Validation of a simplified human body model in relaxed and braced conditions in low-speed frontal sled tests

Injury Risk Predictions in Lunar Terrain Vehicle (LTV) Extravehicular Activities (EVAs): A Pilot Study

Extravehicular activities will play a crucial role in lunar exploration on upcoming Artemis missions and may involve astronauts operating a lunar terrain vehicle (LTV) in a standing posture. This study assessed kinematic response and injury risks using an active muscle human body model (HBM) restrained in an upright posture on the LTV by simulating dynamic acceleration pulses related to lunar surface irregularities. Linear accelerations and rotational displacements of 5 lunar obstacles (3 craters; 2 rocks) over 5 slope inclinations were applied across 25 simulations. All body injury metrics were below NASA's injury tolerance limits, but compressive forces were highest in the lumbar (250-550N lumbar, tolerance: 5300N) and lower extremity (190-700N tibia, tolerance: 1350N) regions. There was a strong association between the magnitudes of body injury metrics and LTV resultant linear acceleration (ρ = 0.70-0.81). There was substantial upper body motion, with maximum forward excursion reaching 375 mm for the head and 260 mm for the chest. Our findings suggest driving a lunar rover in an upright posture for these scenarios is a low severity impact presenting low body injury risks. Injury metrics increased along the load path, from the lower body (highest metrics) to the upper body (lowest metrics). While upper body injury metrics were low, increased body motion could potentially pose a risk of injury from flail and occupant interaction with the surrounding vehicle, suit, and restraint hardware.

Predicting occupant head displacements in evasive maneuvers; tuning and comparison of a rotational based and a translational based neck muscle controller

Objective: Real-life car crashes are often preceded by an evasive maneuver, which can alter the occupant posture and muscle state. To simulate the occupant response in such maneuvers, human body models (HBMs) with active muscles have been developed. The aim of this study was to implement an omni-directional rotational head-neck muscle controller in the SAFER HBM and compare the bio-fidelity of the HBM with a rotational controller to the HBM with a translational controller, in simulations of evasive maneuvers. Methods: The rotational controller was developed using an axis-angle representation of head rotations, with x, y, and z components in the axis. Muscle load sharing was based on rotational direction in the simulation and muscle activity recorded in three volunteer experiments in these directions. The gains of the rotational and translational controller were tuned to minimize differences between translational and rotational head displacements of the HBM and volunteers in braking and lane change maneuvers using multi-objective optimizations. Bio-fidelity of the model with tuned controllers was evaluated objectively using CORrelation and Analysis (CORA). Results: The results indicated comparable performance for both controllers after tuning, with somewhat higher bio-fidelity for rotational kinematics with the translational controller. After tuning, good or excellent bio-fidelity was indicated for both controllers in the loading direction (forward in braking, and lateral in lane change), with CORA scores of 0.86-0.99 and 0.93-0.98 for the rotational and translational controllers, respectively. For rotational displacements, and translational displacements in the other directions, bio-fidelity ranged from poor to excellent, with slightly higher average CORA scores for the HBM with the translational controller in both braking and lane changing. Time-averaged muscle activity was within one standard deviation of time-averaged muscle activity from volunteers. Conclusion: Overall, the results show that when tuned, both the translational and rotational controllers can be used to predict the occupant response to an evasive maneuver, allowing for the inclusion of evasive maneuvers prior to a crash in evaluation of vehicle safety. The rotational controller shows potential in controlling omni-directional head displacements, but the translational controller outperformed the rotational controller. Thus, for now, the recommendation is to use the translational controller with tuned gains.

Passenger muscle responses in emergency braking events with reclined seating

Emergency braking can generate forward displacement that may influence the effectiveness of protection in collisions, especially for passengers. The development of automated vehicles has enabled the diversification and rationalization of sitting positions, including reclined seating. However, the passenger response in pre-crash scenarios in reclined seating differs from that in standard seating, which poses different requirements for biofidelic human body models (HBMs) to evaluate passenger injuries in collisions. This study conducted emergency braking trials in vehicles at an initial velocity of 80 km/h. Five volunteers were exposed to approximately 1 g manual emergency braking (MEB), and the muscle responses at the front passenger seat with backrest angles of 25°, 45°, and 65° were recorded. The electromyography obtained from 14 muscles of the neck, torso, and lower extremity were normalized using maximum voluntary contractions (MVCs). In the quiet sitting phase, the activity levels were low (< 5% MVC) in all muscles for the three sitting positions. During emergency braking, the muscles are activated to restrict the body motion. There were differences in muscle amplitude and onset time in different backrest angles, with higher muscle activity levels in most muscles in a reclined sitting position. In particular, the sternocleidomastoid, rectus abdominis, and vastus medialis showed different patterns in the peak and steady-state phases. We found that the tibialis anterior was consistently activated at a lower level in all sitting postures (< 8% MVC), which indicates limited support of the shank for the body. The data provided in the paper are presented in corridors and intended for use in the development and validation of HBMs with active muscle models to simulate evasive maneuvers that potentially occur before a crash in the reclined sitting position.

Modular incorporation of deformable spine and 3D neck musculature into a simplified human body finite element model

Spinal injuries are a concern for automotive applications, requiring large parametric studies to understand spinal injury mechanisms under complex loading conditions. Finite element computational human body models (e.g. Global Human Body Models Consortium (GHBMC) models) can be used to identify spinal injury mechanisms. However, the existing GHBMC detailed models (with high computational time) or GHBMC simplified models (lacking vertebral fracture prediction capabilities) are not ideal for studying spinal injury mechanisms in large parametric studies. To overcome these limitations, a modular 50th percentile male simplified occupant model combining advantages of both the simplified and detailed models, M50-OS + DeformSpine, was developed by incorporating the deformable spine and 3D neck musculature from the detailed GHBMC model M50-O (v6.0) into the simplified GHBMC model M50-OS (v2.3). This new modular model was validated against post-mortem human subject test data in four rigid hub impactor tests and two frontal impact sled tests. The M50-OS + DeformSpine model showed good agreement with experimental test data with an average CORrelation and Analysis (CORA) score of 0.82 for the hub impact tests and 0.75 for the sled impact tests. CORA scores were statistically similar overall between the M50-OS + DeformSpine (0.79 ± 0.11), M50-OS (0.79 ± 0.11), and M50-O (0.82 ± 0.11) models (p > 0.05). This new model is computationally 6 times faster than the detailed M50-O model, with added spinal injury prediction capabilities over the simplified M50-OS model.

A simulation-based study for optimizing proportional-integral-derivative controller gains for different control strategies of an active upper extremity model using experimental data

This study investigates the effect of PID controller gains, reaction time, and initial muscle activation values on active human model behavior while comparing three different control strategies. The controller gains and reaction delays were optimized using published experimental data focused on the upper extremity. The data describes the reaction of five male subjects in four tests based on two muscle states (relaxed and tensed) and two states of awareness (open and closed eye). The study used a finite element model of the left arm isolated from the Global Human Body Models Consortium (GHBMC) average male simplified occupant model for simulating biomechanical simulations. Major skeletal muscles of the arm were modeled as 1D beam elements and assigned a Hill-type muscle material. Angular position control, muscle length control, and a combination of both were used as a control strategy. The optimization process was limited to 4 variables; three Proportional-Integral-Derivative (PID) controller gains and one reaction delay time. The study assumed the relaxed and tensed condition require distinct sets of controller gains and initial activation and that the closed-eye simulations can be achieved by increasing the reaction delay parameter. A post-hoc linear combination of angle and muscle length control was used to arrive at the final combined control strategy. The premise was supported by variation in the controller gains depending on muscle state and an increase in reaction delay based on awareness. The CORA scores for open-eye relaxed, closed-eye relaxed, open-eye tensed, and closed-eye tensed was 0.95, 0.90, 0.95, and 0.77, respectively using the combined control strategy.

An investigation of tendon strains in jersey finger injury load cases using a finite element neuromuscular human body model

Introduction: A common hand injury in American football, rugby and basketball is the so-called jersey finger injury (JFI), in which an eccentric overextension of the distal interphalangeal joint leads to an avulsion of the connected musculus flexor digitorum profundus (FDP) tendon. In the field of automotive safety assessment, finite element (FE) neuromuscular human body models (NHBMs) have been validated and are employed to evaluate different injury types related to car crash scenarios. The goal of this study is to show, how such a model can be modified to assess JFIs by adapting the hand of an FE-NHBM for the computational analysis of tendon strains during a generalized JFI load case. Methods: A jersey finger injury criterion (JFIC) covering the injury mechanisms of tendon straining and avulsion was defined based on biomechanical experiments found in the literature. The hand of the Total Human Model for Safety (THUMS) version 3.0 was combined with the musculature of THUMS version 5.03 to create a model with appropriate finger mobility. Muscle routing paths of FDP and musculus flexor digitorum superficialis (FDS) as well as tendon material parameters were optimized using literature data. A simplified JFI load case was simulated as the gripping of a cylindrical rod with finger flexor activation levels between 0% and 100%, which was then retracted with the velocity of a sprinting college football player to forcefully open the closed hand. Results: The optimization of the muscle routing node positions and tendon material parameters yielded good results with minimum normalized mean absolute error values of 0.79% and 7.16% respectively. Tendon avulsion injuries were detected in the middle and little finger for muscle activation levels of 80% and above, while no tendon or muscle strain injuries of any kind occurred. Discussion: The presented work outlines the steps necessary to adapt the hand model of a FE-NHBM for the assessment of JFIs using a newly defined injury criterion called the JFIC. The injury assessment results are in good agreement with documented JFI symptoms. At the same time, the need to rethink commonly asserted paradigms concerning the choice of muscle material parameters is highlighted.

Development and verification of a physiologically motivated internal controller for the open-source extended Hill-type muscle model in LS-DYNA

Nowadays, active human body models are becoming essential tools for the development of integrated occupant safety systems. However, their broad application in industry and research is limited due to the complexity of incorporated muscle controllers, the long simulation runtime, and the non-regular use of physiological motor control approaches. The purpose of this study is to address the challenges in all indicated directions by implementing a muscle controller with several physiologically inspired control strategies into an open-source extended Hill-type muscle model formulated as LS-DYNA user-defined umat41 subroutine written in the Fortran programming language. This results in increased usability, runtime performance and physiological accuracy compared to the standard muscle material existing in LS-DYNA. The proposed controller code is verified with extensive experimental data that include findings for arm muscles, the cervical spine region, and the whole body. Selected verification experiments cover three different muscle activation situations: (1) passive state, (2) open-loop and closed-loop muscle activation, and (3) reflexive behaviour. Two whole body finite element models, the 50th percentile female VIVA OpenHBM and the 50th percentile male THUMS v5, are used for simulations, complemented by the simplified arm model extracted from the 50th percentile male THUMS v3. The obtained results are evaluated additionally with the CORrelation and Analysis methodology and the mean squared error method, showing good to excellent biofidelity and sufficient agreement with the experimental data. It was shown additionally how the integrated controller allows simplified mimicking of the movements for similar musculoskeletal models using the parameters transfer method. Furthermore, the Hill-type muscle model presented in this paper shows better kinematic behaviour even in the passive case compared to the existing one in LS-DYNA due to its improved damping and elastic properties. These findings provide a solid evidence base motivating the application of the enhanced muscle material with the internal controller in future studies with Active Human Body Models under different loading conditions.

Investigating sources for variability in volunteer kinematics in a braking maneuver, a sensitivity analysis with an active human body model

Occupant kinematics during evasive maneuvers, such as crash avoidance braking or steering, varies within the population. Studies have tried to correlate the response to occupant characteristics such as sex, stature, age, and BMI, but these characteristics explain no or very little of the variation. Therefore, hypothesis have been made that the difference in occupant response stems from voluntary behavior. The aim of this study was to investigate the effect from other sources of variability: in neural delay, in passive stiffness of fat, muscle tissues and skin, in muscle size and in spinal alignment, as a first step towards explaining the variability seen among occupants in evasive maneuvers. A sensitivity analysis with simulations of the SAFER Human Body Model in braking was performed, and the displacements from the simulations were compared to those of volunteers. The results suggest that the head and torso kinematics were most sensitive to spinal alignment, followed by muscle size. For head and torso vertical displacements, the range in model kinematics was comparable to the range in volunteer kinematics. However, for forward displacements, the included parameters only explain some of the variability seen in the volunteer experiment. To conclude, the results indicate that the variation in volunteer vertical kinematics could be partly attributed to the variability in human characteristics analyzed in this study, while these cannot alone explain the variability in forward kinematics. The results can be used in future tuning of HBMs, and in future volunteer studies, when further investigating the potential causes of the large variability seen in occupant kinematics in evasive maneuvers.

Repositioning forward-leaning passengers by seatbelt pre-pretensioning

OBJECTIVE

The study determined the seatbelt pre-pretensioner force needed and the time required to reposition average male front-seat passengers from forward-leaning to upright using finite element simulations of the Active SAFER Human Body Model (Active SHBM).

METHODS

The Active SHBM was positioned in an initial forward-leaning position (29° forward from upright) on a deformable vehicle seat. A pre-pretensioner was modeled as a pre-loaded spring and its ability to reposition the forward-leaning Active SHBM to an upright position was simulated for twenty-four different pre-crash conditions. Four parameters were varied: (1) Automated Emergency Braking (AEB) active with 11 m/s2 or no AEB, (2) type of seatbelt system: Belt-In-Seat or B-pillar, (3) pre-pretensioner activation time (200 ms before, 100 ms before, or at the same time as AEB ramp-up), and (4) pre-pretensioner force (200 N, 300 N, 400 N, 600 N). The first thoracic vertebra fore-aft (T1 X) trajectories were compared against a reference upright position to determine the force and time needed to reposition and the effectiveness of repositioning in the different conditions.

RESULTS

The lowest force enabling repositioning in all simulations was 400 N (no AEB, Belt-In-Seat). It took about 350 ms. In the presence of AEB, activating the pre-pretensioner 200 ms before AEB and using 600 N pre-pretensioner force was needed for repositioning (taking 200 ms with Belt-In-Seat and 260 ms with B-pillar installations). Repositioning was faster and thus more effective with the Belt-In-Seat seatbelt in all simulations.

CONCLUSIONS

All four parameters (presence of AEB, type of seatbelt system, pre-pretensioner activation time and force) affected the repositioning ability and time required. Far from all combinations repositioned a forward-leaning average male occupant model, but those found to be effective and fast appear as a feasible option for vehicle safety systems to reposition out-of-position occupants during pre-crash events.

Investigation of traffic accidents involving seated pedestrians using a finite element simulation-based approach

Pedestrians who use wheelchairs (seated pedestrians) report 36% - 75% higher mortality rates than standing pedestrians in car-to-pedestrian collisions but the cause of this mortality is unknown. This is the first study to investigate the cause of seated pedestrian mortality in vehicle impacts using finite element simulations. In this study a manual wheelchair model was developed using geometry taken from publicly available CAD data, and was tested to meet ISO standards. The GHBMC 50^th percentile male simplified occupant model was used as the seated pedestrian and the EuroNCAP family car and sports utility vehicle models were used as the impacting vehicles. The seated pedestrian was impacted by the two vehicles at three different locations on the vehicle and at 30 and 40 km/h. In 75% of the impacts the pedestrian was ejected from the wheelchair. In the rest of the impacts, the pedestrian and wheelchair were pinned to the vehicle and the pedestrian was not ejected. The underlying causes of seated pedestrian mortality in these impacts were head and brain injury. Life-threatening head injury risks (0.0% - 100%) were caused by the ground-pedestrian contact, and life-threatening brain injury risks (0.0 - 97.9%) were caused by the initial vehicle-wheelchair contact and ground-pedestrian contact. Thoracic and abdominal compression reported no risks of life-threatening injuries, but may do so in faster impacts or with different wheelchair designs. Protective equipment such as the wheelchair seatbelt or personal airbag may be useful in reducing injury risks but future research is required to investigate their efficacy.

Development and Validation of an Active Muscle Simplified Finite Element Human Body Model in a Standing Posture

Active muscles play an important role in postural stabilization, and muscle-induced joint stiffening can alter the kinematic response of the human body, particularly that of the lower extremities, under dynamic loading conditions. There are few full-body human body finite element models with active muscles in a standing posture. Thus, the objective of this study was to develop and validate the M50-PS+Active model, an average-male simplified human body model in a standing posture with active musculature. The M50-PS+Active model was developed by incorporating 116 skeletal muscles, as one-dimensional beam elements with a Hill-type material model and closed-loop Proportional Integral Derivative (PID) controller muscle activation strategy, into the Global Human Body Models Consortium (GHBMC) simplified pedestrian model M50-PS. The M50-PS+Active model was first validated in a gravity standing test, showing the effectiveness of the active muscles in maintaining a standing posture under gravitational loading. The knee kinematics of the model were compared against volunteer kinematics in unsuited and suited step-down tests from NASA's active response gravity offload system (ARGOS) laboratory. The M50-PS+Active model showed good biofidelity with volunteer kinematics with an overall CORA score of 0.80, as compared to 0.64 (fair) in the passive M50-PS model. The M50-PS+Active model will serve as a useful tool to study the biomechanics of the human body in vehicle-pedestrian accidents, public transportation braking, and space missions piloted in a standing posture.

Sensitivity Analysis for Multidirectional Spaceflight Loading and Muscle Deconditioning on Astronaut Response

A sensitivity analysis for loading conditions and muscle deconditioning on astronaut response for spaceflight transient accelerations was carried out using a mid-size male human body model with active musculature. The model was validated in spaceflight-relevant 2.5-15 g loading magnitudes in seven volunteer tests, showing good biofidelity (CORA: 0.69). Sensitivity analysis was carried out in simulations varying pulse magnitude (5, 10, and 15 g), rise time (32.5 and 120 ms), and direction (10 directions: frontal, rear, vertical, lateral, and their combination) along with muscle size change (± 15% change) and responsiveness (pre-braced, relaxed, vs. delayed response) changes across 600 simulations. Injury metrics were most sensitive to the loading direction (50%, partial-R²) and least sensitive to muscle size changes (0.2%). The pulse magnitude also had significant effect on the injury metrics (16%), whereas muscle responsiveness (3%) and pulse rise time (2%) had only slight effects. Frontal and upward loading directions were the worst for neck, spine, and lower extremity injury metrics, whereas rear and downward directions were the worst for head injury metrics. Higher magnitude pulses and pre-bracing also increased the injury risk.

Effect of Active Muscles on Astronaut Kinematics and Injury Risk for Piloted Lunar Landing and Launch While Standing

While astronauts may pilot future lunar landers in a standing posture, the response of the human body under lunar launch and landing-related dynamic loading conditions is not well understood. It is important to consider the effects of active muscles under these loading conditions as muscles stabilize posture while standing. In the present study, astronaut response for a piloted lunar mission in a standing posture was simulated using an active human body model (HBM) with a closed-loop joint-angle based proportional integral derivative controller muscle activation strategy and compared with a passive HBM to understand the effects of active muscles on astronaut body kinematics and injury risk. While head, neck, and lumbar spine injury risk were relatively unaffected by active muscles, the lower extremity injury risk and the head and arm kinematics were significantly changed. Active muscle prevented knee-buckling and spinal slouching and lowered tibia injury risk in the active vs. passive model (revised tibia index: 0.02-0.40 vs. 0.01-0.58; acceptable tolerance: 0.43). Head displacement was higher in the active vs. passive model (11.6 vs. 9.0 cm forward, 6.3 vs. 7.0 cm backward, 7.9 vs. 7.3 cm downward, 3.7 vs. 2.4 cm lateral). Lower arm movement was seen with the active vs. passive model (23 vs. 35 cm backward, 12 vs. 20 cm downward). Overall simulations suggest that the passive model may overpredict injury risk in astronauts for spaceflight loading conditions, which can be improved using the model with active musculature.

Implementation and calibration of active small female and average male human body models using low-speed frontal sled tests

OBJECTIVE

The objective of this study was to implement active muscles in a computationally efficient small female finite element model (54.1 kg, 149.9 cm) suitable for predicting occupant response during precrash braking and low-speed frontal sled tests. We further calibrate and compare its results against an average male model (78.4 kg, 174.9 cm) using the same developmental approach.

METHODS

The active female model (F05-OS + Active) was developed by adding active skeletal muscle elements (n = 232) to the Global Human Body Models Consortium (GHBMC) 5th percentile female simplified occupant model (F05-OS v2.3). The muscle properties and physiological cross-sectional area (PCSA) for each muscle were taken from the M50-OS + Active v2.3 model but PCSAs were mass scaled to a 5th percentile female. A total of 8 simulations were conducted; 2 acceleration pulses (1.0 g and 2.5 g), 2 models (F05-OS + Active and M50-OS + Active), and 2 muscle states (activation and control; e.g., no activation). Each model's kinematics and reaction forces were compared with experimental data. Occupant responses of 6 5th percentile female and 6 50th percentile male volunteers (n = 12 total) were used. The data depict occupant response in precrash braking and low-speed frontal sled tests in a rigid test buck. All procedures were reviewed and approved by the Virginia Tech institutional review board. Each volunteer was in a relaxed state before the applied acceleration.

RESULTS

The occupant peak forward excursion results of both active models reasonably match the volunteer data for both pulse severities. The differences between active and control models were found to be significant by Wilcoxon signed-rank test (p < .05). The reaction loads of the active and control models lie within the experimental corridors.

CONCLUSIONS

To the authors' knowledge, this study is the first to concurrently calibrate and compare equivalently developed computational models of females and males in precrash and low-speed impacts. The modeling approach is capable of capturing the varied kinematics observed in the relaxed condition, which may be an important factor in studies focused on the effects of low-g vehicle dynamics on the occupant position. Finally, the computationally efficient modeling approach is imperative given the long duration (>500 ms) of the events simulated.

Evaluation of muscle strain injury severity in active human body models

Even though significant efforts in the field of injury detection with finite element active human body models (FE AHBMs) have been made, injuries of the muscle-tendon unit (MTU) have not yet been taken into consideration. Therefore, the goal of this study was to define a muscle strain injury criterion (MSIC) to evaluate the damage sustained by the musculature during muscle driven movement scenarios. The MSIC was derived from biomechanical tests found in the literature and the proposed threshold values were substantiated through a comparison to an estimate of the ultimate tensile strength of human skeletal muscle and the forces acting on the biceps femoris long head muscle during one sprinting gait cycle. The application of the MSIC to state-of-the-art FE AHBMs was demonstrated by evaluating the strain injury severity of selected neck muscles of a full-body AHBM during two seat rotation load cases. The results of the MSIC substantiation suggest that all three injury threshold values proposed in this work fall in a plausible corridor of forces acting on the MTU. The combined results of the AHBM simulations indicate that neither of the two examined seat rotations are likely to cause strain injury to the neck muscles and that the proposed MSIC can easily be applied to current AHBMs without further modification of the model architecture or the muscle parameters. The MSIC was also used to formulate a hypothesis on the aetiology of muscle strain injuries, through which it was demonstrated that material inhomogeneities in the MTU might be the cause for strain injuries sustained during otherwise physiological movements. This work is a first step in the direction of the definition of a wholistic injury criterion for the human skeletal muscle fibre.

Analysis of control strategies for VIVA OpenHBM with active reflexive neck muscles

Modeling muscle activity in the neck muscles of a finite element (FE) human body model can be based on two biological reflex systems. One approach is to approximate the Vestibulocollic reflex (VCR) function, which maintains the head orientation relative to a fixed reference in space. The second system tries to maintain the head posture relative to the torso, similar to the Cervicocolic reflex (CCR). Strategies to combine these two neck muscle controller approaches in a single head-neck FE model were tested, optimized, and compared to rear-impact volunteer data. The first approach, Combined-Control, assumed that both controllers simultaneously controlled all neck muscle activations. In the second approach, Distributed-Control, one controller was used to regulate activation of the superficial muscles while a different controller acted on deep neck muscles. The results showed that any muscle controller that combined the two approaches was less effective than only using one of VCR- or CCR-based systems on its own. A passive model had the best objective rating for cervical spine kinematics, but the addition of a single active controller provided the best response for both head and cervical spine kinematics. The present study demonstrates the difficulty in completely capturing representative head and cervical spine responses to rear-impact loading and identified a controller capturing the VCR reflex as the best candidate to investigate whiplash injury mechanisms through FE modeling.

‘Falling heads’: investigating reflexive responses to head–neck perturbations

Background

Reflexive responses to head–neck perturbations affect the injury risk in many different situations ranging from sports-related impact to car accident scenarios. Although several experiments have been conducted to investigate these head–neck responses to various perturbations, it is still unclear why and how individuals react differently and what the implications of these different responses across subjects on the potential injuries might be. Therefore, we see a need for both experimental data and biophysically valid computational Human Body Models with bio-inspired muscle control strategies to understand individual reflex responses better.

Methods

To address this issue, we conducted perturbation experiments of the head–neck complex and used this data to examine control strategies in a simulation model. In the experiments, which we call ’falling heads’ experiments, volunteers were placed in a supine and a prone position on a table with an additional trapdoor supporting the head. This trapdoor was suddenly released, leading to a free-fall movement of the head until reflexive responses of muscles stopped the downwards movement.

Results

We analysed the kinematic, neuronal and dynamic responses for all individuals and show their differences for separate age and sex groups. We show that these results can be used to validate two simple reflex controllers which are able to predict human biophysical movement and modulate the response necessary to represent a large variability of participants.

Conclusions

We present characteristic parameters such as joint stiffness, peak accelerations and latency times. Based on this data, we show that there is a large difference in the individual reflexive responses between participants. Furthermore, we show that the perturbation direction (supine vs. prone) significantly influences the measured kinematic quantities. Finally, ’falling heads’ experiments data are provided open-source to be used as a benchmark test to compare different muscle control strategies and to validate existing active Human Body Models directly.

Dynamic Spatial Tuning Patterns of Shoulder Muscles with Volunteers in a Driving Posture

Computational human body models (HBMs) of drivers for pre-crash simulations need active shoulder muscle control, and volunteer data are lacking. The goal of this paper was to build shoulder muscle dynamic spatial tuning patterns, with a secondary focus to present shoulder kinematic evaluation data. 8M and 9F volunteers sat in a driver posture, with their torso restrained, and were exposed to upper arm dynamic perturbations in eight directions perpendicular to the humerus. A dropping 8-kg weight connected to the elbow through pulleys applied the loads; the exact timing and direction were unknown. Activity in 11 shoulder muscles was measured using surface electrodes, and upper arm kinematics were measured with three cameras. We found directionally specific muscle activity and presented dynamic spatial tuning patterns for each muscle separated by sex. The preferred directions, i.e. the vector mean of a spatial tuning pattern, were similar between males and females, with the largest difference of 31° in the pectoralis major muscle. Males and females had similar elbow displacements. The maxima of elbow displacements in the loading plane for males was 189 ± 36 mm during flexion loading, and for females, it was 196 ± 36 mm during adduction loading. The data presented here can be used to design shoulder muscle controllers for HBMs and evaluate the performance of shoulder models.

Potential effect of pre-activated muscles under a far-side lateral impact

OBJECTIVE

The goal of this study is to evaluate the potential effect of muscle pre-activation under a lateral impact scenario, in this case focusing on a far-side impact, using an Active Human Body Model.

METHODS

In total fourteen simulations were run, out of these, twelve were computed with an Active Human Body Model and two with a passive one. The models were subjected to a far-side impact scenario reaching up to 14 g's. Two different pre-crash scenarios were analyzed with the Active Human Body Model: (1) constant velocity, and (2) braking deceleration. During the pre-crash phase a lambda control based on the muscle length computed the muscle activation. Since there is no available data concerning the neuromuscular strategy of the occupants subjected to high accelerations, six different control strategies were analyzed during the in-crash phase. Besides, rib fracture and brain injury risk were analyzed, since they are the two most relevant body regions in this simplified far-side crash scenario.

RESULTS

The pre-activation of the muscles showed an effect on both the occupant kinematics and estimated injury risks. Depending on the considered muscle strategy, the head lateral excursion varied up to 75 mm, specifically for the scenario with constant velocity. Moreover, the rib fracture probability and the brain injury indicator revealed higher injury risks for the passive Human Body Model. When applying the constant velocity during pre-crash, the fracture probability for two or more ribs ranged from 9.91 to 46.06% for the Active Human Body Model, whereas it reached 84.3% for the passive model. The brain injury indicator was reduced by about 10% when using the active model compared to the passive one.

CONCLUSIONS

The numerical results show that the pre-activation of the muscles affects the kinematic and injury outcomes in car crashes. In this study, six muscular control strategies have been proposed. The two muscular controls that may be most realistic are: constant activation after the in-crash phase starts, by trying to hold the position prior to the crash, or no stimulation, by not responding to the upcoming in-crash event.

Trunk Skeletal Muscle Changes on CT with Long-Duration Spaceflight

Astronauts exposed to microgravity for extended time are susceptible to trunk muscle atrophy, which may compromise strength and function on mission and after return. This study investigates changes in trunk skeletal muscle size and composition using computed tomography (CT) and dual-energy X-ray absorptiometry (DXA) among 16 crewmembers (1 female, 15 male) on 4-6 month missions. Muscle cross-sectional area and muscle attenuation were measured using abdominal CT scans at pre-flight, post-flight return, 1 year post-flight, and 2-4 years post-flight. Longitudinal muscle changes were analyzed using mixed models. In six crewmembers, CT and DXA data were used to calculate subject height-normalized skeletal muscle indices. Changes in these indices were analyzed using paired t-tests and compared by imaging modality using Pearson correlations. Trunk muscle area decreased at post-flight return (- 4.7 ± 1.1%, p < 0.001) and recovered to pre-flight values at 1-4 years post-flight. Muscle attenuation changes were not significant. Skeletal muscle index from CT decreased (- 5.2 ± 1.0%, p = 0.004) while appendicular skeletal muscle index from DXA did not change significantly. In summary, trunk muscle atrophies with long-duration microgravity exposure but recovers to pre-flight values within 1-4 years. The CT measures highlight size decreases not detected with DXA, emphasizing the importance of advanced imaging modalities in assessing muscle health with spaceflight.

Multibody Models for the Analysis of a Fall From Height: Accident, Suicide, or Murder?

The final subject position is often the only evidence in the case of the fall of a human being from a given height. Foreseeing the body trajectory and the respective driving force may not be trivial due to the possibility of rotations and to an unknown initial position and momentum of the subject. This article illustrates how multibody models can be used for this aim, with specific reference to an actual case, where a worker fell into a stair well, prior to stair mounting, and he was found in an unexpected posture. The aim of the analysis was establishing if this worker was dead in that same place, if he had been pushed, and which was his initial position. A multibody model of the subject has been built ("numerical android"), given his stature and his known mass. Multiple simulations have been performed, following a design of experiments where various initial positions and velocity as well as pushing forces have been considered, while the objective function to be minimized was the deviation of the numerical android position from the actual worker position. At the end of the analysis, it was possible to point how a very limited set of conditions, all including the application of an external pushing force (or initial speed), could produce the given final posture with an error on the distance function equal to 0.39 m. The full analysis gives a demonstration of the potentiality of multibody models as a tool for the analysis of falls in forensic inquiries.