equipe Matériaux multi-échelles et Biomécanique (MMB)
Rémy [email protected]
Menschmodelle- DynamoreStuttgart June 2016
91
HEAD INJURY RISK ON « BONNET POINT »
Real pedestrian test
0 10 20 30 40 50
0
250
500
750
1000
1250
1500
Resultant
Lin
ear
Head A
ccele
ration
[m/s
²]
Time [ms]
0 10 20 30 40 50
-8000
-6000
-4000
-2000
0
2000
4000
6000
Y R
ota
tional
Head A
ccele
ration
[rad/s
²]
Time [ms]
6 head accelerations
0 10 20 30 40 50 60 700
1000
2000
3000
4000
5000
6000
7000
8000
9000
Norm
ale
Forc
e [N
]
Displacement [mm]
Force-displacement curves computed
Pedestrian test simulation
0 10 20 30 40 500
250
500
750
1000
1250
1500Finit Element ModelLumped Model
Resultant Lin
ear
Head A
cce
lera
tion [m
/s²]
Time [ms]
« Bonnet point » validation
« Bonnet point » validated model
Step 1: Validation procedure
Predictif head FE model
Injury risk based on biomechanical criteria
Step 2: FE test procedure