Relationships between Racket Arm Joint Moments and Racket Head Speed during the Badminton Jump Smash Performed by Elite Male Malaysian Players

Three-dimensional position data of nineteen elite male Malaysian badminton players performing a series of maximal jump smashes were collected using a motion capture system. A ‘resultant moments’ inverse dynamics analysis was performed on the racket arm joints (shoulder, elbow and wrist). Relationships between racket head speed and peak joint moments were quantified using correlational analyses, inclusive of a Benjamini–Hochberg correction for multiple-hypothesis testing. The racket head centre speed at racket–shuttlecock contact was, on average, 61.2 m/s with a peak of 68.5 m/s which equated to average shuttlecock speeds of 95.2 m/s with a peak of 105.0 m/s. The correlational analysis revealed that a larger shoulder internal rotation moment (r = 0.737), backwards shoulder plane of elevation moment (r = 0.614) and wrist extension moment (r = −0.564) were associated with greater racket head centre speed at racket–shuttlecock contact. Coaches should consider strengthening the musculature associated with shoulder internal rotation, plane of elevation and wrist extension. This work provides a unique analysis of the joint moments of the racket arm during the badminton jump smash performed by an elite population and highlights significant relationships between racket head speed and peak resultant joint moments.

Internal Tibial Forces and Moments During Graded Running

This note is to correct errata in the paper "Internal Tibial Forces and Moments During Graded Running" published in Journal of Biomechanical Engineering, Vol. 144, p. 011009 (2021), DOI: 10.1115/1.4051924. In the Data Analysis section, it was stated that, "The joint moments used in the optimization were the flexion-extension and abduction-adduction moments at the hip and ankle, and the flexion-extension moment at the knee." However, it has come to our attention that this is incorrect, and instead the joint moments used in the static optimization routine were the flexion-extension and abduction-adduction moments at the hip, and the flexion-extension moment at the knee and ankle. Please accept our apologies for the error.

Machine Learning Model to Estimate Net Joint Moments during Lifting Task Using Wearable Sensors: A Preliminary Study for Design of Exoskeleton Control System

Accurately measuring the lower extremities and L5/S1 moments is important since L5/S1 moments are the principal parameters that measure the risk of musculoskeletal diseases during lifting. In this study, protocol that predicts lower extremities and L5/S1 moments with an insole sensor was proposed to replace the prior methods that have spatial constraints. The protocol is hierarchically composed of a classification model and a regression model to predict joint moments. Additionally, a single LSTM model was developed to compare with proposed protocol. To optimize hyperparameters of the machine learning model and input feature, Bayesian optimization method was adopted. As a result, the proposed protocol showed a relative root mean square error (rRMSE) of 8.06~13.88% while the single LSTM showed 9.30~18.66% rRMSE. This protocol in this research is expected to be a starting point for developing a system for estimating the lower extremity and L5/S1 moment during lifting that can replace the complex prior method and adopted to workplace environments. This novel study has the potential to precisely design a feedback iterative control system of an exoskeleton for the appropriate generation of an actuator torque.

Machine Learning-Based Estimation of Ground Reaction Forces and Knee Joint Kinetics from Inertial Sensors While Performing a Vertical Drop Jump

Nowadays, the use of wearable inertial-based systems together with machine learning methods opens new pathways to assess athletes’ performance. In this paper, we developed a neural network-based approach for the estimation of the Ground Reaction Forces (GRFs) and the three-dimensional knee joint moments during the first landing phase of the Vertical Drop Jump. Data were simultaneously recorded from three commercial inertial units and an optoelectronic system during the execution of 112 jumps performed by 11 healthy participants. Data were processed and sorted to obtain a time-matched dataset, and a non-linear autoregressive with external input neural network was implemented in Matlab. The network was trained through a train-test split technique, and performance was evaluated in terms of Root Mean Square Error (RMSE). The network was able to estimate the time course of GRFs and joint moments with a mean RMSE of 0.02 N/kg and 0.04 N·m/kg, respectively. Despite the comparatively restricted data set and slight boundary errors, the results supported the use of the developed method to estimate joint kinetics, opening a new perspective for the development of an in-field analysis method.

Ontogenetic changes in limb posture, kinematics, forces, and joint moments in American alligators (Alligator mississippiensis)

As animals increase in size, common patterns of morphological and physiological scaling may require them to perform behaviors such as locomotion while experiencing a reduced capacity to generate muscle force and an increased risk of tissue failure. Large mammals are known to manage increased mechanical demands by using more upright limb posture. However, the presence of such size-dependent changes in limb posture has rarely been tested in animals that use non-parasagittal limb kinematics. Here, we used juvenile to subadult American alligators (total length 0.46–1.27 m, body mass 0.3–5.6 kg) and examined their limb kinematics, forces, joint moments, and center of mass to test for ontogenetic shifts in posture and limb mechanics. Larger alligators typically walked with a more adducted humerus and femur and a more extended knee. Normalized peak joint moments reflected these postural patterns, with shoulder and hip moments imposed by the ground reaction force showing relatively greater magnitudes in the smallest individuals. Thus, as larger alligators use more upright posture, they incur relatively smaller joint moments than smaller alligators, which could reduce the forces that the shoulder and hip adductors of larger alligators must generate. The center of mass (CoM) shifted nonlinearly from juveniles through subadults. The more anteriorly positioned CoM in small alligators, together with their compliant hindlimbs, contributes to their higher forelimb and lower hindlimb normalized peak vertical forces in comparison to larger alligators. Future studies of alligators that approach maximal adult sizes could give further insight into how animals with non-parasagittal limb posture modulate locomotor patterns as they increase in mass and experience changes in the CoM.

Inertial Motion Capture-Based Whole-Body Inverse Dynamics

Inertial Motion Capture (IMC) systems enable in situ studies of human motion free of the severe constraints imposed by Optical Motion Capture systems. Inverse dynamics can use those motions to estimate forces and moments developing within muscles and joints. We developed an inverse dynamic whole-body model that eliminates the usage of force plates (FPs) and uses motion patterns captured by an IMC system to predict the net forces and moments in 14 major joints. We validated the model by comparing its estimates of Ground Reaction Forces (GRFs) to the ground truth obtained from FPs and comparing predictions of the static model’s net joint moments to those predicted by 3D Static Strength Prediction Program (3DSSPP). The relative root-mean-square error (rRMSE) in the predicted GRF was 6% and the intraclass correlation of the peak values was 0.95, where both values were averaged over the subject population. The rRMSE of the differences between our model’s and 3DSSPP predictions of net L5/S1 and right and left shoulder joints moments were 9.5%, 3.3%, and 5.2%, respectively. We also compared the static and dynamic versions of the model and found that failing to account for body motions can underestimate net joint moments by 90% to 560% of the static estimates.

Comparison of Gait Symmetry and Joint Moments in Unilateral and Bilateral Hip Osteoarthritis Patients and Healthy Controls

Patients with unilateral hip osteoarthritis show a characteristic gait pattern in which they unload the affected leg and overload the unaffected leg. Information on the gait characteristics of patients with bilateral hip osteoarthritis is very limited. The main purposes of this study were to investigate whether the gait pattern of both legs of patients with bilateral hip osteoarthritis deviates from healthy controls and whether bilateral hip osteoarthritis patients show a more symmetrical joint load compared to unilateral hip osteoarthritis patients. In this prospective study, 26 patients with bilateral hip osteoarthritis, 26 patients with unilateral hip osteoarthritis and 26 healthy controls were included. The three groups were matched for gender, age and walking speed. Patients were scheduled for a unilateral total hip arthroplasty on the more affected/more painful side. All participants underwent a three-dimensional gait analysis. Gait kinematics and gait kinetics of patients and controls were compared using Statistical Parametric Mapping. Corrected for speed, the gait kinematics and kinetics of both legs of patients with bilateral hip osteoarthritis differed from healthy controls. Bilateral patients had symmetrical knee joint loading, in contrast to the asymmetrical knee joint loading in unilateral hip osteoarthritis patients. The ipsilateral leg of the bilateral patients could be included in studies in addition to unilateral hip osteoarthritis patients as no differences were found. Although patients with bilateral hip osteoarthritis show more symmetrical frontal plane knee joint moments, a pathological external knee adduction moment in the second half of stance was present in the ipsilateral leg in patients with unilateral and bilateral hip osteoarthritis. The lateral adjustment of the knee adduction moment may initiate or accelerate progression of degenerative changes in the lateral compartment of the knee.