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  • 1.
    Aare, Magnus
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Evaluation of head response to ballistic helmet impacts, using FEM2003Conference paper (Refereed)
  • 2. Aare, Magnus
    et al.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Evaluation of head response to ballistic helmet impacts using the finite element method2007In: International Journal of Impact Engineering, ISSN 0734-743X, E-ISSN 1879-3509, Vol. 34, no 3, p. 596-608Article in journal (Refereed)
    Abstract [en]

    Injuries to the head caused by ballistic impacts are not well understood. Ballistic helmets provide good protection, but still, injuries to both the skull and brain occur. Today there is a lack of relevant test procedure to evaluate the efficiency of a ballistic helmet. The purpose of this project was (1) to study how different helmet shell stiffness affects the load levels in the human head during an impact, and (2) to study how different impact angles affects the load levels in the human head. A detailed finite element (FE) model of the human head, in combination with an FE model of a ballistic helmet (the US Personal Armour System Ground Troops' (PASGT) geometry) was used. The head model has previously been validated against several impact tests on cadavers. The helmet model was validated against data from shooting tests. Focus was aimed on getting a realistic response of the coupling between the helmet and the head and not on modeling the helmet in detail. The studied data from the FE simulations were stress in the cranial bone, strain in the brain tissue, pressure in the brain, change in rotational velocity and translational and rotational acceleration. A parametric study was performed to see the influence of a variation in helmet shell stiffness on the outputs from the model. The effect of different impact angles was also studied. Dynamic helmet shell deflections larger than the initial distance between the shell and the skull should be avoided in order to protect the head from the most injurious threat levels. It is more likely that a fracture of the skull bone occurs if the inside of the helmet shell strikes the skull. Oblique ballistic impacts may in some cases cause higher strains in the brain tissue than pure radial ones.

  • 3.
    Aare, Magnus
    et al.
    KTH, Superseded Departments (pre-2005), Aeronautical and Vehicle Engineering.
    Kleiven, Svein
    KTH, Superseded Departments (pre-2005), Aeronautical and Vehicle Engineering.
    Halldin, Peter
    KTH, Superseded Departments (pre-2005), Aeronautical and Vehicle Engineering.
    Injury tolerances for oblique impact helmet testing2004In: International Journal of Crashworthiness, ISSN 1358-8265, E-ISSN 1754-2111, Vol. 9, no 1, p. 15-23Article in journal (Refereed)
    Abstract [en]

    The most frequently sustained severe injuries in motorcycle crashes are injuries to the head, and many of these are caused by rotational force. Rotational force is most commonly the result of oblique impacts to the head. Good testing methods for evaluating the effects of such impacts are currently lacking. There is also a need for improving our understanding of the effects of oblique impacts on the human head. Helmet standards currently in use today do not measure rotational effects in test dummy heads. However rotational force to the head results in large shear strains arising in the brain, which has been proposed as a cause of traumatic brain injuries like diffuse axonal injuries (DAI). This paper investigates a number of well-defined impacts, simulated using a detailed finite element (FE) model of the human head, an FE model of the Hybrid III dummy head and an FE model of a helmet. The same simulations were performed on both the FE human head model and the FE Hybrid III head model, both fitted with helmets. Simulations on both these heads were performed to describe the relationship between load levels in the FE Hybrid III head model and strains in the brain tissue in the FE human head model. In this study, the change in rotational velocity and the head injury criterion (HIC) value were chosen as appropriate measurements. It was concluded that both rotational and translational effects are important when predicting the strain levels in the human brain.

  • 4.
    Aare, Magnus
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Proposed global injury thresholds for oblique helmet impacts2003Conference paper (Refereed)
  • 5.
    Alvarez, Victor
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Fahlstedt, Madelen
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Importance of neck muscle tonus in head kinematics during pedestrian accidents2013In: 2013 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, 2013, p. 747-761Conference paper (Refereed)
    Abstract [en]

    Unprotected pedestrians are an exposed group in the rural traffic and the most vulnerable human body region is the head which is the source of many fatal injuries. This study was performed to gain a better understanding of the influence that the neck muscle tonus has on head kinematics during pedestrian accidents. This was done using a detailed whole body FE model and a detailed FE vehicle model. To determine the influence of the muscle tonus a series of simulations were performed where the vehicle speed, pedestrian posture and muscle tonus were varied. Since the human reaction time for muscle activation is in the order of the collision time, the pedestrian was assumed to be prepared for the oncoming vehicle in order to augment the possible influence of muscle tonus. From the simulations performed, kinematic data such as head rotations, trajectory and velocities were extracted for the whole collision event, as well as velocity and accelerations at head impact. These results show that muscle tonus can influence the head rotation during a vehicle collision and therefore alter the head impact orientation. The level of influence on head rotation was in general lower than when altering the struck leg forward and backward, but in the same order of magnitude for some cases. The influence on head accelerations was higher due to muscle tonus than posture in all cases.

  • 6.
    Alvarez, Victor
    et al.
    KTH.
    Halldin, Peter
    KTH.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    The Influence of Neck Muscle Tonus and Posture on Brain Tissue Strain in Pedestrian Head Impacts2014In: SAE Technical Papers, ISSN 0148-7191, Vol. 58Article in journal (Refereed)
    Abstract [en]

    Pedestrians are one of the least protected groups in urban traffic and frequently suffer fatal head injuries. An important boundary condition for the head is the cervical spine, and it has previously been demonstrated that neck muscle activation is important for head kinematics during inertial loading. It has also been shown in a recent numerical study that a tensed neck musculature also has some influence on head kinematics during a pedestrian impact situation. The aim of this study was to analyze the influence on head kinematics and injury metrics during the isolated time of head impact by comparing a pedestrian with relaxed neck and a pedestrian with increased tonus. The human body Finite Element model THUMS Version 1.4 was connected to head and neck models developed at KTH and used in pedestrian-to-vehicle impact simulations with a generalized hood, so that the head would impact a surface with an identical impact response in all simulations. In order to isolate the influence of muscle tonus, the model was activated shortly before head impact so the head would have the same initial position prior to impact among different tonus. A symmetric and asymmetric muscle activation scheme that used high level of activation was used in order to create two extremes to investigate. It was found that for the muscle tones used in this study, the influence on the strain in the brain was very minor, in general about 1-14% change. A relatively large increase was observed in a secondary peak in maximum strains in only one of the simulated cases. 

  • 7.
    Alvarez, Victor S
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Effect of pediatric growth on cervical spine kinematics and deformations in automotive crashes2018In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 71, p. 76-83, article id S0021-9290(18)30075-7Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) models are a powerful tool that can be used to understand injury mechanisms and develop better safety systems. This study aims to extend the understanding of pediatric spine biomechanics, where there is a paucity of studies available. A newly developed and continuously scalable FE model was validated and scaled to 1.5-, 3-, 6-, 10-, 14- and 18-year-old using a non-linear scaling technique, accounting for local topological changes. The oldest and youngest ages were also scaled using homogeneous geometric scaling. To study the effect of pediatric spinal growth on head kinematics and intervertebral disc strain, the models were exerted to 3.5 g acceleration pulse at the T1 vertebra to simulate frontal, rear and side impacts. It was shown that the head rotation increases with age, but is over predicted when geometrically scaling down from 18- to 1.5-year-old and under predicted when geometrically scaling up from 1.5- to 18-year-old. The strain in the disc, however, showed a clear decrease with age in side impact and for the upper cervical spine in rear impact, indicating a higher susceptibility for neck injury at younger ages. In the frontal impact, no clear age dependence could be seen, suggesting a large contribution from changed facet joint angles, and lower levels of strain, suggesting a lower risk of injury. The results also highlight the benefit of rearward facing children in a seat limiting head lateral motion.

  • 8.
    Alvarez, Victor S
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Importance of Windscreen Modelling Approach for Head Injury Prediction2016In: 2016 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, 2016Conference paper (Refereed)
    Abstract [en]

    The objective of this study is to evaluate the capability of two modelling approaches in capturing  both accelerations and deformations from head impacts, and to evaluate the effect of modelling approach on  brain injury prediction. The first approach is a so‐called smeared technique, in which the properties of the two  glass  sheets and  the intermediate  polyvinyl  butyral  (PVB) are  combined and  divided into  two  coinciding  shell layers, of which one can fracture. The second approach consists of three shell layers, representing the glass and  PVB,  separated by  the  distance of  their  thickness, using a non‐local  failure criterion  to initiate  fracture in  the  glass.  The  two  modelling  approaches  are  compared  to  impact  experiments  of  flat  circular  windscreens,  measuring  deformations  and  accelerations  as  well  as  accelerations  from  impacts  against  full  vehicle  windscreens.  They  are  also  used  to  study  head‐to‐windscreen  impacts  using  a  detailed  Finite  Element  (FE)  model,  varying  velocity,  impact  direction  and  impact  point.  Only  the  non‐local  failure  model  is  able  to  adequately  capture  both  the accelerations and  deformations  of an  impactor. The FE  head model  simulations  also reveal that the choice of modelling approach has a large effect on the both localisation of the strain in the  brain and the characteristics of the strain‐time curve, with a difference in peak strain between 8% and 40%.  

  • 9. Beillas, P.
    et al.
    Petit, P.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kirscht, S.
    Chawla, A.
    Jolivet, E.
    Faure, F.
    Praxl, N.
    Bhaskar, A.
    Specifications of a software framework to position and personalise human body models2015In: 2015 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, International Research Council on the Biomechanics of Injury , 2015, p. 594-595Conference paper (Refereed)
  • 10. Beillas, Philippe
    et al.
    Wang, Xuguang
    Lafon, Yoann
    Frechede, Bertrand
    Janak, Tomas
    Dupeux, Thomas
    Mear, Matthieu
    Pacquaut, Guillaume
    Chevalier, Marie-Christine
    Le Ruyet, Anicet
    Eichene, Alexandre
    Theodorakos, Ilias
    Yin, Xingjia
    Gardegaront, M
    Collot, Jerome
    Petit, Philippe
    Eric, Song
    Moreau, Baptiste
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Giordano, Chiara
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Strömbäck, Alvarez Victor
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    et al,
    PIPER EU Project Final publishable summary2017Report (Refereed)
  • 11. Cecchi, N. J.
    et al.
    Domel, A. G.
    Liu, Y.
    Rice, E.
    Lu, R.
    Zhan, X.
    Zhou, Z.
    Raymond, S. J.
    Sami, S.
    Singh, H.
    Rangel, I.
    Watson, L. P.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Zeineh, M.
    Camarillo, D. B.
    Grant, G.
    Identifying Factors Associated with Head Impact Kinematics and Brain Strain in High School American Football via Instrumented Mouthguards2021In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 49, no 10, p. 2814-2826Article in journal (Refereed)
    Abstract [en]

    Repeated head impact exposure and concussions are common in American football. Identifying the factors associated with high magnitude impacts aids in informing sport policy changes, improvements to protective equipment, and better understanding of the brain’s response to mechanical loading. Recently, the Stanford Instrumented Mouthguard (MiG2.0) has seen several improvements in its accuracy in measuring head kinematics and its ability to correctly differentiate between true head impact events and false positives. Using this device, the present study sought to identify factors (e.g., player position, helmet model, direction of head acceleration, etc.) that are associated with head impact kinematics and brain strain in high school American football athletes. 116 athletes were monitored over a total of 888 athlete exposures. 602 total impacts were captured and verified by the MiG2.0’s validated impact detection algorithm. Peak values of linear acceleration, angular velocity, and angular acceleration were obtained from the mouthguard kinematics. The kinematics were also entered into a previously developed finite element model of the human brain to compute the 95th percentile maximum principal strain. Overall, impacts were (mean ± SD) 34.0 ± 24.3 g for peak linear acceleration, 22.2 ± 15.4 rad/s for peak angular velocity, 2979.4 ± 3030.4 rad/s2 for peak angular acceleration, and 0.262 ± 0.241 for 95th percentile maximum principal strain. Statistical analyses revealed that impacts resulting in Forward head accelerations had higher magnitudes of peak kinematics and brain strain than Lateral or Rearward impacts and that athletes in skill positions sustained impacts of greater magnitude than athletes in line positions. 95th percentile maximum principal strain was significantly lower in the observed cohort of high school football athletes than previous reports of collegiate football athletes. No differences in impact magnitude were observed in athletes with or without previous concussion history, in athletes wearing different helmet models, or in junior varsity or varsity athletes. This study presents novel information on head acceleration events and their resulting brain strain in high school American football from our advanced, validated method of measuring head kinematics via instrumented mouthguard technology.

  • 12. Cloots, R. J. H.
    et al.
    van Dommelen, J. A. W.
    Nyberg, Tobias
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Geers, M. G. D.
    Micromechanics of diffuse axonal injury: influence of axonal orientation and anisotropy2011In: Biomechanics and Modeling in Mechanobiology, ISSN 1617-7959, E-ISSN 1617-7940, Vol. 10, no 3, p. 413-422Article in journal (Refereed)
    Abstract [en]

    Multiple length scales are involved in the development of traumatic brain injury, where the global mechanics of the head level are responsible for local physiological impairment of brain cells. In this study, a relation between the mechanical state at the tissue level and the cellular level is established. A model has been developed that is based on pathological observations of local axonal injury. The model contains axons surrounding an obstacle (e.g., a blood vessel or a brain soma). The axons, which are described by an anisotropic fiber-reinforced material model, have several physically different orientations. The results of the simulations reveal axonal strains being higher than the applied maximum principal tissue strain. For anisotropic brain tissue with a relatively stiff inclusion, the relative logarithmic strain increase is above 60%. Furthermore, it is concluded that individual axons oriented away from the main axonal direction at a specific site can be subjected to even higher axonal strains in a stress-driven process, e.g., invoked by inertial forces in the brain. These axons can have a logarithmic strain of about 2.5 times the maximum logarithmic strain of the axons in the main axonal direction over the complete range of loading directions. The results indicate that cellular level heterogeneities have an important influence on the axonal strain, leading to an orientation and location-dependent sensitivity of the tissue to mechanical loads. Therefore, these effects should be accounted for in injury assessments relying on finite element head models.

  • 13.
    Cloots, Rudy J.H.
    et al.
    Eindhoven University of Technology, Department of Mechanical Engineering.
    van Dommelen, J.A.W.
    Eindhoven University of Technology, Department of Mechanical Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Geers, Marc
    Eindhoven University of Technology, Department of Mechanical Engineering.
    Multi-scale mechanics of traumatic brain injury: predicting axonal strains from head loads2013In: Biomechanics and Modeling in Mechanobiology, ISSN 1617-7959, E-ISSN 1617-7940, Vol. 12, no 1, p. 137-150Article in journal (Refereed)
    Abstract [en]

    The length scales involved in the development of diffuse axonal injury typically range from the head level (i.e., mechanical loading) to the cellular level. The parts of the brain that are vulnerable to this type of injury are mainly the brainstem and the corpus callosum, which are regions with highly anisotropically oriented axons. Within these parts, discrete axonal injuries occur mainly where the axons have to deviate from their main course due to the presence of an inclusion. The aim of this study is to predict axonal strains as a result of a mechanical load at the macroscopic head level. For this, a multi-scale finite element approach is adopted, in which a macro-level head model and a micro-level critical volume element are coupled. The results show that the axonal strains cannot be trivially correlated to the tissue strain without taking into account the axonal orientations, which indicates that the heterogeneities at the cellular level play an important role in brain injury and reliable predictions thereof. In addition to the multi-scale approach, it is shown that a novel anisotropic equivalent strain measure can be used to assess these micro-scale effects from head-level simulations only.

  • 14.
    Cloots, Rudy J.H.
    et al.
    Eindhoven University of Technology, Department of Mechanical Engineering.
    van Dommelen, JAW
    Eindhoven University of Technology, Department of Mechanical Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Geers, Marc
    Eindhoven University of Technology, Department of Mechanical Engineering.
    Traumatic Brain Injury at Multiple Length Scales: Relating Diffuse Axonal Injury to Discrete Axonal Impairment2010In: 2010 INTERNATIONAL IRCOBI CONFERENCE ON THE BIOMECHANICS OF INJURY PROCEEDINGS, 2010, p. 119-130Conference paper (Refereed)
  • 15. Cui, Zhao Ying
    et al.
    Famaey, Nele
    Depreitere, Bart
    Ivens, Jan
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Vander Sloten, Jos
    On the assessment of bridging vein rupture associated acute subdural hematoma through finite element analysis2017In: Computer Methods in Biomechanics and Biomedical Engineering, ISSN 1025-5842, E-ISSN 1476-8259, Vol. 20, no 5, p. 530-539Article in journal (Refereed)
    Abstract [en]

    Acute subdural hematoma (ASDH) is a type of intracranial haemorrhage following head impact, with high mortality rates. Bridging vein (BV) rupture is a major cause of ASDH, which is why a biofidelic representation of BVs in finite element (FE) head models is essential for the successful prediction of ASDH. We investigated the mechanical behavior of BVs in the KTH FE head model. First, a sensitivity study quantified the effect of loading conditions and mechanical properties on BV strain. It was found that the peak rotational velocity and acceleration and pulse duration have a pronounced effect on the BV strains. Both Young's modulus and diameter are also negatively correlated with the BV strains. A normalized multiple linear regression model using Young's modulus, outer diameter and peak rotational velocity to predict the BV strain yields an adjusted -value of 0.81. Secondly, cadaver head impact experiments were simulated with varying sets of mechanical properties, upon which the amount of successful BV rupture predictions was evaluated. The success rate fluctuated between 67 and 75%. To further increase the predictive capability of FE head models w.r.t. BV rupture, future work should be directed towards improvement of the BV representation, both geometrically and mechanically.

  • 16.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Abayazid, F.
    Imperial College, Dyson School of Design Engineering.
    Panzer, M. B.
    University of Virginia, Department of Mechanical and Aerospace Engineering.
    Trotta, A.
    University Collge Dublin, School of Mechanical & Materials Engineering.
    Zhao, W.
    Worcester Polytechnic Institute, Department of Mechanical Engineering.
    Ghajari, M.
    Imperial College, Dyson School of Design Engineering.
    Gilchrist, M. D.
    University College Dublin, School of Mechanical & Materials Engineering.
    Ji, S.
    Worcester Polytechnic Institute, Department of Mechanical Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Annaidh, A. N.
    University College Dublin, School of Mechanical & Materials Engineering.
    Halldin, Peter
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Ranking and Rating Bicycle Helmet Safety Performance in Oblique Impacts Using Eight Different Brain Injury Models2021In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686Article in journal (Refereed)
    Abstract [en]

    Bicycle helmets are shown to offer protection against head injuries. Rating methods and test standards are used to evaluate different helmet designs and safety performance. Both strain-based injury criteria obtained from finite element brain injury models and metrics derived from global kinematic responses can be used to evaluate helmet safety performance. Little is known about how different injury models or injury metrics would rank and rate different helmets. The objective of this study was to determine how eight brain models and eight metrics based on global kinematics rank and rate a large number of bicycle helmets (n=17) subjected to oblique impacts. The results showed that the ranking and rating are influenced by the choice of model and metric. Kendall’s tau varied between 0.50 and 0.95 when the ranking was based on maximum principal strain from brain models. One specific helmet was rated as 2-star when using one brain model but as 4-star by another model. This could cause confusion for consumers rather than inform them of the relative safety performance of a helmet. Therefore, we suggest that the biomechanics community should create a norm or recommendation for future ranking and rating methods.

  • 17.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Baeck, Katrien
    Mechanical Engineering Department, Biomechanics Section, Katholieke Universiteit Leuven, Belgium.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Vander Sloten, Jos
    Mechanical Engineering Department, Biomechanics Section, Katholieke Universiteit Leuven, Belgium.
    Goffin, Jan
    Mechanical Engineering Department, Biomechanics Section, Katholieke Universiteit Leuven, Belgium.
    Depreitere, Bart
    Mechanical Engineering Department, Biomechanics Section, Katholieke Universiteit Leuven, Belgium.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Influence of impact velocity and angle in a detailed reconstruction of a bicycle accident2012In: 2012 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, 2012, p. 787-799Conference paper (Refereed)
    Abstract [en]

    Bicycle accidents have become the most common cause of serious injury in the traffic during the last couple of years in Sweden. The objective of this study was to investigate the effect of the input variables, initial velocity and head orientation, of a bicycle accident reconstruction on the strain levels in the brain using a detailed FE head model. The accident involved a non-helmeted 68 year old male who sustained a linear skull fracture, contusions, acute subdural hematoma, and small bleeding at the swelling (subarachnoid blood). The orientation of the head just before impact was determined from the swelling appearing in the computer tomography (CT) scans. The head model used in this study was developed at the Royal Institute of Technology in Stockholm. The stress in the cranial bone, first principal strain in the brain tissue and acceleration were determined. The model was able to predict a strain pattern that correlated well with the medical images from the victim. The variation study showed that the tangential velocity had a large effect on the strain levels in the studied case. The strain pattern indicated larger areas of high strain with increased tangential velocity especially at the more superior sections.

  • 18.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Depreitere, Bart
    Experimental Neurosurgery and Neuroanatomy, KU Leuven, Belgium.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Vander Sloten, Jos
    Biomechanics, KU Leuven, Belgium.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Correlation between Injury Pattern and Finite Element Analysis in Biomechanical Reconstructions of Traumatic Brain Injuries2015In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 48, no 7Article in journal (Refereed)
    Abstract [en]

    At present, Finite Element (FE) analyses are often used as a tool to better understand the mechanisms of head injury. Previously, these models have been compared to cadaver experiments, with the next step under development being accident reconstructions. Thus far, the main focus has been on deriving an injury threshold and little effort has been put into correlating the documented injury location with the response displayed by the FE model. Therefore, the purpose of this study was to introduce a novel image correlation method that compares the response of the FE model with medical images.

    The injuries shown on the medical images were compared to the strain pattern in the FE model and evaluated by two indices; the Overlap Index (OI) and the Location Index (LI). As the name suggests, OI measures the area which indicates both injury in the medical images and high strain values in the FE images. LI evaluates the difference in center of mass in the medical and FE images. A perfect match would give an OI and LI equal to 1.

    This method was applied to three bicycle accident reconstructions. The reconstructions gave an average OI between 0.01 and 0.19 for the three cases and between 0.39 and 0.88 for LI. Performing injury reconstructions are a challenge as the information from the accidents often is uncertain. The suggested method evaluates the response in an objective way which can be used in future injury reconstruction studies.

  • 19.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Comparison of MADYMO and Finite Element Human Body Models in Pedestrian Accidents with the Focus on Head KinematicsManuscript (preprint) (Other academic)
  • 20.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Comparison of multibody and finite element human body models in pedestrian accidents with the focus on head kinematics.2016In: Traffic Injury Prevention, ISSN 1538-9588, E-ISSN 1538-957X, Vol. 17, no 3Article in journal (Refereed)
    Abstract [en]

    OBJECTIVE: The objective of this study was to compare and evaluate the difference in head kinematics between the TNO and THUMS models in pedestrian accident situations.

    METHODS: The TNO pedestrian model (version 7.4.2) and the THUMS pedestrian model (version 1.4) were compared in one experiment setup and 14 different accident scenarios where the vehicle velocity, leg posture, pedestrian velocity, and pedestrian's initial orientation were altered. In all simulations, the pedestrian model was impacted by a sedan. The head trajectory, head rotation, and head impact velocity were compared, as was the trend when various different parameters were altered.

    RESULTS: The multibody model had a larger head wrap-around distance for all accident scenarios. The maximum differences of the head's center of gravity between the models in the global x-, y-, and z-directions at impact were 13.9, 5.8, and 5.6 cm, respectively. The maximum difference between the models in head rotation around the head's inferior-superior axis at head impact was 36°. The head impact velocity differed up to 2.4 m/s between the models. The 2 models showed similar trends for the head trajectory when the various parameters were altered.

    CONCLUSIONS: There are differences in kinematics between the THUMS and TNO pedestrian models. However, these model differences are of the same magnitude as those induced by other uncertainties in the accident reconstructions, such as initial leg posture and pedestrian velocity.

  • 21.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Importance of the Bicycle Helmet Design and Material for the Outcome in Bicycle Accidents2014In: Proceedings, International Cycling Safety Conference 2014, Chalmers , 2014, p. 1-14Conference paper (Refereed)
    Abstract [en]

    In Sweden the most common traffic group that needs to be hospitalized due to injury is cyclists where head injuries are the most common severe injuries. According to current standards, the performance of a helmet is only tested against radial impact which is not commonly seen in real accidents. Some studies about helmet design have been published but those helmets have been tested for only a few loading conditions. Therefore, the purpose of this study was to use finite element models to evaluate the effect of the helmet’s design on the head in some more loading conditions.

    A detailed head model was used to evaluate three different helmet designs as well as non-helmet situations. The first helmet (Baseline Helmet) was an ordinary helmet available on the market. The two other helmet designs were a modification of the Baseline helmet with either a lower density of the EPS liner (Helmet 1) or a sliding layer between the scalp and the EPS liner (Helmet 2). Four different impact locations combined with four different impact directions were tested.

    The study showed that using a helmet can reduce the peak linear acceleration (85%), peak angular acceleration (87%), peak angular velocity (77%) and peak strain in the brain tissue (77%). The reduction of the strain level was dependent on the loading conditions. Moreover, in thirteen of the sixteen loading conditions Helmet 2 gave lowest peak strain.

    The alteration of the helmet design showed that more can be done to improve the protective effect of the helmet. This study highlighted the need of a modification of current helmet standard test which can lead to helmets with even better protective properties as well as some challenges in implementing new test standards.

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  • 22.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    The protective effect of a helmet in three bicycle accidents: A finite element study2016In: Accident Analysis and Prevention, ISSN 0001-4575, E-ISSN 1879-2057, Vol. 91, p. 135-143Article in journal (Refereed)
    Abstract [en]

    There is some controversy regarding the effectiveness of helmets in preventing head injuries among cyclists. Epidemiological, experimental and computer simulation studies have suggested that helmets do indeed have a protective effect, whereas other studies based on epidemiological data have argued that there is no evidence that the helmet protects the brain. The objective of this study was to evaluate the protective effect of a helmet in single bicycle accident reconstructions using detailed finite element simulations. Strain in the brain tissue, which is associated with brain injuries, was reduced by up to 43% for the accident cases studied when a helmet was included. This resulted in a reduction of the risk of concussion of up to 54%. The stress to the skull bone went from fracture level of 80 MPa down to 13-16 MPa when a helmet was included and the skull fracture risk was reduced by up to 98% based on linear acceleration. Even with a 10% increased riding velocity for the helmeted impacts, to take into account possible increased risk taking, the risk of concussion was still reduced by up to 46% when compared with the unhelmeted impacts with original velocity. The results of this study show that the brain injury risk and risk of skull fracture could have been reduced in these three cases if a helmet had been worn.

  • 23.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    The Protective Effect of Bicycle HelmetsManuscript (preprint) (Other academic)
  • 24.
    Fahlstedt, Madelen
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Halldin, Peter
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    S. Alvarez, Victor
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Influence of the Body and Neck on Head Kinematics and Brain Injury Risk in Bicycle Accident Situations2016In: IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, International Research Council on the Biomechanics of Injury , 2016, p. 459-478Conference paper (Refereed)
    Abstract [en]

    Previous studies about the influence of the neck on head kinematics and brain injuries have shown different results. Today bicycle helmets are certified with only a headform in radial experiments but could be improved with oblique impacts. Then the question is how the helmet's performance will be affected by the neck and the rest of the body. Therefore, the objective of this study was to use finite element simulations to investigate the influence of the body on head kinematics and injury prediction in single bicycleaccident situations with and without a helmet. The THUMS-KTH model was used to study the difference between head only and full body. In total, a simulation matrix of 120 simulations was compared by altering initial impact posture, head protection, and muscle activation. The results show that the body in impacts against a hard surface can change the amplitudes and curve shapes of the kinematics and brain tissue strain. The study found an average ratio between head only and full body for peak brain tissue strain to be 1.04 (SD 0.11), for peak linear acceleration 1.06 (SD 0.04), for peak angular acceleration 1.08 (SD 0.09) and for peak angular velocity 1.05 (SD 0.13).

  • 25.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Current Playground Surface Test Standards Underestimate Brain Injury Risk for Children2019In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380Article in journal (Refereed)
    Abstract [en]

    Playgrounds surface test standards have been introduced to reduce the number of fatal and severe injuries. However, these test standards have several simplifications to make it practical, robust and cost-effective, such as the head is represented with a hemisphere, only the linear kinematics is evaluated and the body is excluded. Little is known about how these simplifications may influence the test results. The objective of this study was to evaluate the effect of these simplifications on global head kinematics and head injury prediction for different age groups. The finite element human body model PIPER was used and scaled to seven different age groups from 1.5 up to 18 years old, and each model was impacted at three different playground surface stiffness and three head impact locations. All simulations were performed in pairs, including and excluding the body. Linear kinematics and skull bone stress showed small influence if excluding the body while head angular kinematics and brain tissue strain were underestimated by the same simplification. The predicted performance of the three different playground surface materials, in terms of head angular kinematics and brain tissue strain, was also altered when including the body. A body and biofidelic neck need to be included, together with suitable head angular kinematics based injury thresholds, in future physical or virtual playground surface test standards to better prevent brain injuries.

  • 26.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    The Influence of the Body on Head Kinematics in Playground Falls for Different Age Groups2018In: Proceedings of International Research Council on Biomechanics of Injury (IRCOBI) Conference, 2018Conference paper (Refereed)
  • 27.
    Fahlstedt, Madelen
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Meng, Shiyang
    MIPS AB, Kemistvagen 1B, S-18379 Taby, Sweden..
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Influence of Strain post-processing on Brain Injury Prediction2022In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 132, article id 110940Article in journal (Refereed)
    Abstract [en]

    Finite element head models are a tool to better understand brain injury mechanisms. Many of the models use strain as output but with different percentile values such as 100th, 95th, 90th, and 50th percentiles. Some use the element value, whereas other use the nodal average value for the element. Little is known how strain post-processing is affecting the injury predictions and evaluation of different prevention systems. The objective of this study was to evaluate the influence of strain output on injury prediction and ranking.& nbsp;Two models with different mesh densities were evaluated (KTH Royal Institute of Technology head model and the Total Human Models for Safety (THUMS)). Pulses from reconstructions of American football impacts with and without a diagnosis of mild traumatic brain injury were applied to the models. The value for 100th, 99th, 95th, 90th, and 50th percentile for element and nodal averaged element strain was evaluated based on peak values, injury risk functions, injury predictability, correlation in ranking, and linear correlation.& nbsp;The injury risk functions were affected by the post-processing of the strain, especially the 100th percentile element value stood out. Meanwhile, the area under the curve (AUC) value was less affected, as well as the correlation in ranking (Kendall's tau 0.71-1.00) and the linear correlation (Pearson's r2 0.72-1.00). With the results presented in this study, it is important to stress that the same post-processed strain should be used for injury predictions as the one used to develop the risk function.

  • 28.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Cloots, R. J. H.
    van Dommelen, J. A. W.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    The influence of anisotropy on brain injury prediction2014In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 47, no 5, p. 1052-1059Article in journal (Refereed)
    Abstract [en]

    Traumatic Brain Injury (TBI) occurs when a mechanical insult produces damage to the brain and disrupts its normal function. Numerical head models are often used as tools to analyze TBIs and to measure injury based on mechanical parameters. However, the reliability of such models depends on the incorporation of an appropriate level of structural detail and accurate representation of the material behavior. Since recent studies have shown that several brain regions are characterized by a marked anisotropy, constitutive equations should account for the orientation-dependence within the brain. Nevertheless, in most of the current models brain tissue is considered as completely isotropic. To study the influence of the anisotropy on the mechanical response of the brain, a head model that incorporates the orientation of neural fibers is used and compared with a fully isotropic model. A simulation of a concussive impact based on a sport accident illustrates that significantly lowered strains in the axonal direction as well as increased maximum principal strains are detected for anisotropic regions of the brain. Thus, the orientation-dependence strongly affects the response of the brain tissue. When anisotropy of the whole brain is taken into account, deformation spreads out and white matter is particularly affected. The introduction of local axonal orientations and fiber distribution into the material model is crucial to reliably address the strains occurring during an impact and should be considered in numerical head models for potentially more accurate predictions of brain injury.

  • 29.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Connecting Fractional Anisotropy from Medical Images with Mechanical Anisotropy of a Hyperviscoelastic Fibre-reinforced Constitutive Model for Brain Tissue2014In: Journal of the Royal Society Interface, ISSN 1742-5689, E-ISSN 1742-5662, Vol. 11, no 91, p. 20130914-Article in journal (Refereed)
    Abstract [en]

    Brain tissue modelling has been an active area of research for years. Brain matter does not follow the constitutive relations for common materials and loads applied to the brain turn into stresses and strains depending on tissue local morphology. In this work, a hyperviscoelastic fibre-reinforced anisotropic law is used for computational brain injury prediction. Thanks to a fibrere-inforcement dispersion parameter, this formulation accounts for anisotropic features and heterogeneities of the tissue owing to different axon alignment. The novelty of the work is the correlation of the material mechanical anisotropy with fractional anisotropy (FA) from diffusion tensor images. Finite-element (FE) models are used to investigate the influence of the fibre distribution for different loading conditions. In the case of tensile-compressive loads, the comparison between experiments and simulations highlights the validity of the proposed FA-k correlation. Axon alignment affects the deformation predicted by FE models and, when the strain in the axonal direction is large with respect to the maximum principal strain, decreased maximum deformations are detected. It is concluded that the introduction of fibre dispersion information into the constitutive law of brain tissue affects the biofidelity of the simulations.

  • 30.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Development of a 3-year-old child FE head model, continuously scalable from 1.5-to 6-year-old2016In: 2016 IRCOBI Conference Proceedings - International Research Council on the Biomechanics of Injury, International Research Council on the Biomechanics of Injury , 2016, p. 288-302Conference paper (Refereed)
    Abstract [en]

    This study summarised efforts in developing a 3-year-old FE head model, continuously scalable in the range 1.5-to 6-year-old. The FE models were transformed into one another using nonlinear scaling driven by control points corresponding to anthropometric dimensions. Procedures to mimic age-specific structural changes occurring during the paediatric development were implemented by means of transition of elements. The performances of the head models were verified on drop and compressive tests available from the literature. A stable and experimentally well-correlated family of FE models in the range 1.5-to 6-year-old was created.

  • 31.
    Giordano, Chiara
    et al.
    KTH.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury2016In: SAE Technical Papers, SAE International , 2016, no NovemberConference paper (Refereed)
    Abstract [en]

    This study describes a method to identify laboratory test procedures and impact response requirements suitable for assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of the experimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility and relevance of the available experimental data. A weighted averaging procedure was chosen in order to consider different contributions from the various test conditions and target measurements based on experimental error. According to the quality criteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of response curves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time history response to the measured data. Optimization of the CORA global settings led to the recommendation of performing curve comparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation. The allowable maximum time shift was adjusted depending on the shape of the experimental curves (DMAX = 0.12 for intracranial pressure, DMAX = 0.40 for brain motion and DMAX = 0.25 for brain deformation). Finally, bigger penalization of ratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or time shift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage of finite element head models for traumatic brain injury prediction. 

  • 32.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH).
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Development of an Unbiased Validation Protocol to Assess the Biofidelity of Finite Element Head Models used in Prediction of Traumatic Brain Injury2016In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 60, p. 363-471Article in journal (Refereed)
    Abstract [en]

    This study describes a method to identify laboratory test procedures and impact response requirements suitablefor assessing the biofidelity of finite element head models used in prediction of traumatic brain injury. The selection of theexperimental data and the response requirements were result of a critical evaluation based on the accuracy, reproducibility andrelevance of the available experimental data. A weighted averaging procedure was chosen in order to consider differentcontributions from the various test conditions and target measurements based on experimental error. According to the qualitycriteria, 40 experimental cases were selected to be a representative dataset for validation. Based on the evaluation of responsecurves from four head finite element models, CORA was chosen as a quantitative method to compare the predicted time historyresponse to the measured data. Optimization of the CORA global settings led to the recommendation of performing curvecomparison on a fixed time interval of 0-30 ms for intracranial pressure and at least 0-40 ms for brain motion and deformation.The allowable maximum time shift was adjusted depending on the shape of the experimental curves (􀜦􀯆􀮺􀯑􀀃􀀃= 0.12 forintracranial pressure, 􀜦􀯆􀮺􀯑 = 0.40 for brain motion and 􀜦􀯆􀮺􀯑 = 0.25 for brain deformation). Finally, bigger penalization ofratings was assigned to curves with fundamentally incorrect shape compared to those having inaccuracies in amplitude or timeshift (cubic vs linear). This rigorous approach is necessary to ensure confidence in the model results and progress in the usage offinite element head models for traumatic brain injury prediction.

  • 33.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Evaluation of Axonal Strain as a Predictor for Mild Traumatic Brain Injuries Using Finite Element Modeling2014In: Stapp Car Crash Journal, ISSN 1532-8546, Vol. 58Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI.Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC.

  • 34.
    Giordano, Chiara
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Neuronic Engineering.
    Evaluation of Axonal Strain as a Predictor for Mild Traumatic Brain Injuries Using Finite Element Modeling2014In: SAE Technical Papers, ISSN 0148-7191Article in journal (Refereed)
    Abstract [en]

    Finite element (FE) models are often used to study the biomechanical effects of traumatic brain injury (TBI). Measures based on mechanical responses, such as principal strain or invariants of the strain tensor, are used as a metric to predict the risk of injury. However, the reliability of inferences drawn from these models depends on the correspondence between the mechanical measures and injury data, as well as the establishment of accurate thresholds of tissue injury. In the current study, a validated anisotropic FE model of the human head is used to evaluate the hypothesis that strain in the direction of fibers (axonal strain) is a better predictor of TBI than maximum principal strain (MPS), anisotropic equivalent strain (AESM) and cumulative strain damage measure (CSDM). An analysis of head kinematics-based metrics, such as head injury criterion (HIC) and brain injury criterion (BrIC), is also provided. Logistic regression analysis is employed to compare binary injury data (concussion/no concussion) with continuous strain/kinematics data. The threshold corresponding to 50% of injury probability is determined for each parameter. The predictive power (area under the ROC curve, AUC) is calculated from receiver operating characteristic (ROC) curve analysis. The measure with the highest AUC is considered to be the best predictor of mTBI.Logistic regression shows a statistical correlation between all the mechanical predictors and injury data for different regions of the brain. Peaks of axonal strain have the highest AUC and determine a strain threshold of 0.07 for corpus callosum and 0.15 for the brainstem, in agreement with previously experimentally derived injury thresholds for reversible axonal injury. For a data set of mild TBI from the national football league, the strain in the axonal direction is found to be a better injury predictor than MPS, AESM, CSDM, BrIC and HIC. 

  • 35.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Li, Xiaogai
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Performances of the PIPER scalable child human body model in accident reconstruction2017In: PLOS ONE, E-ISSN 1932-6203, Vol. 12, no 11, article id e0187916Article in journal (Refereed)
    Abstract [en]

    Human body models (HBMs) have the potential to provide significant insights into the pediatric response to impact. This study describes a scalable/posable approach to perform child accident reconstructions using the Position and Personalize Advanced Human Body Models for Injury Prediction (PIPER) scalable child HBM of different ages and in different positions obtained by the PIPER tool. Overall, the PIPER scalable child HBM managed reasonably well to predict the injury severity and location of the children involved in real-life crash scenarios documented in the medical records. The developed methodology and workflow is essential for future work to determine child injury tolerances based on the full Child Advanced Safety Project for European Roads (CASPER) accident reconstruction database. With the workflow presented in this study, the open-source PIPER scalable HBM combined with the PIPER tool is also foreseen to have implications for improved safety designs for a better protection of children in traffic accidents.

  • 36.
    Giordano, Chiara
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering.
    Zappalà, Stefano
    KTH, School of Technology and Health (STH).
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Anisotropic finite element models for brain injury prediction: the sensitivity of axonal strain to white matter tract inter-subjectvariability2017In: Biomechanics and Modeling in Mechanobiology, ISSN 1617-7959, E-ISSN 1617-7940Article in journal (Refereed)
    Abstract [en]

    Computational models incorporating anisotropic features of brain tissue have become a valuable tool for studying the occurrence of traumatic brain injury. The tissue deformation in the direction of white matter tracts (axonal strain) was repeatedly shown to be an appropriate mechanical parameter to predict injury. However, when assessing the reliability of axonal strain to predict injury in a population, it is important to consider the predictor sensitivity to the biological inter-subject variability of the human brain. The present study investigated the axonal strain response of 485 white matter subject-specific anisotropic finite element models of the head subjected to the same loading conditions. It was observed that the biological variability affected the orientation of the preferential directions (coefficient of variation of 39.41% for the elevation angle—coefficient of variation of 29.31% for the azimuth angle) and the determination of the mechanical fiber alignment parameter in the model (gray matter volume 55.55–70.75%). The magnitude of the maximum axonal strain showed coefficients of variation of 11.91%. On the contrary, the localization of the maximum axonal strain was consistent: the peak of strain was typically located in a 2 cm3 volume of the brain. For a sport concussive event, the predictor was capable of discerning between non-injurious and concussed populations in several areas of the brain. It was concluded that, despite its sensitivity to biological variability, axonal strain is an appropriate mechanical parameter to predict traumatic brain injury.

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  • 37.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Aare, Magnus
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    von Holst, Hans
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Improved helmet design and test methods to reduce rotational induced brain injuries2003Conference paper (Refereed)
    Abstract [en]

    Accidental impacts to the human head are often a combination of translational and rotational accelerations. The most frequent severe brain injuries from accidents are diffuse axonal injury (DAI) and subdural hematoma that both are reported to arise from rotational violence to the head. Most helmet standards used today do only take the translational accelerations into account. It is therefore suggested that an oblique impact test that measures both translational and rotational accelerations should be a complement to the helmet standards used today. This study investigates the potential to reduce the risk for DAI by improving the helmet design by use of an oblique helmet impact test rig. The method used is a detailed finite element (FE) model of the human head. The FE model is used to measure the maximum principal strain in the brain which is suggested as a measurement for the risk to get DAI. The results clearly show the importance of testing a helmet in oblique impacts. Comparing a pure vertical impact with a 45 degree oblique impact with the same initial impact energy shows that the strain in the central parts of the brain is increased with a factor of 6. It is therefore suggested that a future helmet impact standard should include a rotational component so that the helmet is designed for both radial and tangential forces. Such a test method, an oblique impact test, was used to compare two different helmet designs. One helmet was manufactured with the shell glued to the liner and one helmet was designed with a low friction layer between the shell and the liner (MIPS). It was shown that the strain in the FE model of the human head was reduced be 27% comparing the MIPS helmet to the glued helmet design.

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    fulltext
  • 38.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Aare, Magnus
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    von Holst, Hans
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Reduced risk for DAI by use of a new safety helmet2003Conference paper (Refereed)
    Abstract [en]

    Accidental impacts to the human head are often a combination of translational and rotational accelerations. The most frequent severe brain injuries from accidents are diffuse axonal injury (DAI) and subdural hematoma that both are reported to arise from rotational violence to the head. Most helmet standards used today do only take the translational accelerations into account. It is therefore suggested that an oblique impact test that measures both translational and rotational accelerations should be a complement to the helmet standards used today. This study investigates the potential to reduce the risk for DAI by improving the helmet design by use of an oblique helmet impact test rig. The method used is a detailed finite element (FE) model of the human head. The FE model is used to measure the maximum principal strain in the brain which is suggested as a measurement for the risk to get DAI. The results clearly show the importance of testing a helmet in oblique impacts. Comparing a pure vertical impact with a 45 degree oblique impact with the same initial impact energy shows that the strain in the central parts of the brain is increased with a factor of 6. It is therefore suggested that a future helmet impact standard should include a rotational component so that the helmet is designed for both radial and tangential forces. Such a test method, an oblique impact test, was used to compare two different helmet designs. One helmet was manufactured with the shell glued to the liner and one helmet was designed with a low friction layer between the shell and the liner (MIPS). It was shown that the strain in the FE model of the human head was reduced be 27% comparing the MIPS helmet to the glued helmet design.

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  • 39.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Jakobsson, Lotta
    Chalmers tekniska högskola School of Mechanical Engineering. Institutionen för tillämpad mekanik. .
    Brolin, Karin
    Chalmers tekniska högskola School of Mechanical Engineering. Institutionen för tillämpad mekanik. .
    Palmertz, Camilla
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    von Holst, Hans
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Investigations of Conditions that Affect Neck Compression-Flexion Injuries Using Numerical Techniques2000In: Stapp Car Crash Journal, ISSN 1532-8546Article in journal (Refereed)
  • 40.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Improved helmet design and test methods to reduce rotational induced brain injuries2009Conference paper (Other (popular science, discussion, etc.))
  • 41.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    The development of next generation test standards for helmets.2013In: The development of next generation test standards for helmets., 2013, Vol. 1, article id HPD-2013-1Conference paper (Refereed)
    Abstract [en]

    Injury statistics show that accidents with a head impact often happen with an angle to the impacting object. An angled impact will result in a rotation of the head if the friction is high enough. It is also known that the head is more sensitive to rotation than pure linear motion of the head. CEN has initiated the work to design a new helmet test oblique or angled impact test method a helmet test method that can measure the rotational energy absorption in a helmet during an angled impact. This paper presents a short summary of possibilities and limitations on how to build a helmet test method that can measure the rotational energy absorption in a helmet during an angled impact.

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  • 42.
    Halldin, Peter
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Lanner, Daniel
    MIPS AB.
    Coomber, Richard
    Revision Military Inc., Montreal, Canada.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Evaluation of blunt impact protection in a military helmet designed to offer blunt & ballistic impact protection.2013In: Proceedings of the 1st International Conference on Helmet Performance and Design, 2013, article id HPD-2013-6Conference paper (Refereed)
    Abstract [en]

    This paper describes both a numerical and an experimental approach to measuring the ballistic and blunt impact protection offered by military helmets. The primary purpose of military helmets is to protect users from ballistic impact but modern military helmets protect users from blunt force as well. Altering ballistic shell stiffness, lining the shell with material of different density, even separating the liner from the shell so that they can move independently all affect the transfer of stress to the head and the resulting strain experienced by the brain. The results of this study suggest that there is potential for a helmet that protects the user from both blunt and ballistic impact and can be further improved by implementing an energy absorbing sliding layer, such as the MIPS system, between the shell and the liner to mitigate the effect of oblique impacts.

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  • 43. Hernandez, F.
    et al.
    Wu, L. C.
    Yip, M. C.
    Hoffman, A. R.
    Lopez, J.
    Grant, G.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Camarillo, D. B.
    Finite Element Simulation Of Brain Deformation From Six Degree Of Freedom Acceleration Measurements Of Mild Traumatic Brain Injury2014In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 31, no 12, p. A124-A124Article in journal (Other academic)
  • 44. Hernandez, Fidel
    et al.
    Giordano, Chiara
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Camarillo, David
    CORONAL HEAD ROTATION, FALX CEREBRI DISPLACEMENT, AND CORPUS CALLOSUM STRAIN ARE RELATED AND IMPLICATED IN SPORTS-RELATED MTBI2016In: Journal of Neurotrauma, ISSN 0897-7151, E-ISSN 1557-9042, Vol. 33, no 13, p. A34-A35Article in journal (Other academic)
  • 45. Hernandez, Fidel
    et al.
    Wu, Lyndia C
    Yip, Michael C
    Laksari, Kaveh
    Hoffman, Andrew R
    Lopez, Jaime R
    Grant, Gerald A
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Camarillo, David B
    Erratum to: Six Degree-of-Freedom Measurements of Human Mild Traumatic Brain Injury.2016In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 44, no 3, p. 828-829Article in journal (Refereed)
  • 46. Hernandez, Fidel
    et al.
    Wu, Lyndia C.
    Yip, Michael C.
    Laksari, Kaveh
    Hoffman, Andrew R.
    Lopez, Jaime R.
    Grant, Gerald A.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Medical Engineering, Neuronic Engineering.
    Camarillo, David B.
    Six Degree-of-Freedom Measurements of Human Mild Traumatic Brain Injury2015In: Annals of Biomedical Engineering, ISSN 0090-6964, E-ISSN 1573-9686, Vol. 43, no 8, p. 1918-1934Article in journal (Refereed)
    Abstract [en]

    This preliminary study investigated whether direct measurement of head rotation improves prediction of mild traumatic brain injury (mTBI). Although many studies have implicated rotation as a primary cause of mTBI, regulatory safety standards use 3 degree-of-freedom (3DOF) translation-only kinematic criteria to predict injury. Direct 6DOF measurements of human head rotation (3DOF) and translation (3DOF) have not been previously available to examine whether additional DOFs improve injury prediction. We measured head impacts in American football, boxing, and mixed martial arts using 6DOF instrumented mouthguards, and predicted clinician-diagnosed injury using 12 existing kinematic criteria and 6 existing brain finite element (FE) criteria. Among 513 measured impacts were the first two 6DOF measurements of clinically diagnosed mTBI. For this dataset, 6DOF criteria were the most predictive of injury, more than 3DOF translation-only and 3DOF rotation-only criteria. Peak principal strain in the corpus callosum, a 6DOF FE criteria, was the strongest predictor, followed by two criteria that included rotation measurements, peak rotational acceleration magnitude and Head Impact Power (HIP). These results suggest head rotation measurements may improve injury prediction. However, more 6DOF data is needed to confirm this evaluation of existing injury criteria, and to develop new criteria that considers directional sensitivity to injury.

  • 47.
    Ho, Johnson
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    An automatic method to generate a patient specific finite element head model2006In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 39, no 1, p. S428-Article in journal (Refereed)
  • 48.
    Ho, Johnson
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Can sulci protect the brain from traumatic injury?2009In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 42, no 13, p. 2074-2080Article in journal (Refereed)
    Abstract [en]

    The influence of sulci in dynamic finite element simulations of the human head has been investigated. First, a detailed 3D FE model was constructed based on an MRI scan of a human head. A second model with a smoothed brain surface was created based on the same MRI scan as the first FE model. These models were validated against experimental data to confirm their human-like dynamic responses during impact. The validated FE models were subjected to several acceleration impulses and the maximum principle strain and strain rate in the brain were analyzed. The results suggested that the inclusion of sulci should be considered for future FE head models as it alters the strain and strain distribution in an FE model.

  • 49.
    Ho, Johnson
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Dynamic response of the brain with vasculature: A three-dimensional computational study2007In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, Vol. 40, no 13, p. 3006-3012Article in journal (Refereed)
    Abstract [en]

    To date, the influence of the vasculature on the dynamic response of the brain has not been studied with a complete three-dimensional (3D) finite element head model. In this study, short duration rotational (10,000 rad/s2 with a duration of 5 ms) and translational (100G with a duration of 5 ms) acceleration impulses were applied to the 3D finite element models to study the dynamic response of the brain. The hypothesis of this study was that due to the convoluted organization and non-linear material properties of cerebral vasculature, the difference in maximum principle strain between models with and without vasculature should be minimal. The effects of non-linear material properties and the convoluted structure of the vasculature were examined by comparing the results from the 3D finite element models. The peak average strain reduction in a model with non-linear elastic vasculature and a model with linear elastic vasculature compared to a model without vasculature was 2% and 5%, respectively, indicating that the influence of the vasculature on the dynamic response of the brain is minimal.

  • 50.
    Ho, Johnson
    et al.
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Kleiven, Svein
    KTH, School of Technology and Health (STH), Neuronic Engineering.
    Investigation of the Dynamic Response Contribution of Vasculature in a 3D Finite Element Head Model2006Conference paper (Refereed)
1234 1 - 50 of 189
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