Coordination Variability During Walking and Running in Individuals With and Without Patellofemoral Pain Part 1: Lower Limb Intersegmental Coordination Variability

Haghighat, Farzaneh; Rezaie, Mohammadreza; Ebrahimi, Samaneh; Shokouhyan, Seyed Mohammadreza; Motealleh, Alireza; Parnianpour, Mohammad

doi:10.1007/s40846-021-00603-5

Cited by 4 publications

(5 citation statements)

References 35 publications

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“…Since increased hip adduction has the potential to induce pain by putting stress on the PF joint in persons with PFP, the results of the present study (negative correlation between hip adduction and coordination variability) confirm the findings of those reporting reduced variability of coordinative patterns in the presence of PFP [19,[21][22][23][24]. After the theory proposed by Hamill [19], numerous biomechanical and motor control studies have suggested that coordination variability plays a functional role, and its absence indicates dysfunction in performing a task [14].…”

Section: Discussionsupporting

confidence: 84%

“…It is also suggested that the reduced variability of movement patterns causes the same joint structures to be exposed to continuous stress, which over time can result in PFP. Reduced variability is also suggested to limit the individual from responding to internal and external perturbations [ 18 , 19 , 23 , 24 , 37 ].…”

Section: Discussionmentioning

confidence: 99%

“…Reduced variability is proposed to cause the same area of the joint to be constantly exposed to pressure, resulting in excessive wear and tear of the articular structures and eventually overuse injuries [19]. Since then, more researches have been done based on this concept in different musculoskeletal injuries, including PFP [20][21][22][23][24].…”

mentioning

confidence: 99%

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The Correlation between Intersegmental Coordination Variability and Frontal Plane Hip Kinematics during Running in Persons with Patellofemoral Pain

2023

J Biomed Phys Eng

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Background: Despite the existing evidence indicating altered hip kinematics as well as the studies showing altered movement coordination variability in persons with patellofemoral pain (PFP), there is no study investigating the correlation between hip joint kinematic and movement coordination variability in persons with patellofemoral pain (PFP). Objective: This study aims to evaluate the correlation between peak hip adduction and variability of thigh frontal-shank transverse coordination during running in persons with PFP. Material and Methods: In this cross-sectional correlational study, kinematic data were collected from 34 females (17 with and 17 without PFP) aged 18-35 years during treadmill running at preferred and fixed speeds, each for 30 s. The continuous relative phase method was used to calculate the coordination of thigh frontal-shank transverse. To calculate the deviation phase as the variability of intersegmental coordination, the standard deviation of the ensemble continuous relative phase curve points was averaged. The parameters of interest were peak hip adduction and coordination variability of thigh frontal-shank transverse. The Pearson Correlation Coefficient (r) was used to calculate the correlation between the variables. Results: The Pearson correlation coefficient showed a significant negative correlation between the peak hip adduction angle and variability of thigh frontal– shank transverse during running at both fixed (r=-0.553, P <0.05) and preferred (r=-0.660, P <0.01) speeds in persons with PFP while the control group showed a small nonsignificant correlation (r<0.29, P >0.05). Conclusion: The results indicated that greater adduction of the hip joint in persons with PFP during running is contributed to lesser variability of thigh frontal-shank transverse.

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Section: Discussionsupporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

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The Correlation between Intersegmental Coordination Variability and Frontal Plane Hip Kinematics during Running in Persons with Patellofemoral Pain

2023

J Biomed Phys Eng

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“…There are various techniques for quantifying coordination variability [ 52 ], but the techniques chosen should be based on the research questions. When participants perform CM, the joint movements of their lower extremities exhibit a non-sinusoidal pattern (except for the sagittal plane movements of the hip joint) [ 53 ]. However, Vector coding permits tests with non-sinusoidal motion patterns and is therefore deemed more suitable for clinical testing [ 49 , 54 ].…”

Section: Methodsmentioning

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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“…Others advocated the importance of considering the sensory inputs, particularly in terms of weighting the various proprioceptive signals, a critical consideration in optimal postural control ( Gandevia et al, 1992 ; Lackner and DiZio, 2005 ; Carver et al, 2006 ). It is indeed well established that musculoskeletal injuries ( Haghighat et al, 2021a ; Haghighat et al, 2021b ; Haghighat et al, 2021c ; Haghighat et al, 2021d ; Davoudi et al, 2022a ), neuromusculoskeletal disease, such as stroke, Parkinson’s, Multiple Sclerosis, Chronic obstructive pulmonary disease ( Davoudi et al, 2022b ) and other psychological factors including anxiety, are associated with disrupting the function of the sensory systems ( Jamali et al, 2019 ; Dehmiyani et al, 2022 ). Change in sensory input function has also been observed among patients with NSLBP ( Newcomer et al, 2000 ).…”

Section: Introductionmentioning

confidence: 99%

Distinction of non-specific low back pain patients with proprioceptive disorders from healthy individuals by linear discriminant analysis

Shokouhyan

Davoudi

Hoviattalab

et al. 2022

Front. Bioeng. Biotechnol.

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The central nervous system (CNS) dynamically employs a sophisticated weighting strategy of sensory input, including vision, vestibular and proprioception signals, towards attaining optimal postural control during different conditions. Non-specific low back pain (NSLBP) patients frequently demonstrate postural control deficiencies which are generally attributed to challenges in proprioceptive reweighting, where they often rely on an ankle strategy regardless of postural conditions. Such impairment could lead to potential loss of balance, increased risk of falling, and Low back pain recurrence. In this study, linear and non-linear indicators were extracted from center-of-pressure (COP) and trunk sagittal angle data based on 4 conditions of vibration positioning (vibration on the back, ankle, none or both), 2 surface conditions (foam or rigid), and 2 different groups (healthy and non-specific low back pain patients). Linear discriminant analysis (LDA) was performed on linear and non-linear indicators to identify the best sensory condition towards accurate distinction of non-specific low back pain patients from healthy controls. Two indicators: Phase Plane Portrait ML and Entropy ML with foam surface condition and both ankle and back vibration on, were able to completely differentiate the non-specific low back pain groups. The proposed methodology can help clinicians quantitatively assess the sensory status of non-specific low back pain patients at the initial phase of diagnosis and throughout treatment. Although the results demonstrated the potential effectiveness of our approach in Low back pain patient distinction, a larger and more diverse population is required for comprehensive validation.

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Coordination Variability During Walking and Running in Individuals With and Without Patellofemoral Pain Part 1: Lower Limb Intersegmental Coordination Variability

Cited by 4 publications

References 35 publications

The Correlation between Intersegmental Coordination Variability and Frontal Plane Hip Kinematics during Running in Persons with Patellofemoral Pain

The Correlation between Intersegmental Coordination Variability and Frontal Plane Hip Kinematics during Running in Persons with Patellofemoral Pain

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

Distinction of non-specific low back pain patients with proprioceptive disorders from healthy individuals by linear discriminant analysis

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