Biomechanical influences of gait patterns on knee joint: Kinematic & EMG analysis

Equinus deformity of the foot is a common feature of hemiplegia, which impairs the gait pattern of patients. The aim of the present study was to explore the role of ankle-foot deformity in gait impairment. A hierarchical cluster analysis was used to classify the gait patterns of 49 chronic hemiplegic patients with equinus deformity of the foot, based on temporal-distance parameters and joint kinematic measures obtained by an innovative protocol for motion assessment in the sagittal, frontal, and transverse planes, synthesized by parametrical analysis. Cluster analysis identified five subgroups of patients with homogenous levels of dysfunction during gait. Specific joint kinematic abnormalities were found, according to the speed of progression in each cluster. Patients with faster walking were those with less ankle-foot complex impairment or with reduced range of motion of ankle-foot complex, that is with a stiff ankle-foot complex. Slow walking was typical of patients with ankle-foot complex instability (i.e., larger motion in all the planes), severe equinus and hip internal rotation pattern, and patients with hip external rotation pattern. Clustering of gait patterns in these patients is helpful for a better understanding of dysfunction during gait and delivering more targeted treatment.

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Comparing the Knee Joint Kinematic Parameters During Landing at Different Minutes of Soccer Game

Journal of Sport Biomechanics ◽

10.32598/biomechanics.5.1.1 ◽

2019 ◽

pp. 2-13

Author(s):

Abdolrasoul Daneshjoo ◽

Maryam Mohseni

Keyword(s):

Knee Joint ◽

Kinematic Parameters ◽

Joint Kinematic ◽

Soccer Game

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An Electromyogram-Driven Musculoskeletal Model of the Knee to Predict in Vivo Joint Contact Forces During Normal and Novel Gait Patterns

Journal of Biomechanical Engineering ◽

10.1115/1.4023457 ◽

2013 ◽

Vol 135 (2) ◽

Cited By ~ 64

Author(s):

Kurt Manal ◽

Thomas S. Buchanan

Keyword(s):

Knee Joint ◽

Contact Force ◽

Contact Forces ◽

Grand Challenge ◽

Normal Walking ◽

Gait Patterns ◽

Internal Joint ◽

Model Predictions ◽

Joint Contact

Computational models that predict internal joint forces have the potential to enhance our understanding of normal and pathological movement. Validation studies of modeling results are necessary if such models are to be adopted by clinicians to complement patient treatment and rehabilitation. The purposes of this paper are: (1) to describe an electromyogram (EMG)-driven modeling approach to predict knee joint contact forces, and (2) to evaluate the accuracy of model predictions for two distinctly different gait patterns (normal walking and medial thrust gait) against known values for a patient with a force recording knee prosthesis. Blinded model predictions and revised model estimates for knee joint contact forces are reported for our entry in the 2012 Grand Challenge to predict in vivo knee loads. The EMG-driven model correctly predicted that medial compartment contact force for the medial thrust gait increased despite the decrease in knee adduction moment. Model accuracy was high: the difference in peak loading was less than 0.01 bodyweight (BW) with an R2 = 0.92. The model also predicted lateral loading for the normal walking trial with good accuracy exhibiting a peak loading difference of 0.04 BW and an R2 = 0.44. Overall, the EMG-driven model captured the general shape and timing of the contact force profiles and with accurate input data the model estimated joint contact forces with sufficient accuracy to enhance the interpretation of joint loading beyond what is possible from data obtained from standard motion capture studies.

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