The Effect of Fatigue on Lower Limb Joint Stiffness at Different Walking Speeds

Shao, Enze; Lu, Zhenghui; Cen, Xuanzhen; Zheng, Zhiyi; Sun, Dong; Gu, Yaodong

doi:10.3390/diagnostics12061470

Cited by 6 publications

(5 citation statements)

References 67 publications

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“…Notably, the difference in cA was more pronounced in the knee than in the hip for patients with different stiffness levels, a finding that appears somewhat inconsistent with the quantitative assessment results. This inconsistency may be attributed to the fact that although the knee is the primary site of stiffness manifestation in KOA patients, individuals with joint stiffness often face a higher level of limitation in physical function ( 54 , 55 ). Consequently, they are more likely to exhibit more significant differences in the hip during qualitative analysis.…”

Section: Discussionmentioning

confidence: 99%

Exploring the potential of the sit-to-stand test for self-assessment of physical condition in advanced knee osteoarthritis patients using computer vision

Zhao,

Yang,

Qin

et al. 2024

Front. Public Health

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IntroductionKnee osteoarthritis (KOA) is a prevalent condition often associated with a decline in patients’ physical function. Objective self-assessment of physical conditions poses challenges for many advanced KOA patients. To address this, we explored the potential of a computer vision method to facilitate home-based physical function self-assessments.MethodsWe developed and validated a simple at-home artificial intelligence approach to recognize joint stiffness levels and physical function in individuals with advanced KOA. One hundred and four knee osteoarthritis (KOA) patients were enrolled, and we employed the WOMAC score to evaluate their physical function and joint stiffness. Subsequently, patients independently recorded videos of five sit-to-stand tests in a home setting. Leveraging the AlphaPose and VideoPose algorithms, we extracted time-series data from these videos, capturing three-dimensional spatiotemporal information reflecting changes in key joint angles over time. To deepen our study, we conducted a quantitative analysis using the discrete wavelet transform (DWT), resulting in two wavelet coefficients: the approximation coefficients (cA) and the detail coefficients (cD).ResultsOur analysis specifically focused on four crucial joint angles: “the right hip,” “right knee,” “left hip,” and “left knee.” Qualitative analysis revealed distinctions in the time-series data related to functional limitations and stiffness among patients with varying levels of KOA. In quantitative analysis, we observed variations in the cA among advanced KOA patients with different levels of physical function and joint stiffness. Furthermore, there were no significant differences in the cD between advanced KOA patients, demonstrating different levels of physical function and joint stiffness. It suggests that the primary difference in overall movement patterns lies in the varying degrees of joint stiffness and physical function among advanced KOA patients.DiscussionOur method, designed to be low-cost and user-friendly, effectively captures spatiotemporal information distinctions among advanced KOA patients with varying stiffness levels and functional limitations utilizing smartphones. This study provides compelling evidence for the potential of our approach in enabling self-assessment of physical condition in individuals with advanced knee osteoarthritis.

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Section: Discussionmentioning

confidence: 99%

Exploring the potential of the sit-to-stand test for self-assessment of physical condition in advanced knee osteoarthritis patients using computer vision

Zhao,

Yang,

Qin

et al. 2024

Front. Public Health

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“…Notably, we did not find coordinated deformable differences in the three different directions between 0% and 25% stride (e.g., Figure 4 ), so it can be assumed that whatever direction of CM may all have a high risk of injury during this period [ 71 , 72 ]. In addition, during CM in heel-strike mode, the knee joint plays a significant role, and the absorbed energy is redistributed and absorbed by the knee extensors [ 73 ]. In light of this, the functionality of the knee joint is crucial at such high mechanical intensities.…”

Section: Discussionmentioning

confidence: 99%

Predicting Coordination Variability of Selected Lower Extremity Couplings during a Cutting Movement: An Investigation of Deep Neural Networks with the LSTM Structure

Shao

Mei

et al. 2022

Bioengineering

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There are still few portable methods for monitoring lower limb joint coordination during the cutting movements (CM). This study aims to obtain the relevant motion biomechanical parameters of the lower limb joints at 90°, 135°, and 180° CM by collecting IMU data of the human lower limbs, and utilizing the Long Short-Term Memory (LSTM) deep neural-network framework to predict the coordination variability of selected lower extremity couplings at the three CM directions. There was a significant (p < 0.001) difference between the three couplings during the swing, especially at 90° vs the other directions. At 135° and 180°, t13-he coordination variability of couplings was significantly greater than at 90° (p < 0.001). It is important to note that the coordination variability of Hip rotation/Knee flexion-extension was significantly higher at 90° than at 180° (p < 0.001). By the LSTM, the CM coordination variability for 90° (CMC = 0.99063, RMSE = 0.02358), 135° (CMC = 0.99018, RMSE = 0.02465) and 180° (CMC = 0.99485, RMSE = 0.01771) were accurately predicted. The predictive model could be used as a reliable tool for predicting the coordination variability of different CM directions in patients or athletes and real-world open scenarios using inertial sensors.

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“…The results show that the motion amplitude of the hip joint is the smallest, the motion amplitude of the knee joint and the ankle joint is larger and the peak angle shows a stable lag change compared with At the same time, considering that the knee joint is more vulnerable to injury than the ankle joint in actual activities [32,33], and the ankle joint bears most of the body's gravity in daily actions, so the joint rehabilitation is clinically suitable for resting and drug treatment, so this paper further selects the hip joint and knee joint to analyze the movement law in lower limb rehabilitation training.…”

Section: Establishment Of the Dynamic Simulation Modelmentioning

confidence: 99%

“…At the same time, considering that the knee joint is more vulnerable to injury than the ankle joint in actual activities [32, 33], and the ankle joint bears most of the body’s gravity in daily actions, so the joint rehabilitation is clinically suitable for resting and drug treatment, so this paper further selects the hip joint and knee joint to analyze the movement law in lower limb rehabilitation training.…”

Section: Dynamics Modeling and Simulation Of Lower Limb Active Trainingmentioning

confidence: 99%

Research and experiment on active training of lower limb based on five-bar mechanism of man-machine integration system

Sun,

Hu,

Gao

et al. 2024

Robotica

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In view of the fact that the current research on active and passive rehabilitation training of lower limbs is mainly based on the analysis of exoskeleton prototype and the lack of analysis of the actual movement law of limbs, the human-machine coupling dynamic characteristics for active rehabilitation training of lower limbs are studied. In this paper, the forward and inverse kinematics are solved on the basis of innovatively integrating the lower limb and rehabilitation prototype into a human-machine integration system and equivalent to a five-bar mechanism. According to the constraint relationship of hip joint, knee joint and ankle joint, the Lagrange dynamic equation and simulation model of five-bar mechanism under the constraint of human physiological joint motion are constructed, and the simulation problem of closed-loop five-bar mechanism is solved. The joint angle experimental system was built to carry out rehabilitation training experiments to analyze the relationship between lower limb error and height, weight and BMI, and then, a personalized training planning method suitable for people with different lower limb sizes was proposed. The reliability of the method is proved by experiments. Therefore, we can obtain the law of limb movement on the basis of traditional rehabilitation training, appropriately reduce the training speed or reduce the man-machine position distance and reduce the training speed or increase the man-machine distance to reduce the error to obtain the range of motion angle closer to the theory of hip joint and knee joint respectively, so as to achieve better rehabilitation.

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The Effect of Fatigue on Lower Limb Joint Stiffness at Different Walking Speeds

Cited by 6 publications

References 67 publications

Exploring the potential of the sit-to-stand test for self-assessment of physical condition in advanced knee osteoarthritis patients using computer vision

Exploring the potential of the sit-to-stand test for self-assessment of physical condition in advanced knee osteoarthritis patients using computer vision

Predicting Coordination Variability of Selected Lower Extremity Couplings during a Cutting Movement: An Investigation of Deep Neural Networks with the LSTM Structure

Research and experiment on active training of lower limb based on five-bar mechanism of man-machine integration system

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