Are joint torque models limited by an assumption of monoarticularity?

This study determines whether maximal voluntary ankle plantar flexor torque could be more accurately represented using a torque generator that is a function of both knee and ankle kinematics. Iso velocity and isometric ankle plantar flexor torques were measured on a single participant for knee joint angles of 111° to 169° (approximately full extension) using a Contrex M J dynamometer. Maximal voluntary torque was represented by a 19-parameter two-joint function of ankle and knee joint angles and angular velocities with the parameters determined by minimizing a weighted root mean square difference between measured torques and the two-joint function. The weighted root mean square difference between the two-joint function and the measured torques was 10 N-m or 3% of maximum torque. The two-joint function was a more accurate representation of maximal voluntary ankle plantar flexor torques than an existing single-joint function where differences of 19% of maximum torque were found. It is concluded that when the knee is flexed by more than 40°, a two-joint representation is necessary

An isovelocity dynamometer method to determine monoarticular and biarticular muscle parameters

This study aimed to determine whether subject-specific individual muscle models for the ankle plantar flexors could be obtained from single joint isometric and isovelocity maximum torque measurements in combination with a model of plantar flexion. Maximum plantar flexion torque measurements were taken on one subject at six knee angles spanning full flexion to full extension. A planar three-segment (foot, shank and thigh), two muscle (soleus and gastrocnemius) model of plantar flexion was developed. Seven parameters per muscle were determined by minimizing a weighted root mean square difference (wRMSD) between the model output and the experimental torque data. Valid individual muscle models were obtained using experimental data from only two knee angles giving a wRMSD score of 16 N m, with values ranging from 11 to 17 N m for each of the six knee angles. The robustness of the methodology was confirmed through repeating the optimization with perturbed experimental torques (±20%) and segment lengths (±10%) resulting in wRMSD scores of between 13 and 20 N m. Hence, good representations of maximum torque can be achieved from subject-specific individual muscle models determined from single joint maximum torque measurements. The proposed methodology could be applied to muscle-driven models of human movement with the potential to improve their validity

Optimisation of a machine learning algorithm in human locomotion using principal component and discriminant function analyses

Assessment methods in human locomotion often involve the description of normalised graphical profiles and/or the extraction of discrete variables. Whilst useful, these approaches may not represent the full complexity of gait data. Multivariate statistical methods, such as Principal Component Analysis (PCA) and Discriminant Function Analysis (DFA), have been adopted since they have the potential to overcome these data handling issues. The aim of the current study was to develop and optimise a specific machine learning algorithm for processing human locomotion data. Twenty participants ran at a self-selected speed across a 15m runway in barefoot and shod conditions. Ground reaction forces (BW) and kinematics were measured at 1000 Hz and 100 Hz, respectively from which joint angles (°), joint moments (N.m.kg-1) and joint powers (W.kg-1) for the hip, knee and ankle joints were calculated in all three anatomical planes. Using PCA and DFA, power spectra of the kinematic and kinetic variables were used as a training database for the development of a machine learning algorithm. All possible combinations of 10 out of 20 participants were explored to find the iteration of individuals that would optimise the machine learning algorithm. The results showed that the algorithm was able to successfully predict whether a participant ran shod or barefoot in 93.5% of cases. To the authors’ knowledge, this is the first study to optimise the development of a machine learning algorithm

The effect of visual focus on spatio-temporal and kinematic parameters of treadmill running

The characteristics of a treadmill and the environment where it is based could influence the user’s gaze and have an effect on their running kinematics and lower limb impacts. The aim of this study was to identify the effect of visual focus on spatio-temporal parameters and lower limb kinematics during treadmill running. Twenty six experienced runners ran at 3.33 m s−1 on a treadmill under two visual conditions, either looking ahead at a wall or looking down at the treadmill visual display. Spatio-temporal parameters, impact accelerations of the head and tibia, and knee and ankle kinematics were measured for the final 15 s of a 90 s bout of running under each condition. At the end of the test, participants reported their preference for the visual conditions assessed. Participants’ stride angle, flight time, knee flexion during the flight phase, and ankle eversion during contact time were increased when runners directed visual focus toward the wall compared to the treadmill display (p 0.05). However, the effect size of all biomechanical alterations was small. The Treadmill condition was the preferred condition by the participants (p < 0.001; ESw = 1.0). The results of the current study indicate that runners had a greater mass centre vertical displacement when they ran looking ahead, probably with the aim of compensating for reduced visual feedback, which resulted in larger head accelerations. Greater knee flexion during the flight phase and ankle eversion during the contact time were suggested as compensatory mechanisms for lower limb impacts

The calculation, thresholds and reporting of inter-limb strength asymmetry: a systematic review

The prevalence of inter-limb strength differences is well documented in the literature however, there are inconsistencies related to measurement and reporting, and the normative values and effects associated with inter-limb asymmetry. Therefore, the aims of this systematic review were to: 1) assess the appropriateness of existing indices for the calculation of asymmetry, 2) interrogate the evidence basis for literature reported thresholds used to define asymmetry and 3) summarise normative levels of inter-limb strength asymmetry and their effects on injury and performance. To conduct this systematic review, scientific databases (PubMed, Scopus, SPORTDiscus and Web of Science) were searched and a total of 3,594 articles were retrieved and assessed for eligibility and article quality. The robustness of each identified asymmetry index was assessed, and the evidence-basis of the identified asymmetry thresholds was appraised retrospectively using the references provided. Fifty-three articles were included in this review. Only four of the twelve identified indices were unaffected by the limitations associated with selecting a reference limb. Eighteen articles applied a threshold to original research to identify “abnormal” asymmetry, fifteen of which utilised a threshold between 10-15%, yet this threshold was not always supported by appropriate evidence. Asymmetry scores ranged between and within populations from approximate symmetry to asymmetries larger than 15%. When reporting the effects of strength asymmetries, increased injury risk and detriments to performance were often associated with larger asymmetry, however the evidence was inconsistent. Limitations of asymmetry indices should be recognised, particularly those that require selection of a reference limb. Failure to reference the origin of the evidence for an asymmetry threshold reinforces doubt over the use of arbitrary thresholds, such as 10-15%. Therefore, an individual approach to defining asymmetry may be necessary to refine robust calculation methods and to establish appropriate thresholds across various samples and methodologies that enable appropriate conclusions to be drawn

Is it necessary to include biarticular effects within joint torque representations of knee flexion and knee extension?

This article is closed access. It is available at: http://dx.doi.org/10.1615/IntJMultCompEng.2011002379