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

Abstract

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.

Using muscle-tendon load limits to assess unphysiological musculoskeletal model deformation and Hill-type muscle parameter choice

“…Additionally, it consists of distinct muscle and tendon sections, which can be individually evaluated for injury with the MSIC and the TSIC. This Hill-type muscle material was initially implemented in LS-DYNA as the so-called extended Hill-type muscle (EHTM) material model by Kleinbach et al [54] and has since been updated by Wochner et al [55] and Martynenko et al [56]. In our current study, the functionality of the EHTM was further expanded by adding an inbuilt strain injury assessment functionality using the MSIC and TSIC.…”

“…In both arms, musculus brachialis, musculus biceps brachii (long and short head), musculus brachioradialis, musculus triceps brachii (long, lateral, and medial head), musculus anconeus and musculus pronator teres were replaced, resulting in 18 total material changes in the THUMS model. The original *MAT_MUSCLE material parameters were converted for the use with the EHTM using the methodology described in Wochner et al [55] and Nölle et al [57]. A list of all edited muscles and their material parameters is given in S-Table 1 and S-Table 2 in S1 File.…”

“…The FE repositioning simulation was performed using the THUMS AM50 occupant model version 5.03 [44]. Seat, steering wheel and pedals were taken from the openly available THUMS version [55] and Martynenko et al [56]. In our current study, the functionality of the EHTM was further expanded by adding an inbuilt strain injury assessment functionality using the MSIC and TSIC.…”

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

“…To allow for a better assessment of tendon strain injury severity, *MAT_MUSCLE was replaced with a more biophysiological Hill-type muscle material developed by ( Günther et al, 2007 ) and Haeufle et al ( Haeufle et al, 2014 ), which is available in LS-DYNA as a user-defined material named the extended Hill-type material (EHTM). The EHTM was initially implemented in LS-DYNA by Kleinbach et al ( Kleinbach et al, 2017 ) and updated to its most current version by Kleinbach et al ( Kleinbach, 2019 ), Martynenko et al ( Martynenko et al, 2023 ) and Wochner et al ( Wochner et al, 2022 ). Compared to *MAT_MUSCLE, the EHTM material has the additional benefit of including the tendon as a distinct element called the serial elastic element (SEE) ( Haeufle et al, 2014 ), eliminating the need for combining muscle and seatbelt elements to form the MTU.…”

“…Additionally, the Young’s modulus was calculated from the linear parts of the resulting curves. All other non-generic muscle parameters of the EHTM were derived by converting the parameters of *MAT_MUSCLE with an adapted version of the method presented in the EHTM manual ( Nölle et al, 2022a ) and the work of Wochner et al ( Wochner et al, 2022 ). The aim of this method is to achieve a length equilibrium state during the initial simulation timestep in which the following condition holds true (Eq.…”