Muscle coactivation during gait in children with and without cerebral palsy.

BACKGROUND: Children with Cerebral Palsy (CP) walk with an uncoordinated gait compared to Typically Developing (TD) children. This behavior may reflect greater muscle co-activation in the lower limb; however, findings are inconsistent, and the determinants of this construct are unclear. RESEARCH OBJECTIVES: (i) Compare lower-limb muscle co-activation during gait in children with, and without CP, and (ii) determine the extent to which muscle co-activation is influenced by electromyography normalization procedures and Gross Motor Function Classification System (GMFCS) class. METHODS: An electromyography system measured muscle activity in the rectus femoris, semitendinosus, gastrocnemius, and tibialis anterior muscles during walking in 46 children (19 CP, 27 TD). Muscle co-activation was calculated for the tibialis anterior-gastrocnemius (TA-G), rectus femoris-gastrocnemius (RF-G), and rectus femoris-semitendinosus (RF-S) pairings, both using root mean squared (RMS)-averaged and dynamically normalized data, during stance and swing. Mann-Whitney U and independent t-tests examined differences in muscle co-activation by group (CP vs. TD) and GMFCS class (CP only), while mean difference 95% bootstrapped confidence intervals compared electromyography normalization procedures. RESULTS: Using dynamically normalized data, the CP group had greater muscle co-activation for the TA-G and RF-G pairs during stance (p < 0.01). Using RMS-averaged data, the CP group had greater muscle co-activation for TA-G (stance and swing, p < 0.01), RF-G (stance, p < 0.05), and RF-S (swing, p < 0.01) pairings. Muscle co-activation calculated with dynamically normalized, compared to RMS-averaged data, were larger in the RF-S and RF-G (stance) pairs, but smaller during swing (RF-G). Children with CP classified as GMFCS II had greater muscle co-activation during stance in the TA-G pair (p < 0.05). SIGNIFICANCE: Greater muscle co-activation observed in children with CP during stance may reflect a less robust gait strategy. Although data normalization procedures influence muscle co-activation ratios, this behavior was observed independent of normalization technique.

Muscle co-contraction and co-activation in cerebral palsy during gait: A scoping review.

BACKGROUND: Cerebral palsy (CP) results from an injury to a developing brain. Muscle activation patterns during walking are disrupted in individuals with CP. Indeed, excessive muscle co-contraction or co-activation (MCo/MCa) is one of the characteristics of pathological gait. Although some researchers have studied MCo/MCa in individuals with CP during gait, inconsistent results limit our understanding of this literature. Increased knowledge of MCo/MCa patterns in individuals with CP may help the development of improved gait management approaches. RESEARCH QUESTION: This review aims to summarize MCo/MCa patterns while walking in individuals with CP across the existing literature and compare them with their healthy peers. METHODS: This study follows the Joanna Briggs Institute (JBI) guidelines and the recommendations presented in PRISMA Extension for Scoping Reviews (PRISMA-ScR). The recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for scoping Reviews statement were respected. The following databases were searched: MEDLINE (Ovid), EMBASE (Ovid), CINAHL Plus with Full Text (Ebsco), SPORTDiscus with Full Text (Ebsco), and Web of Science. RESULTS: Among 2545 identified studies, 21 studies remained after screening. In total, 337 participants with CP and 249 healthy participants were included. Both MCo and MCa terminologies are used for describing simultaneous muscle activation; however, when it is measured by electromyography (EMG), MCa terminology should be preferred to facilitate interpretation. A wide range of MCo/MCa patterns has been found across studies using different methodologies (e.g., gait protocol, computation methods). Finally, most of the included studies confirm that MCo/MCa is increased in individuals with CP during walking compared to controls. SIGNIFICANCE: This review identified missing concepts and common limitations in the literature which could be addressed in future research such as the association between MCo/MCa and gait deviations, and the most appropriate MCo/MCa computation method.

The effect of uneven surfaces on inter-joint coordination during walking in children with cerebral palsy.

Clinical gait analysis on uneven surfaces contributes to the ecological assessment of gait deviations of children with spastic cerebral palsy (CP). Walking on uneven surfaces requires specific motor strategies, which can be assessed by lower-limb kinematic and inter-joint coordination analyses. This study aimed to assess and compare kinematics and inter-joint coordination between children with CP and their typically developing (TD) peers when walking on even and two levels of uneven surfaces (medium and high). A total of 17 children with CP and 17 TD children (11.5 ± 3.5 and 10.4 ± 4.5 years old, respectively) were asked to complete 6-8 gait trials on a 4-m walkway of each surface (n = 3) in randomized blocks while fit with retro-reflective markers on their lower-limbs. Children with CP showed proximal gait adaptations (i.e., hip and knee) on uneven surfaces. Compared with the TD group, the CP group showed decreased hip extension during late stance (49-63%, d = 0.549, p < 0.001), and a more in-phase knee-hip coordination strategy during swing phase (75-84% of gait cycle, d = 1.035, p = 0.029 and 92-100%, d = 1.091, p = 0.030) when walking on an uneven (high), compared to even surface. This study provides a better understanding of kinematic strategies employed by children with spastic CP when facing typical daily life gait challenges. Further studies are needed to evaluate the benefits of integrating uneven surfaces in rehabilitation care.

The impact of outdoor walking surfaces on lower-limb coordination and variability during gait in healthy adults.

BACKGROUND: Inter-joint coordination and variability during gait provide insight into control and adaptability of the neuromuscular system. To date, coordination research has been restricted to laboratory settings, and it is unclear how these findings translate to real-world, outdoor walking environments. RESEARCH QUESTION: Compared to flat walking, to what extent do outdoor surfaces impact lower-limb inter-joint coordination and variability during gait, in healthy adults? METHODS: Data from inertial measurement units placed on the lower-back, thigh, and shank were extracted from thirty healthy young adults (15 females, 23.5 ± 4.2 years) during outdoor walking on flat (paved sidewalk); irregular (cobblestone, grass); sloped (slope-up, slope-down); and banked (banked-right, banked-left) surfaces. Sagittal joint angles for the right knee and hip were computed and partitioned by gait phase (stance and swing). Continuous Relative Phase analysis determined inter-joint coordination and variability for the knee-hip joint pair using Mean Absolute Relative Phase (MARP) and Deviation Phase (DP), respectively. One-way repeated measures ANOVAs tested surface effects. Post-hoc Bonferroni adjusted surface comparisons were assessed. RESULTS: Significant knee-hip surface effects were seen during all gait phases for MARP (p < 0.001) and DP (p ≤ 0.001). Compared to flat walking, grass prompted more in-phase coordination (smaller MARP) during stance and swing phase (p ≤ 0.003). Slope-up caused more in-phase coordination during stance (p < 0.001), while slope-down caused more out-of-phase coordination during stance and swing (p ≤ 0.003), compared to the flat surface. Sloped surfaces prompted more variable (larger DP) knee-hip coordination (p ≤ 0.001), compared to flat walking during stance and swing phase. SIGNIFICANCE: Compared to flat walking, changes in knee-hip coordination and variability were greatest on slope-up/slope-down surfaces. This could reflect greater changes in lower-limb kinematics on sloped surfaces and/or a neuromuscular response to the demands of a more challenging task.

Lower-limb joint-coordination and coordination variability during gait in children with cerebral palsy.

BACKGROUND: Children with cerebral palsy present with poor motor control, altering their ability to perform tasks such as walking. Continuous relative phase analysis is a popular method to quantify motor control impairments via inter-joint coordination and coordination variability; however, it has not been explored in children with cerebral palsy. METHODS: 45 children with cerebral palsy and 45 typically developing children walked while fit with retroreflective markers. Continuous relative phase analysis for knee-hip and ankle-knee joint pairs quantified inter-joint coordination and coordination variability. The Gait Profile Score estimated gait pathology. Group differences were assessed with unpaired t-tests for coordination amplitude and variability (knee-hip, ankle-knee) across gait events. For the cerebral palsy group, correlations assessed the relation between the gait profile score and coordination metrics. FINDINGS: The cerebral palsy group showed more in-phase patterns for knee-hip coupling compared to the typically developing group (initial contact, loading response, mid-stance, terminal swing) (p ≤ 0.03). The cerebral palsy group showed lower knee-hip coordination variability (mid-stance, mid-swing) (p ≤ 0.037) and lower ankle-knee coordination variability (initial contact, loading response, terminal swing) (p < 0.001). The gait profile score correlated weakly to moderately (r = [0.323-0.472]), and negatively with the knee-hip inter-joint coordination (initial contact, loading response, mid-stance, terminal swing) (p ≤ 0.042). INTERPRETATION: Children with cerebral palsy showed a more in-phase gait strategy during challenging transitional gait cycle phases (beginning and end) and less flexible and adaptable motor behaviors. Moreover, the correlation between in-phase joint patterns and increased gait deviations (gait profile score) reinforces the relevance of coordination analysis to assess motor control impairment.

Gait adaptations of individuals with cerebral palsy on irregular surfaces: A scoping review.

BACKGROUND: Individuals with cerebral palsy (CP) have a reduced ability to perform motor tasks such as walking. During daily walking, they are confronted with environmental constraints such as irregular surfaces (e.g., relief and uneven surfaces) which may require adaptations to maintain stability and avoid falls. Laboratory gait assessments are conventionally conducted under ideal conditions (e.g., regular and even surfaces) and may overlook subtle problems which may only present in challenging walking environments. Increased knowledge of adaptations to successfully navigate irregular surfaces may contribute to a better understanding of everyday walking barriers. RESEARCH QUESTION: This scoping review aims to describe gait adaptations to irregular surfaces in individuals with CP and contrast adaptations with those of healthy individuals. METHODS: This review followed the 6-stage Joanna Briggs Institute methodology and respected the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews statement. The MEDLINE, EMBASE, CINAHL, SPORTDiscus, and Web of Science databases were searched on March 2021. RESULTS: The research strategy identified 1616 studies published between 2014 and 2020, of which 10 were included after abstract and full-text screening. This review reported on 152 individuals with CP (diplegia: n = 117, hemiplegia: n = 35) and 159 healthy individuals. The included studies focused on spatial-temporal, kinematic, kinetic, and muscle activity parameters over relief, inclined, and staircase surfaces. 7/10 studies were conducted in laboratories, often using surfaces that are not representative of the real-world. The results suggest that for individuals with CP, adaptations on irregular surfaces differ from flat surface walking and across CP subtype. Moreover, individuals with CP present with typical and pathology-specific adaptations to irregular surfaces compared to healthy individuals. SIGNIFICANCE: This review highlights the clinical and research interest of focusing future studies on more ecologically valid data collection approaches and provides important recommendations to overcome research gaps in the existing literature.

Lower-limb coordination and variability during gait: The effects of age and walking surface.

BACKGROUND: Falls among community-dwelling older adults are often triggered by uneven walkways. Joint coordination and its variability change with age and may place older adults at risk of falling. It is unclear how irregular surfaces impact lower-limb joint coordination and if such changes are exacerbated by aging. RESEARCH QUESTION: To what extent do lower-limb inter-joint coordination and its variability, over flat and uneven brick walkways, differ between older and young healthy adults? METHODS: A motion-capture system collected kinematic data from walking trials on flat and uneven walkways in seventeen older (72.0 ±â€¯4.2 years) and eighteen younger (27.0 ±â€¯4.7 years) healthy adults. Continuous relative phase analyses were performed for the Knee-Hip and Ankle-Knee joint pairs. Mean Absolute Relative Phase (MARP) quantified coordination amplitude. Deviation Phase (DP) quantified coordinative variability. Two-way mixed ANOVA's tested for effects of age, surface, and age × surface interactions. RESULTS: Uneven surfaces prompted more in-phase MARP inter-joint coordination in adults during most gait phases (p ≤ 0.024). Age × surface interactions were observed during initial contact (Ankle-Knee: p = 0.021, Knee-Hip: p = 0.001) and loading response (Knee-Hip: p = 0.017), with post-hoc analyses showing coordination accentuated in older adults. Uneven surfaces induced higher DP in Knee-Hip (p = 0.017) and Ankle-Knee joint coupling (p < 0.001) during gait, largely independent of age. An age × surface interaction was observed during mid-swing (p = 0.050), with post-hoc analysis revealing increased variability in older adults. SIGNIFICANCE: More in-phase and variable lower-limb gait behavior was observed on uneven walkways. These differences were accentuated in older adults during early stance phase (more tightly coordinated) and mid-swing (more variable). This may reflect a cautious gait strategy on challenging walkways to maintain stability and help prevent falls.

Effect of walking surface, late-cueing, physiological characteristics of aging, and gait parameters on turn style preference in healthy, older adults.

Turning while walking is a crucial component of locomotion, often performed on irregular surfaces with little planning time. Turns can be difficult for some older adults due to physiological age-related changes. Two different turning strategies have been identified in the literature. During step turns, which are biomechanically stable, the body rotates about the outside limb, while for spin turns, generally performed with closer foot-to-foot distance, the inside limb is the main pivot point. Turning strategy preferences of older adults under challenging conditions remains unclear. The aim of this study was to determine how turning strategy preference in healthy older adults is modulated by surface features, cueing time, physiological characteristics of aging, and gait parameters. Seventeen healthy older adults (71.5 ±â€¯4.2 years) performed 90° turns for two surfaces (flat, uneven) and two cue conditions (pre-planned, late-cue). Gait parameters were identified from kinematic data. Measures of lower-limb strength, balance, and reaction-time were also recorded. Generalized linear (logistic) regression mixed-effects models examined the effect of (1) surface and cuing, (2) physiological characteristics of ageing, and (3) gait parameters on turn strategy preference. Step turns were preferred when the condition was pre-planned (p < 0.001) (model 1) and when the gait parameters of stride regularity and maximum acceleration decreased (p = 0.010 and p = 0.039, respectively) (model 3). Differences in turn strategy selection under dynamic conditions ought to be evaluated in future fall-risk research and rehabilitation utilizing real-world activity monitoring.

Machine learning algorithms can classify outdoor terrain types during running using accelerometry data.

BACKGROUND: Running is a popular physical activity that benefits health; however, running surface characteristics may influence loading impact and injury risk. Machine learning algorithms could automatically identify running surface from wearable motion sensors to quantify running exposures, and perhaps loading and injury risk for a runner. RESEARCH QUESTION: (1) How accurately can machine learning algorithms identify surface type from three-dimensional accelerometer sensors? (2) Does the sensor count (single or two-sensor setup) affect model accuracy? METHODS: Twenty-nine healthy adults (23.3 ±â€¯3.6 years, 1.8 ±â€¯0.1 m, and 63.6 ±â€¯8.5 kg) participated in this study. Participants ran on three different surfaces (concrete, synthetic, woodchip) while fit with two three-dimensional accelerometers (lower-back and right tibia). Summary features (n = 208) were extracted from the accelerometer signals. Feature-based Gradient Boosting (GB) and signal-based deep learning Convolutional Neural Network (CNN) models were developed. Models were trained on 90% of the data and tested on the remaining 10%. The process was repeated five times, with data randomly shuffled between train-test splits, to quantify model performance variability. RESULTS: All models and configurations achieved greater than 90% average accuracy. The highest performing models were the two-sensor GB and tibia-sensor CNN (average accuracy of 97.0 ±â€¯0.7 and 96.1 ±â€¯2.6%, respectively). SIGNIFICANCE: Machine learning algorithms trained on running data from a single- or dual-sensor accelerometer setup can accurately distinguish between surfaces types. Automatic identification of surfaces encountered during running activities could help runners and coaches better monitor training load, improve performance, and reduce injury rates.

Machine learning algorithms based on signals from a single wearable inertial sensor can detect surface- and age-related differences in walking.

The aim of this study was to investigate if a machine learning algorithm utilizing triaxial accelerometer, gyroscope, and magnetometer data from an inertial motion unit (IMU) could detect surface- and age-related differences in walking. Seventeen older (71.5 ±â€¯4.2 years) and eighteen young (27.0 ±â€¯4.7 years) healthy adults walked over flat and uneven brick surfaces wearing an inertial measurement unit (IMU) over the L5 vertebra. IMU data were binned into smaller data segments using 4-s sliding windows with 1-s step lengths. Ninety percent of the data were used as training inputs and the remaining ten percent were saved for testing. A deep learning network with long short-term memory units was used for training (fully supervised), prediction, and implementation. Four models were trained using the following inputs: all nine channels from every sensor in the IMU (fully trained model), accelerometer signals alone, gyroscope signals alone, and magnetometer signals alone. The fully trained models for surface and age outperformed all other models (area under the receiver operator curve, AUC = 0.97 and 0.96, respectively; p ≤ .045). The fully trained models for surface and age had high accuracy (96.3, 94.7%), precision (96.4, 95.2%), recall (96.3, 94.7%), and f1-score (96.3, 94.6%). These results demonstrate that processing the signals of a single IMU device with machine-learning algorithms enables the detection of surface conditions and age-group status from an individual's walking behavior which, with further learning, may be utilized to facilitate identifying and intervening on fall risk.

Gait adaptations of older adults on an uneven brick surface can be predicted by age-related physiological changes in strength.

BACKGROUND: Outdoor falls in community-dwelling older adults are often triggered by uneven pedestrian walkways. It remains unclear how older adults adapt to uneven surfaces typically encountered in the outdoor built-environment and whether these adaptations are associated to age-related physiological changes. RESEARCH QUESTION: The aims of this study were to (1) compare gait parameters over uneven and flat brick walkways, (2) evaluate the differences between older and young adults for these two surfaces, and (3) assess if physiological characteristics could predict adaptations in older adults. METHODS: Balance, strength, reaction-time, full-body marker positions, and acceleration signals from a trunk-mounted inertial measurement unit were collected in seventeen older (71.5 ±â€¯4.2 years) and eighteen young (27.0 ±â€¯4.7 years) healthy adults to compute lower-limb joint kinematics, spatio-temporal parameters, dynamic stability, and accelerometry-derived metrics (symmetry, consistency, and smoothness). RESULTS: Both groups increased hip flexion at foot-strike, while decreasing ankle dorsiflexion, margin of stability, symmetry, and consistency on the uneven, compared to flat, surface. Older, compared to young, adults showed a larger increase in knee flexion at foot-strike and a larger decrease in smoothness on the uneven surface. Only young adults decreased hip abduction on the uneven surface. Strength, not balance nor reaction-time, was the main predictor of hip abduction in older adults on both surfaces. SIGNIFICANCE: While older adults may be especially vulnerable, uneven surfaces negatively impact gait, irrespective of age, and could represent a risk to all pedestrians.

Aging may negatively impact movement smoothness during stair negotiation.

Stairs represent a barrier to safe locomotion for some older adults, potentially leading to the adoption of a cautious gait strategy that may lack fluidity. This strategy may be characterized as unsmooth; however, stair negotiation smoothness has yet to be quantified. The aims of this study were to assess age- and task-related differences in head and body center of mass (COM) acceleration patterns and smoothness during stair negotiation and to determine if smoothness was associated with the timed "Up and Go" (TUG) test of functional movement. Motion data from nineteen older and twenty young adults performing stair ascent, stair descent, and overground straight walking trials were analyzed and used to compute smoothness based on the log-normalized dimensionless jerk (LDJ) and the velocity spectral arc length (SPARC) metrics. The associations between TUG and smoothness measures were evaluated using Pearson's correlation coefficient (r). Stair tasks increased head and body COM acceleration pattern differences across groups, compared to walking (p < 0.05). LDJ smoothness for the head and body COM decreased in older adults during stair descent, compared to young adults (p ≤ 0.015) and worsened with increasing TUG for all tasks (-0.60 ≤ r ≤ -0.43). SPARC smoothness of the head and body COM increased in older adults, regardless of task (p < 0.001), while correlations showed improved SPARC smoothness with increasing TUG for some tasks (0.33 ≤ r ≤ 0.40). The LDJ outperforms SPARC in identifying age-related stair negotiation adaptations and is associated with performance on a clinical test of gait.

Are flexible flat feet associated with proximal joint problems in children?

The role of flexible flat feet (FF) in the development of musculoskeletal symptoms at joints proximal to the ankle is unclear. We undertook an observational study to investigate the relationship between foot posture and the proximal joints in children. It was hypothesised that reduced arch height would be associated with proximal joint symptoms and altered gait kinematics and kinetics particularly in the transverse plane at the hip and knee. Ninety-five children between the ages of 8-15 were recruited into this ethically approved study. Foot posture was classified using the arch height index (AHI). The frequency of knee and hip/back pain was documented, and each child underwent three dimensional gait analysis. Reduced arch height was associated with increased odds of knee symptoms (p<0.01) and hip/back symptoms (p=0.01). A flat foot posture was also significantly associated with a reduction in the second peak of the vertical ground reaction force (p=0.03), which concomitantly affected late stance hip and knee moments. A reduced AHI was also associated with increased pelvic retraction and increased knee valgus in midstance. No kinematic and kinetic parameter associated with a flat foot posture related to increased proximal joint symptoms in the FF group. Children with a flatter foot posture are more likely to have pain or discomfort at the knee, hip and back; however, the mechanisms by which this occurs remain unclear. Treating FF without explicit understanding of how it relates to symptoms is difficult, and further work in this area is required.

The relationship between quality of life and foot function in children with flexible flatfeet.

Flat feet in children are common, and at times symptomatic, but the relationship between function and symptoms or impairment is still unclear. We undertook a prospective, observational study comparing children with paediatric flexible flat foot (PFF) and children with neutral feet (NF) using three dimensional gait analysis (3DGA). It was hypothesised that children with PFF would demonstrate differences in both spatio-temporal parameters of gait and foot and ankle kinematics compared to the NF group and that these differences would correlate with impaired quality of life (QoL). The kinematic differences were expected to be most marked in hindfoot coronal plane motion and forefoot sagittal and transverse plane motion. Eighty-three children between the ages of 8 and 15 were recruited in this study: Forty-two were classified as having PFF and forty-one as NF. Each child underwent 3DGA and completed the Oxford Ankle Foot Questionnaire for Children (OxAFQ_C). Reduced OxAFQ_C physical domain scores in the PFF children were associated with slower walking speed (p=0.014) and reduced normalised stride length (p=0.008). PFF children also demonstrated significantly increased hindfoot eversion and forefoot supination during gait. Significant differences between groups were not observed for other foot and ankle joint motions. Increased maximum hindfoot eversion and increased forefoot supination correlated strongly with lower QoL scores in PFF children. These data further our understanding of the functional characteristics that lead to impaired QoL in PFF children. These findings will help guide the surveillance and management of children with this ubiquitous condition.

The use of regression and normalisation for the comparison of spatio-temporal gait data in children.

Spatio-temporal parameters (STPs) are fundamental gait measures often used to compare children of different ages or gait ability. In the first case, non-dimensional normalisation (ND) of STPs using either leg-length or height is frequently conducted even though the process may not remove known inter-subject variability. STPs of children with and without disability can be compared through matched databases or using regression driven prediction. Unfortunately, database assignment is largely arbitrary and previous regressions have employed too few parameters to be successful. Therefore, the aims of this study were to test how well actual and ND STPs could be predicted from anthropometrics and speed and to assess if self-selected speed could be predicted from anthropometrics using multivariate regression in a cohort of eighty-nine typically developing children. Equations were validated on an extraneous dataset. We found that equations for actual step length, stride length, and cadence explained more than 84% of the variance compared to their ND counterparts. Moreover, only leg-length ND versions of these parameters were linearly proportional to speed. Prediction of single and double limb support times was weaker (R(2)=0.69 and 0.72, respectively) and we were unable to predict self-selected speed (R(2)<0.16) suggesting the use of anthropometrics is inappropriate for this purpose. Validation was successful for most STPs except in children lying near or outside the normal ranges and for gait speed. Clinically, regression could be used to quantify the difference between a patient's actual and theoretical STPs, allowing for monitoring of progress pre- and post intervention.