Mechanical Fatigue of Bovine Cortical Bone Using Ground Reaction Force Waveforms in Running

Tibial strains are sensitive to speed perturbations, but not grade perturbations, during running

A fatigue-failure process is hypothesized to govern the development of tibial stress fractures, where bone damage is highly dependent on the peak strain magnitude. To date, much of the work examining tibial strain during running has ignored uphill and downhill running despite the prevalence of this terrain. This study examined the sensitivity of tibial strain to changes in running grade and speed using a combined musculoskeletal-finite element modelling routine. Seventeen participants ran on a treadmill at ±10, ±5 and 0 deg; at each grade, participants ran at 3.33 m s-1 and at a grade-adjusted speed of 2.50 and 4.17 m s-1 for uphill and downhill grades, respectively. Force and motion data were recorded in each grade and speed combination. Muscle and joint contact forces were estimated using inverse-dynamics-based static optimization. These forces were applied to a participant-adjusted finite element model of the tibia. None of the strain variables (50th and 95th percentile strain and strained volume ≥4000 με) differed as a function of running grade; however, all strain variables were sensitive to running speed (F1≥9.59, P≤0.03). In particular, a 1 m s-1 increase in speed resulted in a 9% (∼260 με) and 155% (∼600 mm3) increase in peak strain and strained volume, respectively. Overall, these findings suggest that faster running speeds, but not changes in running grade, may be more deleterious to the tibia.

Learning effects in over-ground running gait retraining: A six-month follow-up of a quasi-randomized controlled trial

This study evaluated learning and recall effects following a feedback-based retraining program. A 6-month follow-up of a quasi-randomized controlled trial was performed with and without recall. Twenty runners were assigned to experimental or control groups and completed a 3-week running program. A body-worn system collected axial tibial acceleration and provided real-time feedback on peak tibial acceleration for six running sessions in an athletic training facility. The experimental group received music-based biofeedback in a faded feedback scheme. The controls received tempo-synchronized music as a placebo for blinding purposes. The peak tibial acceleration and vertical loading rate of the ground reaction force were determined in a lab at baseline and six months following the intervention to assess retention and recall. The impacts of the experimental group substantially decreased at follow-up following a simple verbal recall (i.e., run as at the end of the program): peak tibial acceleration:-32%, p = 0.018; vertical loading rate:-34%, p = 0.006. No statistically significant changes were found regarding the retention of the impact variables. The impact magnitudes did not change over time in the control group. The biofeedback-based intervention did not induce clear learning at follow-up, however, a substantial impact reduction was recallable through simple cueing in the absence of biofeedback.

Speed and surface steepness affect internal tibial loading during running

BACKGROUND

Internal tibial loading is influenced by modifiable factors with implications for the risk of stress injury. Runners encounter varied surface steepness (gradients) when running outdoors and may adapt their speed according to the gradient. This study aimed to quantify tibial bending moments and stress at the anterior and posterior peripheries when running at different speeds on surfaces of different gradients.

METHODS

Twenty recreational runners ran on a treadmill at 3 different speeds (2.5 m/s, 3.0 m/s, and 3.5 m/s) and gradients (level: 0%; uphill: +5%, +10%, and +15%; downhill: -5%, -10%, and -15%). Force and marker data were collected synchronously throughout. Bending moments were estimated at the distal third centroid of the tibia about the medial-lateral axis by ensuring static equilibrium at each 1% of stance. Stress was derived from bending moments at the anterior and posterior peripheries by modeling the tibia as a hollow ellipse. Two-way repeated-measures analysis of variance were conducted using both functional and discrete statistical analyses.

RESULTS

There were significant main effects for running speed and gradient on peak bending moments and peak anterior and posterior stress. Higher running speeds resulted in greater tibial loading. Running uphill at +10% and +15% resulted in greater tibial loading than level running. Running downhill at -10% and -15% resulted in reduced tibial loading compared to level running. There was no difference between +5% or -5% and level running.

CONCLUSION

Running at faster speeds and uphill on gradients ≥+10% increased internal tibial loading, whereas slower running and downhill running on gradients ≥-10% reduced internal loading. Adapting running speed according to the gradient could be a protective mechanism, providing runners with a strategy to minimize the risk of tibial stress injuries.

Effect of increased running speed and weight carriage on peak and cumulative tibial loading

INTRODUCTION

Tibial stress injuries are a burdensome injury among military recruits. Military activities include running and the carriage of additional weight, and this may be related to the high risk of bone stress injuries. The aim of this study was to quantify tibial loading when running at two different speeds, with and without additional weight, and to quantify their combined influence.

METHODS

Fourteen male distance runners who ran at least 40 km per week ran barefoot on a force-instrumented treadmill in four conditions representing preferred running speed (mean (SD) 3.1 (0.3) m/s) and 20% increased running speed (3.8 (0.4) m/s), with and without 20% of body weight carried in a weight vest. Kinematics and kinetics were synchronously collected. Bending moments were estimated about the medial-lateral axis of the tibial centroid located 1/3rd of the length from distal to proximal. Static equilibrium was ensured at each 1% of stance. Peak bending moments were obtained in addition to cumulative-weighted loading, where weighted loading accounted for the relative importance of the magnitude of the bending moment and the quantity of loading using a bone-dependent weighting factor.

RESULTS

There were no interaction effects for running speed and weight carriage on peak or cumulative tibial loading. Running at a 20% faster speed increased peak and cumulative loading per kilometer by 8.0% (p < 0.001) and 4.8% (p < 0.001), respectively. Carriage of an additional 20% of body weight increased peak and cumulative loading per kilometer by 6.6% (p < 0.001) and 8.5% (p < 0.001), respectively.

INTERPRETATION

Increasing the physical demand of running by increasing speed or weight carriage increased peak tibial loading and cumulative tibial loading per kilometer, and this may increase the risk of tibial stress injury. Running speed and weight carriage independently influenced tibial loading.

Low-intensity pulsed ultrasound enhances the positive effects of high-intensity treadmill exercise on bone in rats

INTRODUCTION

Moderate exercise benefits bone health, but excessive loading leads to bone fatigue and a decline in mechanical properties. Low-intensity pulsed ultrasound (LIPUS) can stimulate bone formation. The purpose of this study was to explore whether LIPUS could augment the skeletal benefits of high-intensity exercise.

MATERIALS AND METHODS

MC3T3-E1 osteoblasts were treated with LIPUS at 80 mW/cm2 or 30 mW/cm2 for 20 min/day. Forty rats were divided into sham treatment normal control (Sham-NC), sham treatment high-intensity exercise (Sham-HIE), 80 mW/cm2 LIPUS (LIPUS80), and high-intensity exercise combined with 80 mW/cm2 LIPUS (LIPUS80-HIE). The rats in HIE group were subjected to 30 m/min slope treadmill exercise for 90 min/day, 6 days/week for 12 weeks. The LIPUS80-HIE rats were irradiated with LIPUS (1 MHz, 80 mW/cm2) for 20 min/day at bilateral hind limb after exercise.

RESULTS

LIPUS significantly accelerated the proliferation, differentiation, mineralization, and migration of MC3T3-E1 cells. Compared to 30 mW/cm2 LIPUS, 80 mW/cm2 LIPUS got better promotion effect. 12 weeks of high-intensity exercise significantly reduced the muscle force, which was significantly reversed by LIPUS. Compared with the Sham-NC group, Sham-HIE group significantly optimized bone microstructure and enhanced mechanical properties of femur, and LIPUS80-HIE further enhanced the improvement effect on bone. The mechanisms may be related to activate Wnt/β-catenin signal pathway and then up-regulate the protein expression of Runx2 and VEGF, the key factors of osteogenesis and angiogenesis.

CONCLUSION

LIPUS could augment the skeletal benefits of high-intensity exercise through Wnt/β-catenin signal pathway.

A continuum damage model of fatigue and failure in whole bone

Predicting the fatigue failure of whole bone may provide insight into the etiology of stress fractures and lead to new methods for preventing and rehabilitating these injuries. Although finite element (FE) models of whole bone have been used to predict fatigue failure, they often do not consider the cumulative and nonlinear effect of fatigue damage, which causes stress redistribution over many loading cycles. The purpose of this study was to develop and validate a continuum damage mechanics FE model for the prediction of fatigue damage and failure. Sixteen whole rabbit-tibiae were imaged using computed tomography (CT) and then cyclically loaded in uniaxial compression until failure. CT images were used to generate specimen-specific FE models and a custom program was developed to iteratively simulate cyclic loading and progressive modulus degradation associated with mechanical fatigue. Four tibiae from the experimental tests were used to develop a suitable damage model and define a failure criterion; the remaining twelve tibiae were used to test the validity of the continuum damage mechanics model. Fatigue-life predictions explained 71% of the variation in experimental fatigue-life measurements with a directional bias towards over-predicting fatigue-life in the low-cycle regime. These findings demonstrate the efficacy of using FE modeling with continuum damage mechanics to predict damage evolution and fatigue failure of whole bone. Through further refinement and validation, this model may be used to investigate different mechanical factors that influence the risk of stress fractures in humans.

The "impacts cause injury" hypothesis: Running in circles or making new strides?

Some of the earliest biomechanics research focused on running and the ground reaction forces generated with each step. Research in running gait accelerated in the 1970's as the growing popularity in running increased attention to the musculoskeletal injuries sustained by runners. Despite decades of high-quality research, running remains the most common cause of exercise-related musculoskeletal injuries and rates of overuse running-related injuries (RRI) have not appreciably declined since the research began. One leading area of running gait research focuses on discrete variables derived from the vertical ground reaction force, such as the vertical loading rate. Across sub-disciplines of running gait research, vertical loading rate is often discussed as the primary and undisputed variable associated with RRI despite only low to moderate evidence that retrospectively or prospectively injured runners generate greater vertical loading rates than uninjured counterparts. The central thesis of this review is that relying on vertical loading rate is insufficient to establish causal mechanisms for RRI etiology. To present this argument, this review examines the history of the 'impacts cause injury' hypothesis, including a historical look at ground reaction forces in human running and the research from which this hypothesis was generated. Additionally, a synthesis of studies that have tested the hypothesis is provided and recommendations for future research are discussed. Although it is premature to reject or support the 'impacts cause injury' hypothesis, new knowledge of biomechanical risk factors for RRI will remain concealed until research departs from the current path or adopts new approaches to previous paradigms.

Perspectives from research and practice: A survey on external load monitoring and bone in sport

Introduction

There is limited information regarding the association between external load and estimated bone load in sport, which may be important due to the influence exercise can have on bone accrual and injury risk. The aim of this study was to identify external load measuring tools used by support staff to estimate bone load and assess if these methodologies were supported in research.

Methods

A survey was comprised of 19 multiple choice questions and the option to elaborate on if/how they monitor external load and if/how they used them to estimate bone load. A narrative review was performed to assess how external load is associated to bone in research.

Results

Participants were required to be working as support staff in applied sport. Support staff (n = 71) were recruited worldwide with the majority (85%) working with professional elite athletes. 92% of support staff monitored external load in their organisation, but only 28% used it to estimate bone load.

Discussion

GPS is the most commonly used method to estimate bone load, but there is a lack of research assessing GPS metrics with bone load. Accelerometry and force plates were among the most prevalent methods used to assess external load, but a lack of bone specific measurements were reported by support staff. Further research exploring how external load relates to bone is needed as there is no consensus on which method of external load is best to estimate bone load in an applied setting.

Peak tibial acceleration should not be used as indicator of tibial bone loading during running

Peak tibial acceleration (PTA) is a widely used indicator of tibial bone loading. Indirect bone loading measures are of interest to reduce the risk of stress fractures during running. However, tibial compressive forces are caused by both internal muscle forces and external ground reaction forces. PTA might reflect forces from outside the body, but likely not the compressive force from muscles on the tibial bone. Hence, the strength of the relationship between PTA and maximum tibial compression forces in rearfoot-striking runners was investigated. Twelve runners ran on an instrumented treadmill while tibial acceleration was captured with accelerometers. Force plate and inertial measurement unit data were spatially aligned with a novel method based on the centre of pressure crossing a virtual toe marker. The correlation coefficient between maximum tibial compression forces and PTA was 0.04 ± 0.14 with a range of -0.15 to +0.28. This study showed a very weak and non-significant correlation between PTA and maximum tibial compression forces while running on a level treadmill at a single speed. Hence, PTA as an indicator for tibial bone loading should be reconsidered, as PTA does not provide a complete picture of both internal and external compressive forces on the tibial bone.  .

Preventing Bone Stress Injuries in Runners with Optimal Workload

Bone stress injuries (BSIs) occur at inopportune times to invariably interrupt training. All BSIs in runners occur due to an "error" in workload wherein the interaction between the number and magnitude of bone tissue loading cycles exceeds the ability of the tissue to resist the repetitive loads. There is not a single optimal bone workload, rather a range which is influenced by the prevailing scenario. In prepubertal athletes, optimal bone workload consists of low-repetitions of fast, high-magnitude, multidirectional loads introduced a few times per day to induce bone adaptation. Premature sports specialization should be avoided so as to develop a robust skeleton that is structurally optimized to withstand multidirectional loading. In the mature skeleton, optimal workload enables gains in running performance but minimizes bone damage accumulation by sensibly progressing training, particularly training intensity. When indicated (e.g., following repeated BSIs), attempts to reduce bone loading magnitude should be considered, such as increasing running cadence. Determining the optimal bone workload for an individual athlete to prevent and manage BSIs requires consistent monitoring. In the future, it may be possible to clinically determine bone loads at the tissue level to facilitate workload progressions and prescriptions.

Lower step rate is associated with a higher risk of bone stress injury: a prospective study of collegiate cross country runners

OBJECTIVES

To determine if running biomechanics and bone mineral density (BMD) were independently associated with bone stress injury (BSI) in a cohort of National Collegiate Athletic Association Division I cross country runners.

METHODS

This was a prospective, observational study of 54 healthy collegiate cross country runners over three consecutive seasons. Whole body kinematics, ground reaction forces (GRFs) and BMD measures were collected during the preseason over 3 years via motion capture on an instrumented treadmill and total body densitometer scans. All medically diagnosed BSIs up to 12 months following preseason data collection were recorded. Generalised estimating equations were used to identify independent risk factors of BSI.

RESULTS

Univariably, step rate, centre of mass vertical excursion, peak vertical GRF and vertical GRF impulse were associated with BSI incidence. After adjusting for history of BSI and sex in a multivariable model, a higher step rate was independently associated with a decreased risk of BSI. BSI risk decreased by 5% (relative risk (RR): 0.95; 95% CI 0.91 to 0.98) with each one step/min increase in step rate. BMD z-score was not a statistically significant risk predictor in the final multivariable model (RR: 0.93, 95% CI 0.85 to 1.03). No other biomechanical variables were found to be associated with BSI risk.

CONCLUSION

Low step rate is an important risk factor for BSI among collegiate cross country runners and should be considered when developing comprehensive programmes to mitigate BSI risk in distance runners.

Sacral acceleration can predict whole-body kinetics and stride kinematics across running speeds

Background

Stress fractures are injuries caused by repetitive loading during activities such as running. The application of advanced analytical methods such as machine learning to data from multiple wearable sensors has allowed for predictions of biomechanical variables associated with running-related injuries like stress fractures. However, it is unclear if data from a single wearable sensor can accurately estimate variables that characterize external loading during running such as peak vertical ground reaction force (vGRF), vertical impulse, and ground contact time. Predicting these biomechanical variables with a single wearable sensor could allow researchers, clinicians, and coaches to longitudinally monitor biomechanical running-related injury risk factors without expensive force-measuring equipment.

Purpose

We quantified the accuracy of applying quantile regression forest (QRF) and linear regression (LR) models to sacral-mounted accelerometer data to predict peak vGRF, vertical impulse, and ground contact time across a range of running speeds.

Methods

Thirty-seven collegiate cross country runners (24 females, 13 males) ran on a force-measuring treadmill at 3.8-5.4 m/s while wearing an accelerometer clipped posteriorly to the waistband of their running shorts. We cross-validated QRF and LR models by training them on acceleration data, running speed, step frequency, and body mass as predictor variables. Trained models were then used to predict peak vGRF, vertical impulse, and contact time. We compared predicted values to those calculated from a force-measuring treadmill on a subset of data (n = 9) withheld during model training. We quantified prediction accuracy by calculating the root mean square error (RMSE) and mean absolute percentage error (MAPE).

Results

The QRF model predicted peak vGRF with a RMSE of 0.150 body weights (BW) and MAPE of 4.27  ±  2.85%, predicted vertical impulse with a RMSE of 0.004 BW*s and MAPE of 0.80  ±  0.91%, and predicted contact time with a RMSE of 0.011 s and MAPE of 4.68  ±  3.00%. The LR model predicted peak vGRF with a RMSE of 0.139 BW and MAPE of 4.04  ±  2.57%, predicted vertical impulse with a RMSE of 0.002 BW*s and MAPE of 0.50  ±  0.42%, and predicted contact time with a RMSE of 0.008 s and MAPE of 3.50  ±  2.27%. There were no statistically significant differences between QRF and LR model prediction MAPE for peak vGRF (p = 0.549) or vertical impulse (p = 0.073), but the LR model's MAPE for contact time was significantly lower than the QRF model's MAPE (p = 0.0497).

Conclusions

Our findings indicate that the QRF and LR models can accurately predict peak vGRF, vertical impulse, and contact time (MAPE < 5%) from a single sacral-mounted accelerometer across a range of running speeds. These findings may be beneficial for researchers, clinicians, or coaches seeking to monitor running-related injury risk factors without force-measuring equipment.

Stressed volume estimated by finite element analysis predicts the fatigue life of human cortical bone: The role of vascular canals as stress concentrators

The fatigue life of cortical bone can vary several orders of magnitude, even in identical loading conditions. A portion of this variability is likely related to intracortical microarchitecture and the role of vascular canals as stress concentrators. The size, spatial distribution, and density of canals determine the peak magnitude and volume of stress concentrations. This study utilized a combination of experimental fatigue testing and image-based finite element (FE) analysis to establish the relationship between the stressed volume (i.e., volume of bone above yield stress) associated with vascular canals and the fatigue life of cortical bone. Thirty-six cortical bone samples were prepared from human femora and tibiae from five donors. Samples were allocated to four loading groups, corresponding to stress ranges of 60, 70, 80, and 90 MPa, then cyclically loaded in zero-compression until fracture. Porosity, canal diameter, canal separation, and canal number for each sample was quantified using X-ray microscopy (XRM) after testing. FE models were created from XRM images and used to calculate the stressed volume. Stressed volume was a good predictor of fatigue life, accounting for 67% of the scatter in fatigue-life measurements. An increase in stressed volume was most strongly associated with higher levels of intracortical porosity and larger canal diameters. The findings from this study suggest that a large portion of the fatigue-life variance of cortical bone in zero-compression is driven by intracortical microarchitecture, and that fatigue failure may be predicted by quantifying the stress concentrations associated with vascular canals.

Training Load and Injury: Causal Pathways and Future Directions

Causal pathways between training loads and the mechanisms of tissue damage and athletic injury are poorly understood. Here, the relation between specific training load measures and metrics, and causal pathways of gradual onset and traumatic injury are examined. Currently, a wide variety of internal and external training load measures and metrics exist, with many of these being commonly utilized to evaluate injury risk. These measures and metrics can conceptually be related to athletic injury through the mechanical load-response pathway, the psycho-physiological load-response pathway, or both. However, the contributions of these pathways to injury vary. Importantly, tissue fatigue damage and trauma through the mechanical load-response pathway is poorly understood. Furthermore, considerable challenges in quantifying this pathway exist within applied settings, evidenced by a notable absence of validation between current training load measures and tissue-level mechanical loads. Within this context, the accurate quantification of mechanical loads holds considerable importance for the estimation of tissue damage and the development of more thorough understandings of injury risk. Despite internal load measures of psycho-physiological load speculatively being conceptually linked to athletic injury through training intensity and the effects of psycho-physiological fatigue, these measures are likely too far removed from injury causation to provide meaningful, reliable relationships with injury. Finally, we used a common training load metric as a case study to show how the absence of a sound conceptual rationale and spurious links to causal mechanisms can disclose the weaknesses of candidate measures as tools for altering the likelihood of injuries, aiding the future development of more refined injury risk assessment methods.

Combining wearable sensor signals, machine learning and biomechanics to estimate tibial bone force and damage during running

There are tremendous opportunities to advance science, clinical care, sports performance, and societal health if we are able to develop tools for monitoring musculoskeletal loading (e.g., forces on bones or muscles) outside the lab. While wearable sensors enable non-invasive monitoring of human movement in applied situations, current commercial wearables do not estimate tissue-level loading on structures inside the body. Here we explore the feasibility of using wearable sensors to estimate tibial bone force during running. First, we used lab-based data and musculoskeletal modeling to estimate tibial force for ten participants running across a range of speeds and slopes. Next, we converted lab-based data to signals feasibly measured with wearables (inertial measurement units on the foot and shank, and pressure-sensing insoles) and used these data to develop two multi-sensor algorithms for estimating peak tibial force: one physics-based and one machine learning. Additionally, to reflect current running wearables that utilize running impact metrics to infer musculoskeletal loading or injury risk, we estimated tibial force using a commonly measured impact metric, the ground reaction force vertical average loading rate (VALR). Using VALR to estimate peak tibial force resulted in a mean absolute percent error of 9.9%, which was no more accurate than a theoretical step counter that assumed the same peak force for every running stride. Our physics-based algorithm reduced error to 5.2%, and our machine learning algorithm reduced error to 2.6%. Further, to gain insights into how force estimation accuracy relates to overuse injury risk, we computed bone damage expected due to a given loading cycle. We found that modest errors in tibial force translated into large errors in bone damage estimates. For example, a 9.9% error in tibial force using VALR translated into 104% error in estimated bone damage. Encouragingly, the physics-based and machine learning algorithms reduced damage errors to 41% and 18%, respectively. This study highlights the exciting potential to combine wearables, musculoskeletal biomechanics and machine learning to develop more accurate tools for monitoring musculoskeletal loading in applied situations.

Association between intracortical microarchitecture and the compressive fatigue life of human bone: A pilot study

Many mechanical properties of cortical bone are largely governed by the underlying microarchitecture; however, the influence of microarchitecture on the fatigue life of bone is poorly understood. Furthermore, imaging-based studies investigating intracortical microarchitecture may expose bone samples to large doses of radiation that may compromise fatigue resistance. The purpose of this pilot study was to 1) investigate the relationship between intracortical microarchitecture and the fatigue life of human bone in compression and 2) examine the effects of synchrotron irradiation on fatigue life measurements. Cortical samples were prepared from the femoral and tibial shafts of three cadaveric donors. A subset of samples was imaged using synchrotron X-ray microCT to quantify microarchitecture, including porosity, canal diameter, lacunar density, lacunar volume, and lacunar orientation. A second group of control samples was not imaged and used only for mechanical testing. Fatigue life was quantified by cyclically loading both groups in zero-compression until failure. Increased porosity and larger canal diameter were both logarithmically related to a shorter fatigue life, whereas lacunar density demonstrated a positive linear relationship with fatigue life (r² = 45–73%, depending on measure). Irradiation from microCT scanning reduced fatigue life measurements by 91%, but relationships with microarchitecture measurements remained. Additional research is needed to support the findings of this pilot study and fully establish the relationship between intracortical microarchitecture and the compressive fatigue life of bone.

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Increased porosity and larger canal diameters were associated with a shorter compressive fatigue life.

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A higher lacunar density was related to a longer compressive fatigue life.

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Irradiation from synchrotron X-ray microCT scanning reduced fatigue life by 91%.

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The influence of microarchitecture on fatigue life exhibited similar trends for both irradiated and non-irradiated bone.

Fatigue reliability analysis for medial tibial stress syndrome

Medial Tibial Stress Syndrome MTSS is frequently diagnosed as a severe clinical issue which occurs due to the cycle loadings (fatigue failure). Since the mechanical properties of the bones are random variables, therefore, there is a need for a probabilistic approach to rationally assess the reliability level of the fatigue failure of the tibia. The main contribution of this paper is to introduce a novel limit state function to determine the fatigue damage state and the reliability index of MTSS based on the different loading and aging conditions. In this study, the tibias of the several people at the different ages are subjected to the fatigue loadings. The load carrying capacities of the considered specimen are determined based on the reliability analysis. Indeed, several 3D finite element analyses are performed to find out the damage states of the tibias. Accordingly, the reliability-based stress analysis is accomplished to localize the most vulnerable zone of the bone. As it was expected, the higher loading cycles associated with the elder bones is related to the lowest fatigue reliability level. Finally, the target reliability level of MTSS is proposed to deliberate the safe level of the loading condition on the tibia in terms of the walking distance.

Ground reaction force metrics are not strongly correlated with tibial bone load when running across speeds and slopes: Implications for science, sport and wearable tech

INTRODUCTION

Tibial stress fractures are a common overuse injury resulting from the accumulation of bone microdamage due to repeated loading. Researchers and wearable device developers have sought to understand or predict stress fracture risks, and other injury risks, by monitoring the ground reaction force (GRF, the force between the foot and ground), or GRF correlates (e.g., tibial shock) captured via wearable sensors. Increases in GRF metrics are typically assumed to reflect increases in loading on internal biological structures (e.g., bones). The purpose of this study was to evaluate this assumption for running by testing if increases in GRF metrics were strongly correlated with increases in tibial compression force over a range of speeds and slopes.

METHODS

Ten healthy individuals performed running trials while we collected GRFs and kinematics. We assessed if commonly-used vertical GRF metrics (impact peak, loading rate, active peak, impulse) were strongly correlated with tibial load metrics (peak force, impulse).

RESULTS

On average, increases in GRF metrics were not strongly correlated with increases in tibial load metrics. For instance, correlating GRF impact peak and loading rate with peak tibial load resulted in r = -0.29±0.37 and r = -0.20±0.35 (inter-subject mean and standard deviation), respectively. We observed high inter-subject variability in correlations, though most coefficients were negligible, weak or moderate. Seventy-six of the 80 subject-specific correlation coefficients computed indicated that higher GRF metrics were not strongly correlated with higher tibial forces.

CONCLUSIONS

These results demonstrate that commonly-used GRF metrics can mislead our understanding of loading on internal structures, such as the tibia. Increases in GRF metrics should not be assumed to be an indicator of increases in tibial bone load or overuse injury risk during running. This has important implications for sports, wearable devices, and research on running-related injuries, affecting >50 scientific publications per year from 2015-2017.

Whole-body biomechanical load in running-based sports: The validity of estimating ground reaction forces from segmental accelerations

OBJECTIVES

Unlike physiological loads, the biomechanical loads of training in running-based sports are still largely unexplored. This study, therefore, aimed to assess the validity of estimating ground reaction forces (GRF), as a measure of external whole-body biomechanical loading, from segmental accelerations.

METHODS

Fifteen team-sport athletes performed accelerations, decelerations, 90° cuts and straight running at different speeds including sprinting. Full-body kinematics and GRF were recorded with a three-dimensional motion capture system and a single force platform respectively. GRF profiles were estimated as the sum of the product of all fifteen segmental masses and accelerations, or a reduced number of segments.

RESULTS

Errors for GRF profiles estimated from fifteen segmental accelerations were low (1-2Nkg^-1) for low-speed running, moderate (2-3Nkg^-1) for accelerations, 90° cuts and moderate-speed running, but very high (>4Nkg^-1) for decelerations and high-speed running. Similarly, impulse (2.3-11.1%), impact peak (9.2-28.5%) and loading rate (20.1-42.8%) errors varied across tasks. Moreover, mean errors increased from 3.26±1.72Nkg^-1 to 6.76±3.62Nkg^-1 across tasks when the number of segments was reduced.

CONCLUSIONS

Accuracy of estimated GRF profiles and loading characteristics was dependent on task, and errors substantially increased when the number of segments was reduced. Using a direct mechanical approach to estimate GRF from segmental accelerations is thus unlikely to be a valid method to assess whole-body biomechanical loading across different dynamic and high-intensity activities. Researchers and practitioners should, therefore, be very cautious when interpreting accelerations from one or several segments, as these are unlikely to accurately represent external whole-body biomechanical loads.