Limb Joint Angles Research Articles

Gait Analysis of Elderly and Young People Based on Joint Angles and Positions

For the elderly, the motor function of walking is significant for the maintenance and improvement of their quality of life (QOL). Walking patterns have been postulated to be associated with a decline in walking ability. The objective of this study was to develop a wearable sensor that can capture changes in walking ability in daily life. To this end, motion capture was employed to measure the lower limb joint angles and the trajectories of the lower limbs and knees for each subject while walking at a normal walking speed and to compare the results between elderly and young patients. The differences in walking patterns between the elderly and young patients were analyzed in terms of elevation angles, and an index was calculated to capture changes during walking based on elevation angles and trajectories.

Estimation of Lower Limb Joint Angles Using sEMG Signals and RGB-D Camera.

Estimating human joint angles is a crucial task in motion analysis, gesture recognition, and motion intention prediction. This paper presents a novel model-based approach for generating reliable and accurate human joint angle estimation using a dual-branch network. The proposed network leverages combined features derived from encoded sEMG signals and RGB-D image data. To ensure the accuracy and reliability of the estimation algorithm, the proposed network employs a convolutional autoencoder to generate a high-level compression of sEMG features aimed at motion prediction. Considering the variability in the distribution of sEMG signals, the proposed network introduces a vision-based joint regression network to maintain the stability of combined features. Taking into account latency, occlusion, and shading issues with vision data acquisition, the feature fusion network utilizes high-frequency sEMG features as weights for specific features extracted from image data. The proposed method achieves effective human body joint angle estimation for motion analysis and motion intention prediction by mitigating the effects of non-stationary sEMG signals.

Effect of Unanticipated Tasks on Side-Cutting Stability of Lower Extremity with Patellofemoral Pain Syndrome.

Patellofemoral pain syndrome (PFPS) is one of the most common causes of anterior knee pain encountered in the outpatient setting. The purpose of this study was to compare the lower limb biomechanical differences during anticipated and unanticipated side-cutting in athletes with PFPS. Fifteen male basketball players diagnosed with PFPS were enrolled in the study. Participants executed both anticipated and unanticipated 45-degree side-cutting tasks. Motion analysis systems, force plates, and electromyography (EMG) were used to assess the lower limb joint angles, joint moments, joint stiffness, and patellofemoral joint contact forces. Analyzed biomechanical data were used to compare the differences between the two circumstances. Unanticipated side-cutting resulted in significantly increased ankle plantarflexion and dorsiflexion angles, knee abduction and internal rotation angles, and hip abduction angles, as well as heightened knee adduction moments. Additionally, patellofemoral joint contact forces and stress increased, while contact area decreased during unanticipated tasks. Unanticipated movement raises the demands for joint stability and neuromuscular control, increasing injury risks in athletes with PFPS. These findings have practical implications for developing targeted rehabilitation programs and injury prevention strategies.

Generative adversarial networks to create synthetic motion capture datasets including subject and gait characteristics

Resource-intensive motion capture (mocap) systems challenge predictive deep learning applications, requiring large and diverse datasets. We tackled this by modifying generative adversarial networks (GANs) into conditional GANs (cGANs) that can generate diverse mocap data, including 15 marker trajectories, lower limb joint angles, and 3D ground reaction forces (GRFs), based on specified subject and gait characteristics. The cGAN comprised 1) an encoder compressing mocap data to a latent vector, 2) a decoder reconstructing the mocap data from the latent vector with specific conditions and 3) a discriminator distinguishing random vectors with conditions from encoded latent vectors with conditions. Single-conditional models were trained separately for age, sex, leg length, mass, and walking speed, while an additional model (Multi-cGAN) combined all conditions simultaneously to generate synthetic data. All models closely replicated the training dataset (<8.1 % of the gait cycle different between experimental and synthetic kinematics and GRFs), while a subset with narrow condition ranges was best replicated by the Multi-cGAN, producing similar kinematics (<1°) and GRFs (<0.02 body-weight) averaged by walking speeds. Multi-cGAN also generated synthetic datasets for three previous studies using reported mean and standard deviation of subject and gait characteristics. Additionally, unseen test data was best predicted by the walking speed-conditional, showcasing synthetic data diversity. The same model also matched the dynamical consistency of the experimental data (32 % average difference throughout the gait cycle), meaning that transforming the gait cycle data to the original time domain yielded accurate derivative calculations. Importantly, synthetic data poses no privacy concerns, potentially facilitating data sharing.

Accuracy Validation of a Sensor-Based Inertial Measurement Unit and Motion Capture System for Assessment of Lower Limb Muscle Strength in Older Adults-A Novel and Convenient Measurement Approach.

(1) Background: The aim of this study was to assess lower limb muscle strength in older adults during the transfer from sitting to standing (STS) using an inertial measurement unit (IMU). Muscle weakness in this population can severely impact function and independence in daily living and increase the risk of falls. By using an IMU, we quantified lower limb joint moments in the STS test to support health management and individualized rehabilitation program development for older adults. (2) Methods: This study involved 28 healthy older adults (13 males and 15 females) aged 60-70 years. The lower limb joint angles and moments estimated using the IMU were compared with a motion capture system (Mocap) (pair t-test, ICC, Spearman correlations, Bland-Altman plots) to verify the accuracy of the IMU in estimating lower limb muscle strength in the elderly. (3) Results: There was no significant difference in the lower limb joint angles and moments calculated by the two systems. Joint angles and moments were not significantly different (p > 0.05), and the accuracy and consistency of the IMU system was comparable to that of the Mocap system. For the hip, knee, and ankle joints, the ICCs for joint angles were 0.990, 0.989, and 0.885, and the ICCs for joint moments were 0.94, 0.92, and 0.89, respectively. In addition, the results of the two systems were highly correlated with each other: the r-values for hip, knee, and ankle joint angles were 0.99, 0.99, and 0.96, and the r-values for joint moments were 0.92, 0.96, and 0.85. In the present study, there was no significant difference (p > 0.05) between the IMU system and the Mocap system in calculating lower limb joint angles and moments. (4) Conclusions: This study confirms the accuracy of the IMU in assessing lower limb muscle strength in the elderly. It provides a portable and accurate alternative for the assessment of lower limb muscle strength in the elderly.

Differences in the stride time and lower limb joint angles and their variability during distance running between treadmill and over-ground: a crossover study.

Treadmills have been used in laboratories to assess various measures related to walking and running. However, there has been some skepticism regarding their reliability as a representation of outdoor running. While marathon running has gained popularity as a form of physical activity, there have been few studies examining stride-to-stride variability after distance running, especially in relation to the duration and surface of running. This study compared stride time and lower limb joint angles during distance treadmill running and running over-ground. The hypothesis was that stride-to-stride variability would be influenced by running duration and surface, with greater variability observed during outdoor running. Eleven runners participated in the study, running on a treadmill and over-ground for 31 minutes at their preferred speed. Inertial measurement units were used to measure stride time, total range of motion, and joint angles of the hip, knee, and ankle in different phases of the gait cycle in the sagittal plane movements. Mean and coefficient of variation of each parameter were compared between the initial and final 5 minutes of running on the treadmill and over-ground. There were no significant differences in stride time or its variability based on running duration or surface. However, mean and variability of certain lower limb joint angles were higher during outdoor running, supporting the hypothesis. Variability was higher in the initial duration of running as compared to final phase of running. These findings suggest that treadmill may not fully reflect the dynamics of running over-ground. It is important to consider variability in gait analysis and research, as well as the potential impact on training and clinical practice.

Variability in musculoskeletal fatigue responses associated with repeated exposure to an occupational overhead drilling task completed on successive days

Emerging research suggests that muscular and kinematic responses to overhead work display a high degree of variability in fatigue-related muscular and kinematics changes, both between and within individuals when evaluated across separate days. This study examined whether electromyographic (EMG), kinematic, and kinetic responses to an overhead drilling task performed until volitional fatigue were comparable to those of a repeated identical exposure of the task completed 1 week later. Surface EMG and intramuscular EMG, sampled from 7 shoulder muscles, and right upper limb kinematics and kinetics were analyzed from 15 male and 14 female participants. No significant day-to-day changes in EMG mean power frequency (MPF) were observed, though serratus anterior displayed significantly less fatigue-related increase in EMG root-mean-squared (RMS) signal amplitude on day 2. Unfatigued upper kinematics on day 2 featured an increase in thoracohumeral elevation, elbow flexion, and decrease in wrist ulnar deviation compared to unfatigued state on day 1. Fatigue-related changes in shoulder joint flexion moment that were present on day 1 were reduced on day 2, suggesting that a more efficient overhead work strategy was learned and preserved across successive days. Day-to-day changes in upper limb joint angle variability, quantified by median absolute deviation (MdAD), were joint dependent. Despite yielding a variable fatigue-related kinetic strategy on both days, kinematic and kinetic fatigue-related changes on a second day of completing an overhead drilling task suggested a potential kinematic learning effect.

Lower limb joint contact forces and ground reaction forces analysis based on Azure Kinect motion capture

Traditional gait analysis systems are typically complex to operate, lack portability, and involve high equipment costs. This study aims to establish a musculoskeletal dynamics calculation process driven by Azure Kinect. Building upon the full-body model of the Anybody musculoskeletal simulation software and incorporating a foot-ground contact model, the study utilized Azure Kinect-driven skeletal data from depth videos of 10 participants. The in-depth videos were prepossessed to extract keypoint of the participants, which were then adopted as inputs for the musculoskeletal model to compute lower limb joint angles, joint contact forces, and ground reaction forces. To validate the Azure Kinect computational model, the calculated results were compared with kinematic and kinetic data obtained using the traditional Vicon system. The forces in the lower limb joints and the ground reaction forces were normalized by dividing them by the body weight. The lower limb joint angle curves showed a strong correlation with Vicon results (mean ρ values: 0.78 ~ 0.92) but with root mean square errors as high as 5.66°. For lower limb joint force prediction, the model exhibited root mean square errors ranging from 0.44 to 0.68, while ground reaction force root mean square errors ranged from 0.01 to 0.09. The established musculoskeletal dynamics model based on Azure Kinect shows good prediction capabilities for lower limb joint forces and vertical ground reaction forces, but some errors remain in predicting lower limb joint angles.

The effects of fatigue on the relationship between ankle angle at initial contact and the knee and hip joints in landing: Assessing the risk of ACL injury

BackgroundAnterior cruciate ligament (ACL) injuries may correlate with lower limb angles and biomechanical factors in both dominant and non-dominant legs at initial contact (IC) post-landing. This study aims to investigate the correlation between ankle angles in three axes at IC and knee and hip joint angles during post-spike landings in professional volleyball players, both pre- and post-fatigue induction. Research questionTo what extent does fatigue influence lower limb joint angles, and what is the relationship between ankle joint angles and hip and knee angles at IC during the landing phase following a volleyball spike? MethodsUnder conditions involving the peripheral fatiguing protocol, the lower limb joint angles at IC following post-spike landings were measured in 28 professional male volleyball players aged between 19 and 28 years, who executed the Bosco fatigue protocol both before and after inducing fatigue. A paired t-test was utilized to compare the joint angles pre- and post-fatigue in both dominant and non-dominant legs. Furthermore, Pearson's correlation test was conducted to explore the relationship between ankle angles at IC and the corresponding knee and hip joint angles. ResultsThe findings of the study revealed that fatigue significantly increased hip external rotation and decreased knee joint flexion and external rotation in both the dominant and non-dominant legs (p < 0.05). Additionally, correlation analysis demonstrated that the ankle joint's positioning in the frontal and horizontal planes was significantly associated with hip flexion and external rotation at the IC, as well as with knee flexion and rotation (0.40 < r < 0.80). ConclusionFatigue increased hip external rotation and ankle internal rotation, weakening the correlation between these joints while strengthening the ankle-knee relationship, indicating a reduced hip control in jumps. This suggests a heightened ACL injury risk in the dominant leg due to the weakened ankle-hip connection, contrasting with the non-dominant leg.

Smartphone videos-driven musculoskeletal multibody dynamics modelling workflow to estimate the lower limb joint contact forces and ground reaction forces.

The estimation of joint contact forces in musculoskeletal multibody dynamics models typically requires the use of expensive and time-consuming technologies, such as reflective marker-based motion capture (Mocap) system. In this study, we aim to propose a more accessible and cost-effective solution that utilizes the dual smartphone videos (SPV)-driven musculoskeletal multibody dynamics modeling workflow to estimate the lower limb mechanics. Twelve participants were recruited to collect marker trajectory data, force plate data, and motion videos during walking and running. The smartphone videos were initially analyzed using the OpenCap platform to identify key joint points and anatomical markers. The markers were used as inputs for the musculoskeletal multibody dynamics model to calculate the lower limb joint kinematics, joint contact forces, and ground reaction forces, which were then evaluated by the Mocap-based workflow. The root mean square error (RMSE), mean absolute deviation (MAD), and Pearson correlation coefficient (ρ) were adopted to evaluate the results. Excellent or strong Pearson correlations were observed in most lower limb joint angles (ρ = 0.74 ~ 0.94). The averaged MADs and RMSEs for the joint angles were 1.93 ~ 6.56° and 2.14 ~ 7.08°, respectively. Excellent or strong Pearson correlations were observed in most lower limb joint contact forces and ground reaction forces (ρ = 0.78 ~ 0.92). The averaged MADs and RMSEs for the joint lower limb joint contact forces were 0.18 ~ 1.07 bodyweight (BW) and 0.28 ~ 1.32 BW, respectively. Overall, the proposed smartphone video-driven musculoskeletal multibody dynamics simulation workflow demonstrated reliable accuracy in predicting lower limb mechanics and ground reaction forces, which has the potential to expedite gait dynamics analysis in a clinical setting.

Effects of Anterior Cruciate Ligament Reconstruction on Lower Limb Joint Angle and Shock Absorption Pattern of Adult Males during Single-Leg Drop Landing

PURPOSE This study analyzed the difference in lower extremity joint angle and shock absorption patterns at the point of maximum ground reaction force during single-leg drop landing with or without anterior cruciate ligament reconstruction (ACLR).METHODS Forty adult males were recruited for this study, with 19 in the ACLR group (age: 20.52±1.43years, height: 179.26±5.18cm, weight: 74.91±6.29kg) and 21 in the control group (age: 21.42±1.61years, height: 174.97±6.83cm, weight: 69.27±7.56kg). Participants performed single-leg landings on a 30cm tall box. An independent sample t-test was used to analyze the difference in kinetics variables at the point of maximum ground reaction force upon landing, with significance set at &lt;i&gt;p&lt;/i&gt;=0.05.RESULTS The lower limb joint angle showed significant differences in hip flexion, hip abduction, knee flexion, and knee valgus (&lt;i&gt;p&lt;/i&gt;&lt;0.05) between groups. There was no significant difference between the groups in terms of the results of kinetics variables during single-leg landing (maximum ground reaction force, lower extremity stiffness, and shock absorption time).CONCLUSIONS The ACLR group showed a clear difference in kinematics compared to the control group, but no significant difference in kinetic results was found. The two groups compensated for the same impact with different movements, though movements in the ACLR group may increase the risk of ACL re-injury. Those with ACLR should strive to reduce the risk of re-injury by training to use correct movements.

Effects of overweight and obesity on lower limb walking characteristics from joint kinematics to muscle activations

BackgroundObesity is a crucial factor that increases the risk of initiating and advancing knee osteoarthritis. However, it remains unclear how obesity directly impacts the biomechanical experience of the lower limb joints, potentially triggering or exacerbating joint degeneration. This study investigated the interactive effects of BMI augmentation on lower limb kinematics, kinetics, and muscle activations during walking. MethodologyA group of 60 participants underwent a three-dimensional gait analysis. These individuals were categorized into three groups based on their body mass index (BMI): those with a BMI below 25 were classified as having a healthy weight, those with a BMI between 25 and 30 were categorized as overweight, and those with a BMI exceeding 30 were considered obese. This study analyzed the gait of 60 participants categorized by BMI. During walking trials, they recorded ground reaction forces electromyography of leg muscles like the gastrocnemii, hamstrings, and quadriceps. Lower limb joint angles and net moments were also calculated. Statistical mapping identified variations in kinematic, kinetic, and muscle activation patterns across the stance phase between BMI groups. ResultsThe results displayed distinct biomechanical patterns in obese individuals. Notably, there was a significant increase in flexion observed in the hip and knee joints (P < 0.001) during the initial stance phase and an increase in hip and knee adduction angles and moments throughout the entire stance phase (P < 0.001). Additionally, muscle activations underwent significant changes (P < 0.01), with a positive correlation noted with the BMI factor. This correlation was most pronounced during the early stance phase for the quadriceps and hamstring muscles and the late stance phase for the gastrocnemius. ConclusionThese findings represent a comprehensive picture that contributes to understanding how excess weight and obesity influence joint biomechanics, highlighting the associated risk of joint osteoarthritis.

Photogrammetric analysis of limb joint angles in cows with normal gait before and after hoof trimming

The aim of this study was to evaluate the effect of hoof trimming on overall limb movements by comparing the changes in 8 limb joint angles before and after one week of hoof trimming. Seventeen Holstein-Friesian dairy cows that were able to move freely and had no history of hoof diseases were included in the study. The cows were walked on a rubber mat with a high friction coefficient (HFM) and a low friction coefficient by the spraying of sodium polyacrylate (LFM). A high-speed camera was set to 200 fps on the image analysis software, and the images of the cows that were given 15 reflective markers on their right side were captured while walking on the test mat. The tests were conducted before and after one week of hoof trimming, and the cows were trimmed by the functional hoof trimming method. With image analysis software, video clips of walking cows were confirmed visually and tracked during one gait cycle by each reflective marker attached to the hoof of the forelimb and hindlimb, after which the stance phase and swing phase were identified. The durations of the stance phase and swing phase of the forelimb and hindlimb, respectively, and the maximum, minimum, and range of motion (ROM) values of the 8 joint angles, shoulder joint, elbow joint, carpus joint, forelimb fetlock joint, hip joint, stifle joint, hock joint and hindlimb fetlock joint during one gait cycle were included in the analysis. The maximum and minimum angles of the hip and stifle joints were narrower after hoof trimming than before, although the ROM did not change and was clearer for HFM than for LFM. It was thought that the flexion of the proximal hindlimb would progress smoothly during walking after trimming.

Gait balance recovery after tripping: The influence of walking speed and ground inclination on muscle and joint function

Reactive lower limb muscle function during walking plays a key role in balance recovery following tripping, and ultimately fall prevention. The objective of this study was to evaluate muscle and joint function in the recovery limb during balance recovery after trip-based perturbations during walking. Twenty-four healthy participants underwent gait analysis while walking at slow, moderate and fast speeds over level, uphill and downhill inclines. Trip perturbations were performed randomly during stance, and lower limb kinematics, kinetics, and muscle contribution to the acceleration of the whole-body centre of mass (COM) were computed pre- and post-perturbation in the recovery limb. Ground slope and walking speed had a significant effect on lower limb joint angles, net joint moments and muscle contributions to support and propulsion during trip recovery (p < 0.05). Specifically, increasing walking speed during trip recovery significantly reduced hip extension in the recovery limb and increased knee flexion, particularly when walking uphill and at higher walking speeds (p < 0.05). Gluteus maximus played a critical role in providing support and forward propulsion of the body during trip recovery across all gait speeds and ground inclinations. This study provides a mechanistic link between muscle action, joint motion and COM acceleration during trip recovery, and underscores the potential of increased walking speed and ground inclination to increase fall risk, particularly in individuals prone to falling. The findings of this study may provide guidelines for targeted exercise therapy such as muscle strengthening for fall prevention.

Inclusion of a skeletal model partly improves the reliability of lower limb joint angles derived from a markerless depth camera

A single depth camera provides a fast and easy approach to performing biomechanical assessments in a clinical setting; however, there are currently no established methods to reliably determine joint angles from these devices. The primary aim of this study was to compare joint angles as well as the between-day reliability of direct kinematics to model-constrained inverse kinematics recorded using a single markerless depth camera during a range of clinical and athletic movement assessments.A secondary aim was to determine the minimum number of trials required to maximize reliability. Eighteen healthy participants attended two testing sessions one week apart. Tasks included treadmill walking, treadmill running, single-leg squats, single-leg countermovement jumps, bilateral countermovement jumps, and drop vertical jumps. Keypoint data were processed using direct kinematics as well as in OpenSim using a full-body musculoskeletal model and inverse kinematics. Kinematic methods were compared using statistical parametric mapping and between-day reliability was calculated using intraclass correlation coefficients, mean absolute error, and minimal detectable change. Keypoint-derived inverse kinematics resulted in significantly smaller hip flexion (range = −9 to −2°), hip abduction (range = −3 to −2°), knee flexion (range = −5° to −2°), and greater dorsiflexion angles (range = 6–15°) than direct kinematics. Both markerless kinematic methods had high between-day reliability (inverse kinematics ICC 95 %CI = 0.83–0.90; direct kinematics ICC 95 %CI = 0.80–0.93). For certain tasks and joints, keypoint-derived inverse kinematics resulted in greater reliability (up to 0.47 ICC) and smaller minimal detectable changes (up to 13°) than direct kinematics. Performing 2–4 trials was sufficient to maximize reliability for most tasks. A single markerless depth camera can reliably measure lower limb joint angles, and skeletal model-constrained inverse kinematics improves lower limb joint angle reliability for certain tasks and joints.

Relationship among the COM Motion, the Lower Extremity and the Trunk during the Squat.

Squatting is a common motion in activities of daily living and is frequently used in training programs. Squatting requires a shift of the body in both vertical and anterior-posterior directions. Postural control during squatting is considered a mixed strategy; however, details and roles of the trunk and lower limb joints are unclear. The purpose of this study was to investigate the relationship among the kinematics of the lower limb, the trunk and the center of mass (COM) descent during squatting. Twenty-six healthy young adults performed repeated parallel squats. Lower limb joint and trunk angles and the COM were analyzed using a 3D motion analysis system. We evaluated the relationship between the kinematics and the squat depth by performing correlation analysis and multiple linear regression analysis. The ankle was the first to reach its maximum angle, and the remaining joints reached their maximum angles at the maximum squat depth. The knee joint motion and the squat depth were significantly correlated and there was a correlation between the hip and the ankle joint motion and the anteroposterior displacement of the COM during squatting. Multivariate linear regression analysis indicated that squat depth was predicted by both the knee and ankle motion and that anteroposterior displacement of the COM was predicted by the hip, ankle, and knee joint motion. The knees contributed to the vertical COM motion during squatting, while the hips contributed to the COM motion in the anteroposterior direction. On the other hand, the ankles contributed to COM motions in both the vertical and anteroposterior directions during squatting.

Stroke walking and balance characteristics via principal component analysis

Balance impairment is associated gait dysfunction with several quantitative spatiotemporal gait parameters in patients with stroke. However, the link between balance impairments and joint kinematics during walking remains unclear. Clinical assessments and gait measurements using motion analysis system was conducted in 44 stroke patients. This study utilised principal component analysis to identify key joint kinematics characteristics of patients with stroke during walking using average joint angles of pelvis and bilateral lower limbs in every gait-cycle percentile related to balance impairments. Reconstructed kinematics showed the differences in joint kinematics in both paretic and nonparetic lower limbs that can be distinguished by balance impairment, particularly in the sagittal planes during swing phase. The impaired balance group exhibited greater joint variability in both the paretic and nonparetic limbs in the sagittal plane during entire gait phase and during terminal swing phase respectively compared with those with high balance scores. This study provides a more comprehensive understanding of stroke hemiparesis gait patterns and suggests considering both nonparetic and paretic limb function, as well as bilateral coordination in clinical practice. Principal component analysis can be a useful assessment tool to distinguish differences in balance impairment and dynamic symmetry during gait in patients with stroke.

Anterior-Posterior Center of Pressure Is Associated With Knee Extensor Moment During Landing After Anterior Cruciate Ligament Reconstruction.

A reduced knee extensor moment (KEM) in the involved limb and asymmetry in the KEM during landing tasks are observed after anterior cruciate ligament reconstruction (ACLR). There is limited information about the association of kinetic and kinematic parameters with the KEM during landing after ACLR. This study investigated the association of the anterior-posterior center of pressure (AP-COP) position, vertical ground reaction force (VGRF), and lower limb joint angles with the KEM during landing in female athletes following ACLR. Cross-sectional study. Twenty-two female athletes who underwent ACLR performed a drop vertical jump at 7.9 (1.7)months after surgery. We evaluated the KEM, AP-COP position, VGRF, and sagittal plane hip, knee, and ankle angles using a 3-dimensional motion analysis system with force plates. The peak KEM in the involved limb was significantly smaller than that in the uninvolved limb during landing (1.43 [0.33]N·m/kg/m vs 1.84 [0.41]Nm/kg/m, P = .001). The VGRF in the involved limb was significantly smaller than that in the uninvolved limb (11.9 [2.3]N/kg vs 14.6 [3.5]N/kg, P = .005). The limb symmetry index of the KEM was predicted by that of the VGRF (P < .001, R2 = .621, β = 0.800). The KEM was predicted by the AP-COP position in the involved limb (P = .015, R2 = .227, β = 0.513) and by the VGRF in the uninvolved limb (P = .018, R2 = .213, β = 0.500). No significant correlation was noted between the KEM and the lower limb joint angles. The AP-COP position and VGRF were associated with the KEM during landing. Evaluating the VGRF and AP-COP position, not the lower limb joint angles, may contribute to understanding the KEM during double-leg landing after ACLR in the clinical setting.

Comparing Lower Limb Joint Angles in Basketball Players With Dynamic Knee Valgus Deficiency in Different Positions

Comparing Lower Limb Joint Angles in Basketball Players With Dynamic Knee Valgus Deficiency in Different Positions

Mutual information between joint angles and toe height in healthy subjects

Understanding the relationship between the position of the foot and the lower limb joint angles during normal gait is critical for the identification of the mechanisms involved in pathological gait. In this article, we introduce a novel framework that characterizes this relationship using mutual information in healthy subjects. The nonlinear connection between these variables is quantified using mutual information, and the MINE algorithm is used for precise estimation. Several simulations over Gaussian bivariate random variables reveal that overfitting is a critical factor affecting mutual information estimations by MINE, and we propose a simple methodology to address this issue when using gait signals. Our findings indicate that the statistical dependency between joint angles and toe height is symmetrical between the limbs for healthy subjects. Additionally, our results show that the ipsilateral knee angle holds the most significant amount of information regarding the toe height. In simpler terms, this knee angle serves as the most reliable predictor for toe height, and vice versa. To further enhance our understanding, we have developed a mutual information reference profile that enables the comparison of how the relationship between these biomechanical variables evolves under pathological conditions. The findings have significant implications for gait analysis and may aid in the identification and understanding of gait abnormalities in various contexts, contributing to the advancement of biomechanical research and clinical applications.