Age-related changes in trunk muscle activity and spinal and lower limb kinematics during gait

Crawford, Rebecca; Gizzi, Leonardo; Dieterich, Anja; Mhuiris, Áine Ni; Falla, Deborah

doi:10.1371/journal.pone.0206514

Cited by 21 publications

(20 citation statements)

References 52 publications

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“…This muscular activity during one gait cycle may not be consistent with CCI shown in the previous study, but there is no doubt that the co-contraction functions of at least the left and right internal oblique muscles were reduced. A previous study has reported that the muscle activity time of the internal oblique muscle is prolonged [17], and the CCI of the back-extensor muscles is increased during walking in healthy elderly individuals [18]. Considering these reports, this study showed that the CCI of elderly patients with hip OA was less than, indicating the opposite characteristics to those in healthy elderly individuals.…”

Section: Discussionmentioning

confidence: 49%

“…There were no significant differences in the activities of the left and right internal oblique muscles during each phase of the walking cycle in patients with hip OA; however, their muscle activity levels were significantly greater than those of healthy individuals. Furthermore, in line with this finding, Crawford et al [17] reported no age difference in the peak activity of the internal oblique muscles during walking in healthy adults. Therefore, the result of this study may be unique to hip OA patients.…”

Section: Discussionmentioning

confidence: 62%

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Characteristics of internal oblique muscle activity during walking in healthy and patients with hip osteoarthritis

Okazawa¹,

Katoh²

2019

Phys Ther Rehabil

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Background and purpose: In a clinical setting, patients with hip osteoarthritis often complain of trunk instability during the gait, therefore, this study aims to determine the characteristics of left and right internal oblique muscle activities during walking in healthy individuals and patients with hip osteoarthritis (OA). Methods: Participants included 17 healthy males and 10 (2 males and 8 female) with hip OA. The characteristics of muscle activity in one walking cycle were compared using integrated EMG analysis (% IEMG) and co-contraction index (CCI), which is an index of simultaneous muscles. Results: The %IEMG and CCI values were greater and less, respectively, in patients with hip OA than in healthy individuals. Conclusion: It is important to increase the CCI of the left and right internal oblique muscles to improve the trunk stability during walking in patients with hip OA.

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Section: Discussionmentioning

confidence: 49%

Section: Discussionmentioning

confidence: 62%

Characteristics of internal oblique muscle activity during walking in healthy and patients with hip osteoarthritis

Okazawa¹,

Katoh²

2019

Phys Ther Rehabil

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“…With increased gait speed, trunk perturbation also increases. Accordingly, muscle activity on electromyography should be higher 18 ) and the pelvic rotation should increase 26 ) . Crawford et al 26 ) showed that elderly individuals have a larger perturbation of trunk rotation and longitudinal direction with increased gait speed as compared to younger ones.…”

Section: Discussionmentioning

confidence: 99%

Relationship between gait speed and trunk muscles in frail elderly individuals

Noguchi

Jiroumaru²,

Wachi³

et al. 2021

J Phys Ther Sci

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The external and internal abdominal muscles may be related to gait speed; however, this has not yet been elucidated. In this study, we aimed to clarify the relationship between gait speed and trunk muscle thickness in elderly individuals. [Participants and Methods] The participants were 12 elderly individuals (4 males and 8 females, mean age 83.4 years old, SD ± 0.5) that attend a day service center. We measured the 5 m free gait speed, the 5 m fastest gait speed, and the thickness of five trunk muscles (the rectus abdominis [divided into three parts: upper, central, and lower], external oblique, internal oblique, transverse abdominis, and iliopsoas muscles).[Results] There were positive correlations between the free gait speed and the thickness of the lower rectus abdominis, internal oblique, and transverse abdominis muscles. There were also positive correlations between the fastest gait speed and the thickness of the lower rectus abdominis, internal oblique, and transverse abdominis muscles.[Conclusion] Incorporating muscle strength training of the lower rectus abdominis, internal oblique, and transverse abdominis muscles into existing lower limb muscle training protocols is important to effectively maintain the gait speed of elderly individuals.

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“…Third, we did not include age as a predictor during model building even though individuals with LBP and rmLBP were significantly older than controls. Even though previous studies have reported age-related differences in movement and control strategies [50,51], these differences were examined between adult cohorts with ~ 40 years in age gap. Lastly, given the cross-sectional nature of this study, we view the current work through the lens of a "hypothesis generation" framework, where we explored the predictive value of functional kinematic and EMG variables in a LBP setting.…”

Section: Discussionmentioning

confidence: 99%

Interpretable machine learning models for classifying low back pain status using functional physiological variables

et al. 2020

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Purpose To evaluate the predictive performance of statistical models which distinguishes different low back pain (LBP) sub-types and healthy controls, using as input predictors the time-varying signals of electromyographic and kinematic variables, collected during low-load lifting. Methods Motion capture with electromyography (EMG) assessment was performed on 49 participants [healthy control (con) = 16, remission LBP (rmLBP) = 16, current LBP (LBP) = 17], whilst performing a low-load lifting task, to extract a total of 40 predictors (kinematic and electromyographic variables). Three statistical models were developed using functional data boosting (FDboost), for binary classification of LBP statuses (model 1: con vs. LBP; model 2: con vs. rmLBP; model 3: rmLBP vs. LBP). After removing collinear predictors (i.e. a correlation of > 0.7 with other predictors) and inclusion of the covariate sex, 31 predictors were included for fitting model 1, 31 predictors for model 2, and 32 predictors for model 3. Results Seven EMG predictors were selected in model 1 (area under the receiver operator curve [AUC] of 90.4%), nine predictors in model 2 (AUC of 91.2%), and seven predictors in model 3 (AUC of 96.7%). The most influential predictor was the biceps femoris muscle (peak = 0.047) in model 1, the deltoid muscle (peak = 0.052) in model 2, and the iliocostalis muscle (peak = 0.16) in model 3. Conclusion The ability to transform time-varying physiological differences into clinical differences could be used in future prospective prognostic research to identify the dominant movement impairments that drive the increased risk.

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Age-related changes in trunk muscle activity and spinal and lower limb kinematics during gait

Cited by 21 publications

References 52 publications

Characteristics of internal oblique muscle activity during walking in healthy and patients with hip osteoarthritis

Characteristics of internal oblique muscle activity during walking in healthy and patients with hip osteoarthritis

Relationship between gait speed and trunk muscles in frail elderly individuals

Interpretable machine learning models for classifying low back pain status using functional physiological variables

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