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Springboard diving training is often focused upon skill repetition to establish movement accuracy, stability and consistency. Within-participant study designs provide the ability to understand how individuals create these skills under different movement strategies. IMUs measured angular velocity time-series data of two athletes performing multiple repetitions of forward 3½ somersault pike dives. Functional Principal Component Analyses (fPCA) were performed to examine individual movement structure and variability. The first five fPC's represented approximately 98% of the variability in angular velocity for both divers. To determine the relative importance of angular velocity variability, Pearson's correlations for pairwise comparisons were used to assess the relationship between fPC scores and discrete performance variables during takeoff, flight and entry. Divers exhibited a different number and types of significant correlations (International = 4; National = 11). Only one correlation was common for both divers; higher angular velocity during Initial Flight and/or Somersault phases resulted in more vertically aligned entry posture (International: fPC1 r = −0.761, p < 0.05; National: fPC3 r = −0.796, p < 0.01). Findings identify individualised angular velocity time-series structure and kinematic performance variables (International = angular; National = linear) that can be used by coaching/sport science teams to optimisation performance success. [ABSTRACT FROM AUTHOR]

Research in sports biomechanics often relies on the use of ordinary least squares (OLS) regression. However, since sports biomechanics research is often characterised by high-dimensional data sets with many predictor variables and few observations, use of OLS regression can sometimes be problematic from a statistical perspective. Statistical learning methods may provide alternate ways to deal with high-dimensional data sets and partially address these problems. For example, regularisation adds penalties to the cost function of OLS regression models, which shrinks large regression coefficients and decreases the model’s sensitivity to noise in the data. Regularised regression models also protect against overfitting, improve generalisability, and can be used for variable selection. A short review of biomechanics research studies illustrates how these models provided ways to reduce the number of variables within a model and select only the primary predictors of performance, which helped with the interpretation of results and identified distinct combinations of key predictors of performance. In addition, we illustrate how these models are applied to two sports biomechanics datasets. Given the advantages, sports biomechanists may want to consider the use of regularised regression models in their research design and statistical analyses. Careful consideration should be given, however, to the construction, validation, and interpretation of these models considering their underpinning assumptions and limitations. [ABSTRACT FROM AUTHOR]

Hughes, S, Warmenhoven, J, Haff, GG, Chapman, DW, and Nimphius, S. Countermovement jump and squat jump force-time curve analysis in control and fatigue conditions. J Strength Cond Res 36(10): 2752–2761, 2022—This study aimed to reanalyze previously published discrete force data from countermovement jumps (CMJs) and squat jumps (SJs) using statistical parametric mapping (SPM), a statistical method that enables analysis of data in its native, complete state. Statistical parametric mapping analysis of 1-dimensional (1D) force-time curves was compared with previous zero-dimensional (0D) analysis of peak force to assess sensitivity of 1D analysis. Thirty-two subjects completed CMJs and SJs at baseline, 15 minutes, 1, 24, and 48 hours following fatigue and control conditions in a pseudo random cross-over design. Absolute (CMJABS/SJABS) and time-normalized (CMJNORM/SJNORM) force-time data were analyzed using SPM 2-way repeated measures analysis of variance with significance accepted at α = 0.05. The SPM indicated a magnitude of difference between force-time data with main effects for time (p < 0.001) and interaction (p < 0.001) observed in CMJABS, SJABS, and SJNORM, whereas previously published 0D analysis reported no 2-way interaction in CMJ and SJ peak force. This exploratory research demonstrates the strength of SPM to identify changes between entire movement force-time curves. Continued development and use of SPM analysis techniques could present the opportunity for refined assessment of athlete fatigue and readiness with the analysis of complete force-time curves. [ABSTRACT FROM AUTHOR]

Immunofluorescent tagging of DNA double-strand break (DSB) markers, such as γ-H2AX and other DSB repair proteins, are powerful tools in understanding biological consequences following irradiation. However, whilst the technique is widespread, there are many uncertainties related to its ability to resolve and reliably deduce the number of foci when counting using microscopy. We present a new tool for simulating radiation-induced foci in order to evaluate microscope performance within in silico immunofluorescent images. Simulations of the DSB distributions were generated using Monte Carlo track-structure simulation. For each DSB distribution, a corresponding DNA repair process was modelled and the un-repaired DSBs were recorded at several time points. Corresponding microscopy images for both a DSB and (γ-H2AX) fluorescent marker were generated and compared for different microscopes, radiation types and doses. Statistically significant differences in miscounting were found across most of the tested scenarios. These inconsistencies were propagated through to repair kinetics where there was a perceived change between radiation-types. These changes did not reflect the underlying repair rate and were caused by inconsistencies in foci counting. We conclude that these underlying uncertainties must be considered when analysing images of DNA damage markers to ensure differences observed are real and are not caused by non-systematic miscounting. PyFoci is a tool that simulates distributions of fluorescently labeled DNA double-strand break marker protein foci and allows the estimation of miscounting under different radiation types, doses and microscopy settings. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the motor control strategies employed to control the degrees of freedom when performing a lower limb task with constraints applied at the hip, knee, and ankle. Thirty-five individuals performed vertical jumping tasks: hip flexed, no knee bend, and plantar flexed. Joint moment data from the hip, knee, and ankle were analyzed using principal component analysis (PCA). In all PCA performed, a minimum of two and maximum of six principal components (PC) were required to describe the movements. Similar reductions in dimensionality were observed in the hip flexed and no knee bend conditions (3PCs), compared to the plantar flexed condition (5PCs). A proximal to distal reduction in variability was observed for the hip flexed and no knee bend conditions but not for the plantar flexed condition. Collectively, the results suggest a reduction in the dimensionality of the movement occurs despite the constraints imposed within each condition and would suggest that dimensionality reduction and motor control strategies are a function of the task demands. [ABSTRACT FROM AUTHOR]

The purpose of this study was to use bivariate functional principal components analysis (bfPCA) to quantify patterns in barbell trajectories during the snatch and to investigate whether these patterns correlate with weightlifting performance and biomechanical characteristics that characterise weightlifting technique. A motion capture system was used to record three-dimensional barbell trajectories as six weightlifters performed three snatch lifts during a weightlifting competition. Horizontal and vertical barbell positions of all lifts were used as input to a bfPCA. Weightlifting performance was quantified through the ratio of barbell mass/body-mass, whereas biomechanical variables were quantified through peak vertical barbell velocity and acceleration. The bfPCA extracted barbell trajectory patterns related to variations in general forward/backward motion (pattern 1), peak height (pattern 2), and crossing of the vertical reference line during the first pull (pattern 3). Spearman rank correlations showed that pattern 1 correlated positively with weightlifting performance and negatively with peak barbell velocity and acceleration. The opposite results were found for pattern 3. Interpretation of the extracted barbell trajectory patterns and statistical results suggest that better weightlifting performances were characterised by snatch lifts that exhibited general backward shifts and limited forward motions during the first and second pull, regardless of peak heights. [ABSTRACT FROM AUTHOR]

The proliferation of new biomechanical technology in laboratory and field settings facilitates the capture of data-sets consisting of complex time-series. An understanding of the appropriate statistical approaches for analysing and interpreting these data-sets is required and the functional data analysis (FDA) family of statistical techniques has emerged in the biomechanical literature. Given the use of FDA is currently in its infancy with biomechanical data, this paper will form the first of a two part series aiming to address practical issues surrounding the application of FDA techniques in biomechanics. This work focuses on functional principal components analysis (fPCA), which is explored using existing literature and sample data from an on-water rowing database. In particular methodological considerations for the implementation of fPCA such as temporal normalisation of data, removal of unwanted forms of variation in a data-set and documented methods for preserving the original temporal properties within a set of curves are explored in detail as a part of this review. Limitations and strengths of the technique are outlined and recommendations are provided to encourage the appropriate use of fPCA within the field of applied sports biomechanics. [ABSTRACT FROM AUTHOR]

Based on technological and analytical advances, the capability to more accurately and finitely examine biomechanical and skill characteristics of movement has improved. The purpose of this study was to use Inertial Measurement Units (IMUs) and Functional Principal Components Analysis (fPCA) to examine the role of movement variability (assessed via angular velocity), on 2 divers (1 international level; 1 national) performing the forward 3½ pike somersault dive. Analysis of angular velocity curves during ive-flight identified 5 fPCs, accounting for 96.5% of movement variability. The national diver's scatter plots and standard deviation of fPC scores illustrated larger magnitudes of angular velocity variability across dive flight. For fPC1 and fPC3, magnitudes of SD variability were 282.6 and 201.5, respectively. The international diver illustrated more consistent angular velocity profiles, with clustering of fPCs scores (e.g., fPC1 & 3 = SD's of 75.2 & 68.0). To account for lower variability in the international diver, the ability to better coordinate movement sequences and functionally utilise feedback in response to initiation of the somersault position is highlighted. Overall, findings highlight how both IMUs and fPCA can more holistically and finitely examine the biomechanical and skill characteristics of movement sequences with the capability to inform athlete development. [ABSTRACT FROM AUTHOR]

Sporting performance is often investigated through graphical observation of key technical variables that are representative of whole movements. The presence of differences between athletes in such variables has led to terms such as movement signatures being used. These signatures can be multivariate (multiple time-series observed concurrently), and also be composed of variables measured relative to different scales. Analytical techniques from areas of statistics such as Functional Data Analysis (FDA) present a practical alternative for analysing multivariate signatures. When applied to concurrent bivariate time-series multivariate functional principal components analysis (referred to as bivariate fPCA or bfPCA in this paper) has demonstrated preliminary application in biomechanical contexts. Despite this, given the infancy of bfPCA in sports biomechanics there are still necessary considerations for its use with non-conventional or complex bivariate structures. This paper focuses on the application of bfPCA to the force-angle graph in on-water rowing, which is a bivariate structure composed of variables with different units. A normalisation approach is proposed to investigate and standardise differences in variability between the two variables. The results of bfPCA applied to the non-normalised data and normalised data are then compared. Considerations and recommendations for the application of bfPCA in this context are also provided. [ABSTRACT FROM AUTHOR]

There has been substantial interest in the mechanisms underpinning the skilled movements of on-water rowing for more than 150 years. Contemporary attention from biomechanical research has focused on the important relationship between kinetics (such as force application at the oar) and performance. A range of instrumentation systems have been developed and used in both academic and applied training contexts to better understand this relationship. Both qualitative and quantitative analytical approaches have been used in conjunction with these instrumentation systems for observing differences in propulsive force patterns between rowers. Despite the use of these analytical approaches, there is still limited consensus surrounding which characteristics of force profiles are associated with better rowing performance. Newell’s model of constraints is provided as a framework for understanding why this lack of clarity exists surrounding force profile characteristics and performance. Further to this, direction for further research is provided by a framework that outlines two main streams: (1) exploration of constraints and how they are related to force profile characteristics; and (2) after controlling for constraints, exploration of performance and how it is related to force profile characteristics. These two steps are sequential, with an understanding of constraints influencing how we understand the interaction of force profiles and performance. [ABSTRACT FROM AUTHOR]

Anterior cruciate ligament (ACL) injuries have a significant impact on athletic performance and long‐term quality of life. Force plates and qualitative screening tools are feasible and effective screening methods to identify abnormal movement quality associated with increased injury risk. Comparing qualitative assessments of landing ability with force‐time curves, may detect unique differences between safe and high‐risk athletic movement patterns. The aim of this study was to determine low‐ and high‐risk landing ability from qualitive landing assessments and to examine the resulting force‐time curves using functional principal component analysis (fPCA). Thirty‐one healthy academy athletes (10 males and 21 females) completed double‐ and single‐leg dominant and non‐dominant jump‐landing‐rebound tasks. All movements were filmed in multiple‐planes, and vertical ground reaction forces (vGRF) were simultaneously collected. The Landing Error Scoring System (LESS) and Single‐Leg Landing Error Scoring System (SL‐LESS) were used to score landing footage. From these scores, athletes were categorized into low‐risk and high‐risk groups for further analysis. fPCA was used to examine differences between landing quality groups force‐time curves. Compared to high‐risk landers, low‐risk landers demonstrated significantly longer contact times across all movements. Scores from fPC1 revealed safe and high‐risk landing techniques expose athletes to significantly different loading patterns during double‐ and single‐leg dominant movements. A significant positive relationship was observed between fPC1 and LESS scores, however this relationship was not observed in both single‐leg landing scores. Where possible incorporating curve analysis methods like fPCA into multi‐faceted screening approaches may help practitioners uncover unique insights into athletic loading strategies. [ABSTRACT FROM AUTHOR]

Thomas, C, Dos'Santos, T, Warmenhoven, J, and Jones, PA. Between-limb differences during 180° turns in female soccer players: application of statistical parametric mapping. J Strength Cond Res 36(11): 3136–3142, 2022—This study was exploratory in nature and investigated the ability of statistical parametric mapping (SPM) to assess between-limb differences in lower-extremity movement change of direction. Fourteen female soccer players (mean ± SD ; age = 20.6 ± 0.6 years; height = 1.65 ± 0.07 m; and body mass = 56.04 ± 6.20 kg). For comparisons between preferred and nonpreferred limbs, vertical (Fz) and horizontal (Fx) ground reaction force were determined along with hip, knee, and ankle angles and moments in the sagittal plane during weight acceptance during the final contact. In addition, frontal plane knee abduction angles and moments were calculated during the final contact. Statistical parametric mapping software was then used to assess for differences between the entire weight acceptance phase of preferred and nonpreferred limbs. There were no differences between limbs in all variables using SPM. These results demonstrate that female soccer players exhibit little side-to-side differences in certain lower-limb biomechanics when performing a turn maneuver. These findings can be utilized by practitioners and clinicians when developing injury prevention and rehabilitation programs. [ABSTRACT FROM AUTHOR]

Simple Summary: When cells are irradiated, their DNA can become damaged, this causes different types of repair processes to try and fix the DNA breaks. One of the most lethal types of DNA damage is double-strand breaks (DSBs). This work models the most used DSB repair process called Non-Homologous End Joining (NHEJ) and includes both its resection-independent and resection-dependent pathways. The models produced are benchmarked against experimental normal and deficient cell-types across a wide range of radiation qualities. We compare two approaches of modelling, the first is where the DSBs can repair in parallel and the second is where the DSBs repair is entwined. We find that it is necessary to consider both the resection-independent and resection-dependent pathways as entwined to produce a model which robustly matches experimental work. Through better modelling of NHEJ repair, it can improve our understanding of radiation response which has potential in biological optimisation for radiotherapy. Mechanistic in silico models can provide insight into biological mechanisms and highlight uncertainties for experimental investigation. Radiation-induced double-strand breaks (DSBs) are known to be toxic lesions if not repaired correctly. Non-homologous end joining (NHEJ) is the major DSB-repair pathway available throughout the cell cycle and, recently, has been hypothesised to consist of a fast and slow component in G0/G1. The slow component has been shown to be resection-dependent, requiring the nuclease Artemis to function. However, the pathway is not yet fully understood. This study compares two hypothesised models, simulating the action of individual repair proteins on DSB ends in a step-by-step manner, enabling the modelling of both wild-type and protein-deficient cell systems. Performance is benchmarked against experimental data from 21 cell lines and 18 radiation qualities. A model where resection-dependent and independent pathways are entirely separated can only reproduce experimental repair kinetics with additional restraints on end motion and protein recruitment. However, a model where the pathways are entwined was found to effectively fit without needing additional mechanisms. It has been shown that DaMaRiS is a useful tool when analysing the connections between resection-dependent and independent NHEJ repair pathways and robustly matches with experimental results from several sources. [ABSTRACT FROM AUTHOR]

This study aimed to investigate inter- and intra-athlete technique variability in pre-elite and elite Australian fast bowlers delivering new ball conventional swing bowling. Ball grip angle and pelvis, torso, shoulder, elbow, wrist, upper arm, forearm, and hand kinematics were investigated at the point of ball release for inswing and outswing deliveries. Descriptive evaluations of group and individual data and k-means cluster analyses were used to assess inter- and intra-bowler technique variability. Inter-athlete technique and ball grip variability were identified, demonstrating that skilled bowlers use individualised strategies to generate swing. Functional movement variability was demonstrated by intra-athlete variability in successful swing bowling trials. Bowlers demonstrated stable technique parameters in large proximal body segments of the pelvis and torso, providing a level of repeatability to their bowling action. Greater variation was observed in bowling arm kinematics, allowing athletes to manipulate the finger and ball position to achieve the desired seam orientation at the point of ball release. This study demonstrates that skilled bowlers use individualised techniques and grips to generate swing and employ technique variations in successive deliveries. Coaches should employ individualised training strategies and use constraints-led approaches in training environments to encourage bowlers to seek adaptive movement solutions to generate swing. [ABSTRACT FROM AUTHOR]

Principal components analysis (PCA) of waveforms and functional PCA (f PCA) are statistical approaches used to explore patterns of variability in biomechanical curve data, with f PCA being an accepted statistical method grounded within the functional data analysis (FDA) statistical framework. This technical note demonstrates that PCA of waveforms is the most rudimentary form of FDA, and consequently can be rationalised within the FDA framework of statistical processes. Mathematical proofing applied demonstrations of both techniques, and an example of when f PCA may be of greater benefit to control over smoothing of functional principal components is provided using an open access motion sickness dataset. Finally, open access software is provided with this paper as means of priming the biomechanics community for using these methods as a part of future functional data explorations. [ABSTRACT FROM AUTHOR]

• c-NHEJ modelled as two stage synapsis, with initial stage prone to dissociation. • Initial stage modelled as dissociating after autophosphorylation of DNA-PKcs. • Dissociation of DNA-PK modelled by DNA-PKcs mediated phosphorylation of Ku70/80. • Combining above mechanisms was sufficient to reproduce published cell behaviour. • CTRW sub-diffusion is insufficient to describe DSB end motion and cell behaviour. After radiation exposure, one of the critical processes for cellular survival is the repair of DNA double strand breaks. The pathways involved in this response are complex in nature and involve many individual steps that act across different time scales, all of which combine to produce an overall behaviour. It is therefore experimentally challenging to unambiguously determine the mechanisms involved and how they interact whilst maintaining strict control of all confounding variables. In silico methods can provide further insight into results produced by focused experimental investigations through testing of the hypotheses generated. Such computational testing can asses competing hypotheses by investigating their effects across all time scales concurrently, highlighting areas where further experimental work can have the most significance. We describe the construction of a mechanistic model by combination of several hypothesised mechanisms reported in the literature and supported by experiment. Compatibility of these mechanisms was tested by fitting simulation to results reported in the literature. To avoid over-fitting, we used an approach of sequentially testing individual mechanisms within this pathway. We demonstrate that using this approach the model is capable of reproducing published protein kinetics and overall repair trends. This provides evidence supporting the feasibility of the proposed mechanisms and revealed how they interact to produce an overall behaviour. Furthermore, we show that the assumed motion of individual double strand break ends plays a crucial role in determining overall system behaviour. [ABSTRACT FROM AUTHOR]

Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides are detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level. Author summary: We have used a technique which allows us to understand how parts of our DNA are organised within a cell nucleus. This technique has previously shown differences in the organisation between different cell-types. In this study, we show that these differences produce significant change in the way our DNA is damaged when exposed to radiation. This is important to understand as one of the primary ways we treat cancer is using radiotherapy. However, whilst we attempt to target the cancer with radiation, some healthy tissue also receives radiation. It is the radiation delivered to the healthy tissue which limits how much radiation we can safely give to the cancer without causing significant side effects in patients. To know how much radiation we can give, over time, we have learnt generally safe amounts of radiation that can be given to healthy tissue. Even so, sometimes patients will still have worse side effects than what we would have predicted. If we want to further improve our treatments and patient safety, we need to better understand how this safe limit varies between each patient. The first step in to fully understanding this process comes from a better understanding of how different cell-types are affected by radiation, which is partly driven by DNA organisation, shown in this work. [ABSTRACT FROM AUTHOR]

Hamstring injuries are one of the most prevalent injuries in rugby union and many other running-based sports, such as track sprinting and soccer. The majority of these injuries occur during running; however, the relationship between running mechanics and hamstring injury is unclear. Obtaining large samples of prospective injury data to examine this relationship is difficult, and therefore exploratory analysis frameworks may assist in deriving valuable information from studies with small but novel samples. The aim of this study was to undertake a prospective exploratory analysis of the relationship between running mechanics and hamstring injury. Kinematic and kinetic data of the trunk, pelvis and lower limbs were collected during maximal overground running efforts for ten elite rugby union athletes. Subsequently, hamstring injury occurrence was recorded for the following Super Rugby season, during which three athletes sustained a running-based hamstring injury. Functional principal component analysis was used to visualise patterns of variability in running mechanics during the late swing phase between athletes. Results indicated that subsequently injured athletes demonstrated a tendency for greater thoracic lateral flexion, greater hip extension moments and greater knee power absorption, compared to uninjured athletes. All variables demonstrated an ability to descriptively differentiate between injured and uninjured athletes at approximately 60% of the late swing phase. Therefore, we hypothesize that greater thoracic lateral flexion, a greater hip extension moment and greater knee power absorption between peak hip flexion and peak knee extension during the late swing phase may put rugby athletes at greater risk of running-based hamstring injury. [ABSTRACT FROM AUTHOR]

Micronucleus (MN) formation is routinely used as a biodosimeter for radiation exposures and has historically been used as a measure of DNA damage in cells. Strongly correlating with dose, MN are also suggested to indicate radiation quality, differentiating between particle and photon irradiation. The "gold standard" for measuring MN formation is Fenech's cytokinesis-block micronucleus (CBMN) cytome assay, which uses the cytokinesis blocking agent cytochalasin-B. Here, we present a comprehensive analysis of the literature investigating MN induction trends in vitro , collating 193 publications, with 2476 data points. Data were collected from original studies that used the CBMN assay to quantify MN in response to ionizing radiation in vitro. Overall, the meta-analysis showed that individual studies mostly have a linear increase of MN with dose [85% of MN per cell (MNPC) datasets and 89% of percentage containing MN (PCMN) datasets had an R 2 greater than 0.90]. However, there is high variation between studies, resulting in a low R 2 when data are combined (0.47 for MNPC datasets and 0.60 for PCMN datasets). Particle type, species, cell type, and cytochalasin-B concentration were suggested to influence MN frequency. However, variation in the data meant that the effects could not be strongly correlated with the experimental parameters investigated. There is less variation between studies when comparing the PCMN rather than the number of MNPC. Deviation from CBMN protocol specified timings did not have a large effect on MN induction. However, further analysis showed less variation between studies following Fenech's protocol closely, which provided more reliable results. By limiting the cell type and species as well as only selecting studies following the Fenech protocol, R 2 was increased to 0.64 for both measures. We therefore determine that due to variation between studies, MN are currently a poor predictor of radiation-induced DNA damage and make recommendations for futures studies assessing MN to improve consistency between datasets. [ABSTRACT FROM AUTHOR]

Tibiofemoral shape influences knee kinematics but little is known about the effect of shape on deep knee flexion kinematics. The aim of this study was to examine the association between tibiofemoral joint shape and kinematics during deep kneeling in patients with and without osteoarthritis (OA). Sixty‐one healthy participants and 58 patients with end‐stage knee OA received a computed tomography (CT) of their knee. Participants completed full flexion kneeling while being imaged using single‐plane fluoroscopy. Six‐degree‐of‐freedom kinematics were measured by registering a three‐dimensional (3D)‐static CT onto 2D‐dynamic fluoroscopic images. Statistical shape modeling and bivariate functional principal component analysis (bfPCA) were used to describe variability in knee shape and kinematics, respectively. Random‐forest‐regression models were created to test the ability of shape to predict kinematics controlling for body mass index, sex, and group. The first seven modes of the shape model up to three modes of the bfPCAs captured more than 90% of the variation. The ability of the random forest models to predict kinematics from shape was low, with no more than 50% of the variation being explained in any model. Furthermore, prediction errors were high, ranging between 24.2% and 29.4% of the data. Variations in the bony morphology of the tibiofemoral joint were weakly associated with the kinematics of deep knee flexion. The models only explained a small amount of variation in the data with high error rates indicating that additional predictors need to be identified. These results contribute to the clinical understanding of knee kinematics and potentially the expectations placed on high‐flexion total knee replacement design. [ABSTRACT FROM AUTHOR]

Background: Many injury prevention and rehabilitation programs aim to train hamstring and quadriceps co-activation to constrain excessive anterior tibial translation and protect the anterior cruciate ligament (ACL) from injury. However, despite strong clinical belief in its efficacy, primary evidence supporting training co-activation of the hamstrings and quadriceps muscles for ACL injury prevention and rehabilitation is quite limited. Therefore, the purpose of the study presented in this paper was to determine if hamstring-quadriceps co-activation alters knee joint kinematics, and also establish if it affects ACL elongation. Methods: A computed tomography (CT) scan from each participant's dominant leg was acquired prior to performing two step-ups under fluoroscopy: one with 'natural' hamstring-quadriceps co-activation, one with deliberate co-activation. Electromyography was used to confirm increased motor unit recruitment. The CT scan was registered to fluoroscopy for 4-D modeling, and knee joint kinematics subsequently measured. Anterior cruciate ligament attachments were mapped to the 4-D models and its length was assumed from the distance between attachments. Anterior cruciate ligament elongation was derived from the change in distance between those points as they moved relative to each other. Results: Reduced ACL elongation as well as knee joint rotation, abduction, translation, and distraction was observed for the step up with increased co-activation. A relationship was shown to exist for change in ACL length with knee abduction (r = 0.91; p ≤ 0.001), with distraction (r = -0.70; p = 0.02 for relationship with compression), and with anterior tibial translation (r = 0.52; p = 0.01). However, ACL elongation was not associated with internal rotation or medial translation. Medial hamstring-quadriceps co-activation was associated with a shorter ACL (r = -0.71; p = 0.01), and lateral hamstring-quadriceps co-activation was related to ACL elongation (r = 0.46; p = 0.05). Conclusion: Net co-activation of the hamstrings and quadriceps muscles will likely reduce ACL elongation provided that the proportion of medial hamstring-quadriceps co-activation exceeds lateral. [ABSTRACT FROM AUTHOR]