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In 2009 approximately half of the French population owned a bicycle. However, the cyclist’s accident rate is the highest of all road users. Hence, it is necessary to set up a protection system for cyclists, especially for the cephalic segment. Currently, relatively little literature has dealt with the head impact condition for this kind of accident, especially for cases of cyclist falls. Therefore, the objective of this work was to identify the initial conditions for head impact in cases of cycling fall accidents. The present paper proposes a parametric study by simulating a lot of accident scenarios. A total of 1024 simulations have been automatically carried out using Madymo®’s software and a specially designed program. Two situations of cycling falls have been investigated according to real accident configuration: cyclist falls due to skidding and after hitting a curb. The TNO (Dutch Organization for Applied Scientific Research, Nederlandse Organisatie voor Toegepast Natuurwetenschappelijk Onderzoek) pedestrian 50th percentile human model was coupled to a city bicycle model. The analysed outputs are head impact area and head velocity before impact. The work has provided a solid information base for future work on cyclist accidents. The parametric analysis was also used to study the effects of poorly known environmental parameters, such as speed or torso inclination. The results provided estimates of the impact area and speed of the head, which helps to improve the design of safer helmets and of helmet certification standards tests
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Special Issue Article
Proc IMechE Part P:
J Sports Engineering and Technology
226(3/4) 282–289
ÓIMechE 2012
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DOI: 10.1177/1754337112442326
pip.sagepub.com
Head impact conditions in the case of
cyclist falls
Nicolas Bourdet
1
, Caroline Deck
1
, Rui P Carreira
2
and Re
´my Willinger
1
Abstract
In 2009 approximately half of the French population owned a bicycle. However, the cyclist’s accident rate is the highest
of all road users. Hence, it is necessary to set up a protection system for cyclists, especially for the cephalic segment.
Currently, relatively little literature has dealt with the head impact condition for this kind of accident, especially for cases
of cyclist falls. Therefore, the objective of this work was to identify the initial conditions for head impact in cases of
cycling fall accidents. The present paper proposes a parametric study by simulating a lot of accident scenarios. A total of
1024 simulations have been automatically carried out using Madymo
Ò
s software and a specially designed program. Two
situations of cycling falls have been investigated according to real accident configuration: cyclist falls due to skidding and
after hitting a curb. The TNO (Dutch Organization for Applied Scientific Research, Nederlandse Organisatie voor
Toegepast Natuurwetenschappelijk Onderzoek) pedestrian 50th percentile human model was coupled to a city bicycle
model. The analysed outputs are head impact area and head velocity before impact. The work has provided a solid infor-
mation base for future work on cyclist accidents. The parametric analysis was also used to study the effects of poorly
known environmental parameters, such as speed or torso inclination. The results provided estimates of the impact area
and speed of the head, which helps to improve the design of safer helmets and of helmet certification standards tests.
Keywords
Cycling fall, head impact, multibody simulation, parametric study
Date received: 15 December 2011; accepted: 24 February 2012
Introduction
The cyclist accident rate remains high among all road
users. According to Linn et al.’s study in 1998,
1
the
three segments that are most often hit during cycling
accident are the arms, the legs and the head, with 50%
of the cases. Moreover, Otte
2
showed that 70% of fatal
cyclist accident cases are due to head injuries.
Maimaris et al.
3
and Eilert-Petersson and Schelp
4
reported that most of the cycling accident configura-
tions were single falls. In contrast, Yang and Otte
5
and
Got and Got
6
have shown that most of the cyclist acci-
dents happened against antagonist vehicles. Finally,
Depreitere et al.
7
showed that cycling accidents resulted
from falls and from collisions with vehicles in the same
proportion. According to Ricard and Thelot
8
victims
from cycling falls make up the majority of the injured
population received in emergency (89%).
Currently, there is little information available on the
head impact conditions for this kind of accident, which
mainly concerns windscreen impact. In 2000 and 2003,
Maki et al.
9
and Maki and Kajzer
10
studied the pedes-
trian and cyclist kinematics according to the vehicle
geometry. It appeared that the impact zones, the
impact velocity and angle were different between
cycling accidents and pedestrian accidents. Hence, the
authors concluded that the existing pedestrian tests
were not applicable to cyclists. In 2001, Werner et al.
11
studied the human–bicycle decoupling. He showed that
for off-centre impact, or a bicycle velocity over 5 m/s,
the cyclist was often thrown to the ground without
touching the car. Several authors, such as Serre et al.,
12
have reconstructed many accidents between car and
cyclists in order to identify the cyclist kinematics during
impact. However, cyclist falls that occur on their own
have not been studied because of the wide range of pos-
sible scenarios and the difficulty of categorising them.
Therefore, the objective of the present work is to
1
Strasbourg University, France
2
Oxylane Research Villeneuve d’Ascq, France
Corresponding author:
Nicolas Bourdet, Strasbourg University, 2 rue Boussingault, Strasbourg
F67000, France.
Email: nicolas.bourdet@unistra.fr
evaluate the initial conditions of head impact for cases
of cycling falls by simulating a great number of possible
accident situations.
Materials and methods
The present paper proposes a methodology based on
an automatic parametric study to evaluate the head
impact area and velocity for single cyclist falls. A total
of 1024 simulations have been automatically carried
out using MadymoÒsoftware coupled with a special
designed program allowing to compute and to analyse
the simulated scenarios. The analysed outputs are, suc-
cessively, head initial orientation and velocity just
before head contact. The cyclist’s kinematics were
reconstructed based on multi-body computing with
Madymo software. The principle of solving a multi-
body system is to define a set of rigid bodies repre-
sented by ellipsoids and connected by joints. Unlike
finite elements, contact between two bodies is not com-
puted by deformable surfaces but by a penetration
force defined by a function. The computational time of
this multi-body approach is strongly reduced compared
to finite element simulation. The models are developed
using ellipsoids in such a way that the geometry, mass
and inertia are respected. Hence, the human model
used was the TNO pedestrian model implemented in
the Madymo package and validated against post mor-
tem human tests, as depicted by van Hoof et al.
13
and
De Lange et al.
14
In the present study, the model used
to represent the cyclist had a mass of 75 kg and a height
of 1.75 m. The bicycle was modelled in accordance with
the geometry and mass of a city bicycle, as illustrated
in Figure 1(a). Each part of the frame was modelled by
a rigid body including mass and inertia computed as
steel pipes and connected by ‘bracket’ joints. The frame
and the front fork as well as the frame and the pedal-
board were connected by a revolute joint. Figure 1(b)
illustrates the bicycle model.
Two situations of cycling fall have been studied
according to a hypothetical configuration of real
frequent-accident cases. One configuration consists of a
fall alone after skidding, as depicted in Figure 2(a), and
the second consists of a fall after hitting a curb, as illu-
strated in Figure 2(b). For each configuration a set of
parameters was selected to be changed in the model
such as bicycle linear and angular velocity, torso pos-
ture, hip position, pedals position, handlebars angle
and bicycle incline. For pedalboard, four positions
were selected (0°,90°,180°and 270°) while for handle-
bars only two positions were studied (–30°and 30°)
with the final objective to study some extreme positions
without adding too much to the simulations. The out-
put of the simulations focused on three major results:
head velocity, head orientation and head impact area,
in order to define the conditions of head impact just
before head contact.
Table 1 reports the selected parameters considered
for the parametric study carried out for each configura-
tion with the associated values. The design of the simu-
lation table established for the present parametric study
is a full factorial table with 512 combinations. Hence,
the total number of simulations is 1024.
One of the outputs is the head impact area, so this
point had to be further defined. The head impact point
coordinates are extracted from the simulation and
plotted on the EN960 headform geometry by matching
the height and depth of both head geometries. The
choice of partitioning the cyclist’s head into latitude
and longitude zones was made in order to define easily
and quickly the impact point on the head, extracted
from simulation. Figure 3 illustrates the defined head
regions as follows: around the vertical axis, the head
has been divided into 12 separate regions, with a 30°
interval, leading to six symmetric regions called
Longitude 1 to Longitude 6. In the horizontal plan,
above the reference plan AA#definedintheEN960
standard,
15
the headform has been divided into five
equidistant horizontal sections (Latitude 1 to Latitude
5) and a section located below line AA#with an equiv-
alent width (Latitude 6). The last region, called
Latitude 7, describes the remaining part. The metho-
dology applied for the analysis of the computation
results was conducted in two steps. First, a global
Figure 1. Representation of a real city bicycle (a) and its model under MadymoÒsoftware (b).
Bourdet et al. 283
distribution of the contact area according to the previ-
ous head partition, as well as a mean value of velocity
in terms of resultant, normal and tangential compo-
nents, was evaluated. In a second step, the effect of
each parameter on the impact area and velocity
responses was studied. For this purpose, it was neces-
sary to define a response model associated with the
parametric analysis.
Figure 3. Representation of EN960 headform geometry partition: (a) in latitude and (b) in longitude. The reference line AA#
defined in EN960 is also reported.
Figure 2. Representation of the cyclist model coupled to the bicycle model used for the simulations of fall alone: (a) after
‘skidding’, (b) after ‘hitting a curb’.
Table 1. Display of the selected factors for the parametric study and the associated values.
Factors Bicycle parameters Human parameters
F1 F2 F3 F4 F5 F6 F7 F8
Pedalboard
rotation (°)
Handlebars
rotation (°)
Linear
velocity (m/s)
Angular
velocity (rad/s)
Bicycle
roll (°)
Torso
inclination (°)Hip position (mm)
Vert. Horiz.
Level 1 0 –30 5.5 0 0 21 0 0
Level 2 90 30 11.1 3.14 30 37 200 200
Level 3 180
Level 4 270
284 Proc IMechE Part P: J Sports Engineering and Technology 226(3/4)
The response model was a linear combination of fac-
tors and their interactions, as described in equation (1).
In this study, only the effect values of factors are evalu-
ated, and the effect values of interactions are neglected.
Y=m+X
N
i=1
Fi+X
N1
i=1
Iið1Þ
where mis the total average of the studied response from
all simulations (Nsimulations), F
i2[1,7]
are the effect val-
ues corresponding to the selected factors and I
i2[1,6]
are
the sum of the effect values from interactions between
several factors with order i,asdepictedinequation(2)
I1=P
N1
k=1 P
N
l=k+1
FkFl
...
I6=F1F2F3F4F5F6F76 ð2Þ
The effect value of a factor/interaction at a given level
was calculated as the mean value between the responses
when the factor/interaction had the level uand the aver-
age m.
Results
A total of 1024 simulations of cycling falls were carried
out with Madymo software. Figure 4(a) and (b) shows
the distribution of head impact area for both the ‘skid-
ding’ and ‘after hitting a curb’ fall configurations in
terms of latitude and longitude. It can be observed that
in the ‘skidding’ configuration the latitude areas most
often impacted are Latitude 6 and Latitude 5, with
90% of the total impacts. However, for the fall config-
uration after hitting a curb, the area is more spread out,
including Latitudes 4 to 6, with 65% of total impacts.
Considering longitude distribution, both fall config-
urations present a large range of impact areas. 80% of
these impacts are located from Longitude 2 to
Longitude 5 for falls after skidding, with an average of
20 61%, and from Longitude 1 to Longitude 4 for falls
after hitting a curb, with an average of 17 62%.
Tables 2 and 3 report the factors influence on the
corresponding response. The significance of the calcu-
lated influence value of the factors according to the
ANOVA test is also calculated. Hence, the non-
significant values are shaded in the tables. It is clear
that the resultant and tangential velocities are strongly
influenced by the bicycle speed in both configurations.
However, the normal component is also influenced by
the bicycle roll angle and the vertical position of the
hip. This can be explained by the fact that these factors
define the vertical position of the head and, hence, the
head drop height.
The previous analysis can further be divided into
two categories according to the bicycle speed, as
follows.
For a cyclist moving with a speed of 5.5 m/s (20 km/h)
and falling alone, as simulated in this study, the resultant
head velocity just before ground contact is, respectively,
6.9 61.2 m/s and 6.4 60.9 m/s in the cases of ‘skidding’
and ‘after hitting a curb’ configurations. Considering the
normal components of the velocities, results are
5.7 61.3 m/s and 5.2 61.0 m/s for ‘skidding’ and ‘after
hitting a curb’, respectively. Coming to the tangential
velocity, both fall configurations give about 3.7 m/s, as
reported in Table 4. In terms of impact angle versus the
normal direction a value of about 35°can be established.
Figure 5 represents the head impact area distribution
extracted from both configurations of falls with a bicycle
speed of 5.5 m/s. The latitude distribution is similar for
both configurations, with a majority of impacts located
at Latitude 5 and Latitude 6 (80% and 65% in the cases
of ‘skidding’ and ‘after hitting a curb’, respectively). On
the other hand, and as for the global distribution, the
impacts among the longitude partitions are spread in the
range from Longitude 1 to Longitude 4.
Considering a bicycle speed of 11.1 m/s (40 km/h),
the resultant head velocity just before ground contact is
11.3 61.1 m/s (6.2 61.0 m/s and 9.4 61.0 m/s for nor-
mal and tangential components, respectively) in the
case of falls after ‘skidding’, and 9.1 62.1 m/s
(4.8 61.3 m/s and 7.7 61.9 m/s for normal and tangen-
tial components, respectively) in the case of falls ‘after
hitting a curb’, as reported in Table 5. It can be
Figure 4. Histogram of the head impact area distribution obtained for the complete set of 1024 simulations in terms of: (a)
latitude; and (b) longitude for both falling configurations.
Bourdet et al. 285
observed that in case of this bicycle speed, the tangential
component is higher than the normal one for both fall
configurations. Indeed, the impact angle is shifted from
35°to 57°. Considering the distribution of head impact
area, it was observed that in the case of falls after
‘skidding’, latitude distribution remains identical to the
configuration with a bicycle speed of 5.5 m/s. On the
other hand, in the case of falls ‘after hitting a curb’, the
distribution becomes more spread out, as shown in
Figure 6.
Figure 5. Histogram of the head impact area distribution in terms of: (a) latitude; and (b) longitude for both falling configurations
with a bicycle speed of 5.5 m/s.
Table 2. Influence of factors on simulated responses in case of falls after ‘skidding’. The non significant influences are in bold.
Factors Bicycle parameters Human parameters
F1 F2 F3 F4 F5 F6 F7 F8
Pedalboard
rotation (°)
Handlebars
rotation (°)
Linear
velocity (m/s)
Angular
velocity (rad/s)
Bicycle
roll (°)
Torso
inclination (°)Hip position (mm)
Vert. Horiz.
V
Resultant
0% 0% 88% 5% 6% 0% 0% 0%
V
Normal
2% 7% 9% 6% 62% 5% 10% 1%
V
Tangential
0% 0% 95% 4% 1% 0% 0% 0%
Latitude 2% 3% 1% 26% 51% 6% 1% 9%
Longitude 1% 2% 0% 74% 19% 0% 1% 3%
Table 3. Influence of factors on simulated responses in case of falls after ‘hitting a curb’. The non significant influences are in bold.
Factors Bicycle parameters Human parameters
F1 F2 F3 F4 F5 F6 F7 F8
Pedalboard
rotation (°)
Handlebars
rotation (°)
Linear
velocity (m/s)
Angular
velocity (rad/s)
Bicycle
roll (°)
Torso
inclination (°)Hip position (mm)
Vert. Horiz.
V
Resultant
0% 2% 62% 3% 16% 1% 16% 0%
V
Normal
2% 7% 7% 0% 31% 5% 47% 0%
V
Tangential
0% 0% 85% 3% 5% 0% 5% 0%
Latitude 1% 6% 31% 1% 47% 0% 12% 1%
Longitude 16% 6% 0% 32% 44% 0% 1% 1%
Table 4. Computed head impact velocities and impact angle for a bicycle speed of 5 .5 m/s.
V
Resultant
(m/s) V
Normal
(m/s) V
Tangential
(m/s) Impact angle (°)
Skidding fall 6.9 61.2 5.7 61.3 3.7 60.9 33.5 68.7
Curb hitting 6.4 60.9 5.2 61.0 3.7 60.8 36 67.7
286 Proc IMechE Part P: J Sports Engineering and Technology 226(3/4)
Figure 7 represents the head impact points extracted
from all 1024 simulations and plotted on the EN960
headform geometry. In order to superimpose this result
with the impact area prescribed in the standard, the test
line defined in the EN1078 standard was plotted. It can
be observed that an important proportion of impact
points are located under the helmet test line.
Discussion
Although cycling falls occur often, it is very difficult to
get real statistics about the head injuries caused to the
victim, especially in the case of accidents without any
antagonist. Due to the large number of possible
scenarios, it is unrealistic to consider all accident types.
In the present study, two realistic and classical accident
scenarios have been considered: one caused after ‘skid-
ding’ and the other ‘after hitting a curb’. Moreover, the
same bicycle and the same human model size were used
for both accident configurations. These constitute a
first limit of this work. Indeed, some further bicycles
with different masses and sizes as well as further heights
and weights for the human body model should be con-
sidered in further research. For the parametric study,
four pedalboard positions were selected, while for han-
dlebars only two positions were studied. This choice
was made in order to study some extreme positions
but also in order to keep a reasonable number of
Figure 7. Representation of the head impact points: (a) for falls after skidding; (b) for falls after hitting a curb.
Figure 6. Histogram of the head impact area distribution in terms of: (a) latitude; and (b) longitude for both falling configurations
with a bicycle speed of 11.1 m/s.
Table 5. Computed head impact velocities and impact angle for a bicycle speed of 11.1 m/s.
V
Resultant
(m/s) V
Normal
(m/s) V
Tangential
(m/s) Impact angle (°)
Skidding fall 11.3 61.1 6.2 61.0 9.4 61.0 56.6 65.1
Curb hitting 9.1 62.1 4.8 61.3 7.7 61.9 58 66.5
Bourdet et al. 287
simulations. It should also be mentioned that for the
zero degree handlebars rotation, the time for the bicycle
fall was too long and caused simulation instability
problems. Nevertheless, it should be integrated into
future work. However, the results obtained with a
bicycle model coupled to a human model with the
height and weight of a 50th percentile man, provided
reasonable new knowledge about cycling falls, dis-
cussed further below.
For each fall configuration, seven parameters linked
to the bicycle and human characteristics have been con-
sidered for a parametric study with 512 simulations.
The analysis of impact locations at head level showed
that the impacts are very often (42%) close to the hel-
met rim line (Latitude 6) for both fall configurations;
more precisely, 57% in the case of falls after ‘skidding’,
but more spread out in the case of falls after ‘hitting a
curb’ (28%). These results are consistent with other
studies presented in the literature, such as Ching et al.,
16
who noted that 49.3% of impact locations on 311 hel-
mets are on the helmet rim. More recently, in 2009,
Serre
17
showed that among a collection of 862 helmets,
the majority of impacts occurred at the border line.
For both fall configurations, the impact in longitude
area is fronto-parietal, with more than 50%. Coming
to the discussion concerning the head speed at the time
just before impact, the results showed that for the nor-
mal components, the obtained values are in the velocity
range recommended by testing standards for the certifi-
cation of helmets (5.42 m/s). Moreover, during head
impact against ground surface, a significant tangential
component of the velocity is observed. Indeed, for a
bicycle speed configuration of 5.5 m/s the head resul-
tant velocity presents a 35°incline versus normal axis,
whereas for a bicycle speed configuration of 11.1 m/s
this angle is about 57°. This tangential component
of the head velocity generates a rotational acceleration
of the head and thus increases the brain injury risk,
as demonstrated by Deck et al.
18
and Deck and
Willinger.
19
Therefore, the standard test for bicycle hel-
met should include this tangential component in future
improved test procedures.
Conclusion
The present study focuses on cyclist head impact condi-
tion in the case of an accident without an antagonist,
an aspect poorly reported in the literature. A multi-
body bicycle and cyclist model has been developed and
applied for extensive parametric study (1024 simula-
tions). Two fall conditions have been considered (‘skid-
ding’ and ‘hitting a curb’) at two bicycle initial speeds
(5.5 m/s and 11.1 m/s). Results demonstrate that head
impact points are very often located around and under
the helmet rim, the normal head initial speed is close
to 5.5 m/s and the head velocity presents a significant
tangential component. It is considered that this infor-
mation should be taken into consideration both in test
procedure design and helmet development.
Funding statement
This research received no specific grant from any funding
agency in the public, commercial, or not-for-profit sectors.
Acknowledgments
This work has been developed within the ANR
PREDIT GO4 project BicyTeˆ te (French Department
of Transport).
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... 30,89 Impact location is usually determined by assessing reclaimed cycle helmets which were involved in collisions. 104,118 Impact speed and angle are generally extracted from recon-struction of head-vehicle or head-ground impacts, primarily modelled computationally using multibody simulation software such as MADYMO 13,14,17,30,95,132 or alternatively with physical drop tower testing. 12,104,118,125 Despite all these efforts, helmet testing methods to date often rely on data collected over 30 years ago in spite changes to vehicle fronts, infrastructure, and helmet technology. ...
... We excluded one study from the meta-analysis due to the simulations not being based on real-world collisions. Bourdet et al. 13 used approach A to assess simulated head impact location in 1024 cyclist falls from loss of control or kerb contact simulated in Madymo. 13 They found that 6% of impacts were to the crown and the rear, 21% to the front and 73% were to the side. ...
... Bourdet et al. 13 used approach A to assess simulated head impact location in 1024 cyclist falls from loss of control or kerb contact simulated in Madymo. 13 They found that 6% of impacts were to the crown and the rear, 21% to the front and 73% were to the side. ...
Article
Full-text available
Head injuries are common for cyclists involved in collisions. Such collision scenarios result in a range of injuries, with different head impact speeds, angles, locations, or surfaces. A clear understanding of these collision characteristics is vital to design high fidelity test methods for evaluating the performance of helmets. We review literature detailing real-world cyclist collision scenarios and report on these key characteristics. Our review shows that helmeted cyclists have a considerable reduction in skull fracture and focal brain pathologies compared to non-helmeted cyclists, as well as a reduction in all brain pathologies. The considerable reduction in focal head pathologies is likely to be due to helmet standards mandating thresholds of linear acceleration. The less considerable reduction in diffuse brain injuries is likely to be due to the lack of monitoring head rotation in test methods. We performed a novel meta-analysis of the location of 1809 head impacts from ten studies. Most studies showed that the side and front regions are frequently impacted, with one large, contemporary study highlighting a high proportion of occipital impacts. Helmets frequently had impact locations low down near the rim line. The face is not well protected by most conventional bicycle helmets. Several papers determine head impact speed and angle from in-depth reconstructions and computer simulations. They report head impact speeds from 5 to 16 m/s, with a concentration around 5 to 8 m/s and higher speeds when there was another vehicle involved in the collision. Reported angles range from 10° to 80° to the normal, and are concentrated around 30°–50°. Our review also shows that in nearly 80% of the cases, the head impact is reported to be against a flat surface. This review highlights current gaps in data, and calls for more research and data to better inform improvements in testing methods of standards and rating schemes and raise helmet safety.
... Despite this, the inclusion of angular motion in helmet testing has not yet been implemented in standards. The standards do not include oblique impact tests against angled surfaces, which would mimic a real impact situation better than impacts to a flat surface [10]. The biofidelity of the standard tests can be further disputed, as many of the standards often use uncoated ATD headforms made of metal [3] [11], favouring repeatability, instead of using the available rubber-coated headforms, such as the commonly used National Operating Committee on Standards for Athletic Equipment (NOCSAE) or Hybrid III (HIII) headforms. ...
... Little is known about how these ratings are influenced by the headform used for the underlying impact tests. Several studies have pointed out the differences in biomechanical impact response in oblique impacts between different headforms [10] [14][15]. Also, between the commonly used HIII and NOCSAE headforms there are considerable differences in shape [22], mass and inertial properties [23]. ...
Conference Paper
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Numerous helmet rating methods have been proposed to assess the safety and effectiveness of bicycle helmets. The methods usually involve a series of experimental impact tests using an Anthropomorphic Test Device (ATD) headform. There are several headforms available for the purpose and this study sought to assess how the choice of headform influences the safety assessment and ratings of bicycle helmets by following four proposed rating programs using three commonly used headforms. 19 head impact cases were evaluated computationally using the National Operating Committee on Standards for Athletic Equipment (NOCSAE) headform, Hybrid III (HIII) headform, and standard EN960 headform. The results show that for most oblique impact cases, EN960 produced considerably lower Peak Angular Acceleration (PAA), Peak Angular Velocity (PAV) and head injury risk compared to HIII and NOCSAE. This implies that the safety performance of bicycle helmets could be rated higher when using uncoated metal headforms compared to rubber-coated ones. The different headforms' tendency to produce varying rotational motion in oblique impacts raises questions about which of the headforms are suitable for such impact tests. The results presented in this study emphasize the occasional contradictions in helmet ratings presented by helmet rating programs.
... 7 Similarly, simulation of over 1000 cyclist falls showed that the head impact angle was between 32°and 56.5°. 6 They showed that increasing the travelling speed from 5.5 to 11.1 m/s decreased the impact angle from 57°to 33°. Contrastingly, in our trip cases, increasing the walking speed resulted in an increase in the impact angle (Fig. 6) while in the forward and backward cases, the walking speed did not have a consistent effect on impact angle. ...
... This allowed us to exclude the groups that have very few cases and find a relationship between head impact speed and angle where most cases with higher impact speeds had higher impact angles. This is different to previous studies, which determined the mean or median values of each factor independently. 6,30 The approach adopted here maintained the relationship between different factors and head impact angle with a 30°angle resolution, thus providing more comprehensive conditions for setting up helmet test methods representative of trips and falls in workplace. This study has several limitations. ...
Article
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Traumatic brain injury (TBI) is a common injury in the workplace. Trips and falls are the leading causes of TBI in the workplace. However, industrial safety helmets are not designed for protecting the head under these impact conditions. Instead, they are designed to pass the regulatory standards which test head protection against falling heavy and sharp objects. This is likely to be due to the limited understanding of head impact conditions from trips and falls in workplace. In this study, we used validated human multi-body models to predict the head impact location, speed and angle (measured from the ground) during trips, forward falls and backward falls. We studied the effects of worker size, initial posture, walking speed, width and height of the tripping barrier, bracing and falling height on the head impact conditions. Overall, we performed 1692 simulations. The head impact speed was over two folds larger in falls than trips, with backward falls producing highest impact speeds. However, the trips produced impacts with smaller impact angles to the ground. Increasing the walking speed increased the head impact speed but bracing reduced it. We found that 41% of backward falls and 19% of trips/forward falls produced head impacts located outside the region of helmet coverage. Next, we grouped all the data into three sub-groups based on the head impact angle: [0°, 30°], (30°, 60°] and (60°, 90°] and excluded groups with small number of cases. We found that most trips and forward falls lead to impact angles within the (30°, 60°] and (60°, 90°] groups while all backward falls produced impact angles within (60°, 90°] group. We therefore determined five representative head impact conditions from these groups by selecting the 75th percentile speed, mean value of angle intervals and median impact location (determined by elevation and azimuth angles) of each group. This led to two representative head impact conditions for trips: 2.7 m/s at 45° and 3.9 m/s at 75°, two for forward falls: 3.8 m/s at 45° and 5.5 m/s at 75° and one for backward falls: 9.4 m/s at 75°. These impact conditions can be used to improve industrial helmet standards.
... The latter encompass diffuse axonal injuries and traumatic brain injuries (TBIs), commonly referred to as concussions, which are highly prevalent in sports due to the risks of head impacts [2]. Sports activities such as contact sports (football, rugby, hockey, etc.) and individual sports with high-speed mobility (e.g., cycling or skiing) are prone to head impacts at different energies, orientations, and frequencies [3]. To mitigate the risks associated with head impacts, the governing organizations of these sports and healthcare practitioners mandate protective head equipment. ...
Article
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Head impacts are a major concern in contact sports and sports with high-speed mobility due to the prevalence of head trauma events and their dire consequences. Surrogates of human heads are required in laboratory testing to safely explore the efficacy of impact-mitigating mechanisms. This work proposes using polymer additive manufacturing technologies to obtain a substitute for the human skull to be filled with a silicone-based brain surrogate. This assembly was instrumentalized with an Inertial Measurement Unit. Its performance was compared to a standard Hybrid III head form in validation tests using commercial headgear. The tests involved impact velocities in a range centered around 5 m/s. The results show a reasonable homology between the head substitutes, with a disparity in the impact response within 20% between the proposed surrogate and the standard head form. The head surrogate herein developed can be easily adapted to other morphologies and will significantly decrease the cost of the laboratory testing of head protection equipment, all while ensuring the safety of the testing process.
... Our study extended previous efforts by using realistic loadings recorded from seventeen bicycle helmets in three distinct impact conditions. These impact conditions represented the most common impact scenarios in bicycle accidents (Bourdet et al. 2012). Our results also further confirmed the early finding the strain peak was affected by the helmet type and impact condition. ...
Preprint
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Traumatic brain injury (TBI) in cyclists is a growing public health problem, with helmets being the major protection gear. Finite element head models have been increasingly used to engineer safer helmets often by mitigating brain strain peaks. However, how different helmets alter the spatial distribution of brain strain remains largely unknown. Besides, existing research primarily used maximum principal strain (MPS) as the injury parameter, while white matter fiber tract-related strains, increasingly recognized as effective predictors for TBI, have rarely been used for helmet evaluation. To address these research gaps, we used an anatomically detailed head model with embedded fiber tracts to simulate fifty-one helmeted impacts, encompassing seventeen bicycle helmets under three impact conditions. We assessed the helmet performance based on four tract-related strains characterizing the normal and shear strain oriented along and perpendicular to the fiber tract, as well as the prevalently used MPS. Our results showed that both the helmet type and impact condition affected the strain peaks. Interestingly, we noted that helmets did not alter strain distribution, except for one helmet under one specific impact condition. Moreover, our analyses revealed that helmet ranking outcome based on strain peaks was affected by the choice of injury metrics (Kendall tau coefficient: 0.58 ~ 0.93). Significant correlations were noted between tract-related strains and angular motion-based injury metrics. This study provided new insights into computational brain biomechanics and highlighted the helmet ranking outcome was dependent on the choice of injury metrics. Our results also hinted that the performance of helmets could be augmented by mitigating the strain peak and optimizing the strain distribution with accounting the selective vulnerability of brain subregions.
... Traumatic brain injury is one of the leading causes of disability around the world and contributes to approximately 30% of all injury deaths [7]. Head injuries from bicycle accidents are often caused by blunt impacts, which are typically oblique with respect to the impact surface [8][9][10]. The oblique impact force is made up of a normal force component that induces linear head kinematics, and a tangential force component that induces rotational head kinematics. ...
Article
Head impacts in bicycle accidents are typically oblique to the impact surface and transmit both normal and tangential forces to the head, causing linear and rotational head kinematics, respectively. Traditional expanded polystyrene (EPS) foam bicycle helmets are effective at preventing many head injuries, especially skull fractures and severe traumatic brain injuries (TBIs) (primarily from normal contact forces). However, the incidence of concussion from collisions (primarily from rotational head motion) remains high, indicating need for enhanced protection. An elastomeric honeycomb helmet design is proposed herein as an alternative to EPS foam to improve TBI protection and be potentially reusable for multiple impacts, and tested using a twin-wire drop tower. Small-scale normal and oblique impact tests showed honeycomb had lower oblique strength than EPS foam, beneficial for diffuse TBI protection by permitting greater shear deformation and had the potential to be reusable. Honeycomb helmets were developed based on the geometry of an existing EPS foam helmet, prototypes were three-dimensional-printed with thermoplastic polyurethane and full-scale flat and oblique drop tests were performed. In flat impacts, honeycomb helmets resulted in a 34% higher peak linear acceleration and 7% lower head injury criteria (HIC15) than EPS foam helmets. In oblique tests, honeycomb helmets resulted in a 30% lower HIC15 and 40% lower peak rotational acceleration compared to EPS foam helmets. This new helmet design has the potential to reduce the risk of TBI in a bicycle accident, and as such, reduce its social and economic burden. Also, the honeycomb design showed potential to be effective for repetitive impact events without the need for replacement, offering benefits to consumers.
... However, quantifying the impact angle in real-world collisions is very difficult. Previous work has used multi-body simulations to estimate the head impact characteristics in bicycle falls to the ground [51]. Their results show that at a travelling speed of 5.5 m/s, the head impact angle is 36 • ± 8 • but it increases to 58 • ± 6 • if travelling speed is increased to 11 m/s. ...
Article
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Traumatic brain injury (TBI) is a prevalent injury among cyclists experiencing head collisions. In legal cases, reliable brain injury evaluation can be difficult and controversial as mild injuries cannot be diagnosed with conventional brain imaging methods. In such cases, accident reconstruction may be used to predict the risk of TBI. However, lack of collision details can render accident reconstruction nearly impossible. Here, we introduce a reconstruction method to evaluate the brain injury in a bicycle–vehicle collision using the crash helmet alone. Following a thorough inspection of the cyclist’s helmet, we identified a severe impact, a moderate impact and several scrapes, which helped us to determine the impact conditions. We used our helmet test rig and intact helmets identical to the cyclist’s helmet to replicate the damage seen on the cyclist’s helmet involved in the real-world collision. We performed both linear and oblique impacts, measured the translational and rotational kinematics of the head and predicted the strain and the strain rate across the brain using a computational head model. Our results proved the hypothesis that the cyclist sustained a severe impact followed by a moderate impact on the road surface. The estimated head accelerations and velocity (167 g, 40.7 rad/s and 13.2 krad/s2) and the brain strain and strain rate (0.541 and 415/s) confirmed that the severe impact was large enough to produce mild to moderate TBI. The method introduced in this study can guide future accident reconstructions, allowing for the evaluation of TBI using the crash helmet only.
Article
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The vehicle traffic accidents have been widely studied in different countries, but the difference of nature of traffic accidents in different countries was not adequately investigated for set suitable protective strategy in different area. This study aimed to identify the occurrence, type and mechanisms of the traumatic injuries of the vulnerable road users (VRUs) in vehicle collisions in China and Germany. The accident data (in the years 2000 to 2005) were collected from traffic police and hospital in Changsha, China as well as from GIDAS database documented in Medical University Hannover, respectively. An in-depth study was carried out based on the collected data by using approaches of statistics analysis and virtual reconstructions. The results from analysis of Chinese data were compared with results from analysis of German data. The injury severities were determined using AIS code and ISS values. The results were presented in terms of cause of injuries, injury distributions, injury patterns, injury severity. The VRUs accidents were identified as vital issue in urban traffic safety and therefore a high priority should be given to this road user group in research of safe urban transportation. It was discussed with regard to accident data collection, accident sampling and injury distributions, the factors influenced the injury outcomes etc. The data sources reflects the real situations of vulnerable road users in traffic accidents in Changsha and Hannover and may not in the whole countries of China and Germany. This study will contribute to the determination of different nature of vehicle traffic accidens between motorized and motorizing areas, which will form a firm background for making safety counter-measures.
Article
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Objectives and methods —Data on 1462 injured bicyclists aged 1–19, obtained over a period of five years from the British Columbia Children's Hospital as part of a national emergency room based program in Canada, were analyzed to describe the epidemiology of injuries, helmet use, and the occurrence of head injuries before the enactment of a new mandatory helmet law. The odds ratio (OR) and 95% confidence interval (CI) were calculated for non-users compared with helmet users. Results —Bicycle injuries comprised 4% of all injuries seen in the five year study period. The proportion of admissions was 12.7% among bicyclists, significantly higher than the 7.9% admissions of all 35 323 non-bicyclist children who were seen during the study period (OR = 1.96, CI = 1.44 to 1.99). Boys were injured more often than girls. The proportion of admissions for boys was 13.8% compared with 10.2% among girls (OR = 1.41, CI = 0.97 to 2.05). More than 70% of injured bicyclists reported no helmet use. The proportion of admissions of injured bicyclists who did not use helmets was always higher than the proportion of admissions of those who used helmets (OR = 2.23, CI = 1.39 to 3.62). Head and face injuries occurred more often among those who did not use helmets (OR = 1.55, CI= 1.18 to 2.04 ). However, there was no excess of minor head injuries among non-users (OR = 1.10, CI = 0.60 to 2.06). Of the 62 concussions, 57 occurred to non-helmet users (OR = 4.04, CI = 1.55 to 11.47). Most injuries occurred in the upper (46.4%) or lower extremities (32.4%). Dental injuries occurred slightly more often among helmet users compared with non-users but this excess was not statistically significant (OR = 1.29, CI = 0.76 to 2.20). Conclusion —The data indicate the need to control injuries by using helmets. A decrease in the number of head injuries and their severity is expected when bicycle helmet use becomes law in British Columbia.
Article
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This paper presents the methodology used to improve knowledge about vulnerable road users accidents and more specifically pedestrians or cyclists. This work is based on a complete analysis of real accidents from three different approaches: in-depth accident investigation, numerical simulation with multibody model and experimental reconstitution with PMHS subject. Accidents chosen from an in-depth multidisciplinary investigation are numerical modelled using a multibody software. Then, a parametric study focused for instance on car velocity and victim position at impact is performed in order to find the best correlations with all indications produced by the in-depth analysis. Finally, the retained configuration close to the presumed real accident conditions is reproduced experimentally by crash-test using cadavers. All results are finally compared in order to validate the real accident reconstruction. This methodology is applied on two real accidents involving one pedestrian or one cyclist.
Article
Our previous report concerned an analysis of bicyclists struck laterally by cars, which is the most fatal type of accident. The current study compares the behavior of bicyclists struck frontally and from the rear by cars. Comparatively few bicyclist fatalities occur in frontal crash accidents. The comparison is based on accident analysis and MADYMO simulations using a humanlike model. Bicyclist impact behavior was made clear on the basis of computer simulations. It was found that the initial impact between a bicyclist's knee and the vehicle front structure is very important in reducing the impact velocity of the bicyclist's head.
Article
To study circumstances of bicycle accidents and nature of injuries sustained and to determine effect of safety helmets on pattern of injuries. Prospective study of patients with cycle related injuries. Accident and emergency department of teaching hospital. 1040 patients with complete data presenting to the department in one year with cycle related injuries, of whom 114 had worn cycle helmets when accident occurred. Type of accident and nature and distribution of injuries among patients with and without safety helmets. There were no significant differences between the two groups with respect to type of accident or nature and distribution of injuries other than those to the head. Head injury was sustained by 4/114 (4%) of helmet wearers compared with 100/928 (11%) of non-wearers (P = 0.023). Significantly more children wore helmets (50/309 (16%)) than did adults (64/731 (9%)) (P < 0.001). The incidence of head injuries sustained in accidents involving motor vehicles (52/288 (18%)) was significantly higher than in those not involving motor vehicles (52/754 (7%)) (chi 2 = 28.9, P < 0.0001). Multiple logistic regression analysis of probability of sustaining a head injury showed that only two variables were significant: helmet use and involvement of a motor vehicle. Mutually adjusted odds ratios showed a risk factor of 2.95 (95% confidence interval 1.95 to 4.47, P < 0.0001) for accidents involving a motor vehicle and a protective factor of 3.25 (1.17 to 9.06, P = 0.024) for wearing a helmet. The findings suggest an increased risk of sustaining head injury in a bicycle accident when a motor vehicle is involved and confirm protective effect of helmet wearing for any bicycle accident.
Article
The objectives of this study were to describe bicycle-related injuries in relation to injury patterns, age, gender and medical treatment in a defined Swedish population and to identify factors contributing to injury. The study group comprised all patients living in the county of Västmanland, Sweden, visiting a physician or dentist because of bicycle-related injury during one year (November 1989-October 1990). Cyclists were mostly injured on pavements, pedestrian malls and cycle tracks. Twenty percent of the events occurred on public roads in urban areas; most frequently, the injured were in the age range 0-24. The most common bicycle injury event involved no other party. The events were often caused by environmental factors, in combination with behaviour such as excessive speed, lack of attention, breach of traffic regulations or a co-ordination problem. Head injuries, including oral injuries, were the most common, in particular among children and adolescents. One in four children in the age range 0-9 sustained an oral injury.
Article
The objective was to evaluate the relationship between helmet damage and head injuries in helmeted bicyclists in a sub-study of a large case-control study of bicycle injuries and helmet effectiveness. The setting consisted of seven hospital emergency departments in Seattle, WA. Hospitalized patients and medical examiners cases were included. The participants in the study were helmeted bicyclists who suffered a head injury or who damaged or hit their helmet in a crash. The Snell Memorial Foundation laboratory evaluated the helmets, blinded to crash circumstance and injury diagnosis. Damage was scored on a five-point scale (0 = none to 4 = destroyed). The damage location for each helmet was coded into regions (six longitudinal and three latitudinal) and mapped onto a three-dimensional CAD (computer-aided design) model of a helmet. The same procedure was also followed for injury location, which was mapped onto a three-dimensional ISO (International Organization for Standardization) headform for visualization of head-injury distribution. 785 helmeted subjects met the criteria for inclusion in the sub-study, and 527 helmets were purchased and evaluated (67%). 316 (60%) of the helmets had no or minimal damage, and 209 (39.7%) had significant damage (score 2, 3 or 4). Helmet types were 49.7% hard shell, 34.2% thin shell and 16.1% no shell. The risk of head and brain injury increased if the helmet was destroyed: OR = 5.3 (95% CI 2.9, 9.9) and OR = 11.2 (95% CI 3.5, 37.9), respectively. A high proportion of helmet impacts were along the front edge of the helmet, with a preponderance of head injuries in the same region. The large number of impacts to the front rim of the helmet, combined with the substantial number of riders with injuries to the forehead, indicate that some helmets, because of poor fit or wearing style, expose the forehead to injury. In addition, the data indicate that for a small proportion of injuries, the energy to the helmet may exceed design limits.