The gait standard deviation, a single measure of kinematic variability

Prediction of joint moments from kinematics using machine learning in children with congenital talipes equino varus and typically developing peers

Background

Understanding joint loading and the crucial role of joint moments is essential for developing treatment strategies in gait analysis, which often requires the precise estimation of joint moments through an inverse dynamic approach. This process necessitates the use of a force plate synchronized with a motion capture system. However, effectively capturing ground reaction force in typically developing (TD) children and those with congenital talipes equino varus (CTEV) presents challenges, while the availability and high cost of additional force plates pose additional challenges. Therefore the study aimed to develop, train, and identify the most effective machine learning (ML) model to predict joint moments from kinematics for TD children and those with CTEV.

Method

In a study at the Gait Lab, 13 children with bilateral CTEV and 17 TD children underwent gait analysis to measure kinematics and kinetics, using a 12-camera Qualisys Motion Capture System and an AMTI force plate. ML models were then trained to predict joint moments from kinematic data as input.

Results

The random forest regressor and deep neural networks (DNN) proved most effective in predicting joint moments from kinematics for TD children, yielding better results. The Random Forest regressor achieved an average r of 0.75 and nRMSE of 23.03 % for TD children, and r of 0.74 and 23.82 % for CTEV. DNN achieved an average r of 0.75 and nRMSE of 22.83 % for TD children, and r of 0.76 and nRMSE of 23.9 % for CTEV.

Conclusions

The findings suggest that using machine learning to predict joint moments from kinematics shows moderate potential as an alternative to traditional gait analysis methods for both TD children and those with CTEV. Despite its potential, the current prediction accuracy limitations hinder the immediate clinical application of these techniques for decision-making in a pediatric population.

Kinematic upper limb analysis outperforms electromyography at grading the severity of dystonia in children with cerebral palsy

BACKGROUND

Severity of dyskinesia in children with cerebral palsy is often assessed using observation-based clinical tools. Instrumented methods to objectively measure dyskinesia have been proposed to improve assessment accuracy and reliability. Here, we investigated the technique and movement features that were most suitable to objectively measure the severity of dystonia in children with cerebral palsy.

METHODS

A prospective observational study was conducted with 12 participants with cerebral palsy with a predominant motor type of dyskinesia, spasticity, or mixed dyskinesia/spasticity who had upper limb involvement (mean age: 12.6 years, range: 6.7-18.2 years). Kinematic and electromyography data were collected bilaterally during three upper limb tasks. Spearman rank correlations of kinematic or electromyography features were calculated against dystonia severity, quantified by the Dyskinesia Impairment Scale.

FINDINGS

Kinematic features were more influential compared to electromyography features at grading the severity of dystonia in children with cerebral palsy. Kinematic measures quantifying jerkiness of volitional movement during an upper limb task with a reaching component performed best (|rs| = 0.78-0.9, p < 0.001).

INTERPRETATION

This study provides guidance on the types of data, features of movement, and activity protocols that instrumented methods should focus on when objectively measuring the severity of dystonia in children with cerebral palsy.

Full-body kinematics and head stabilisation strategies during walking in patients with chronic unilateral and bilateral vestibulopathy

Chronic imbalance is a frequent and limiting symptom of patients with chronic unilateral and bilateral vestibulopathy. A full-body kinematic analysis of the movement of patients with vestibulopathy would provide a better understanding of the impact of the pathology on dynamic tasks such as walking. Therefore, this study aimed to investigate the global body movement during walking, its variability (assessed with the GaitSD), and the strategies to stabilise the head (assessed with the head Anchoring Index). The full-body motion capture data of 10 patients with bilateral vestibulopathy (BV), 10 patients with unilateral vestibulopathy (UV), and 10 healthy subjects (HS) walking at several speeds (slow, comfortable, and fast) were analysed in this prospective cohort study. We observed only a few significant differences between groups in parts of the gait cycle (shoulder abduction-adduction, pelvis rotation, and hip flexion-extension) during the analysis of kinematic curves. Only BV patients had significantly higher gait variability (GaitSD) for all three walking speeds. Head stabilisation strategies depended on the plan of motion and walking speed condition, but BV and UV patients tended to stabilise their head in relation to the trunk and HS tended to stabilise their head in space. These results suggest that GaitSD could be a relevant biomarker of chronic instability in BV and that the head Anchoring Index tends to confirm clinical observations of abnormal head-trunk dynamics in patients with vestibulopathy while walking.

Inter-trial variability is higher in 3D markerless compared to marker-based motion capture: Implications for data post-processing and analysis

Markerless motion capture has recently attracted significant interest in clinical gait analysis and human movement science. Its ease of use and potential to streamline motion capture recordings bear great potential for out-of-the-laboratory measurements in large cohorts. While previous studies have shown that markerless systems can achieve acceptable accuracy and reliability for kinematic parameters of gait, they also noted higher inter-trial variability of markerless data. Since increased inter-trial variability can have important implications for data post-processing and analysis, this study compared the inter-trial variability of simultaneously recorded markerless and marker-based data. For this purpose, the data of 18 healthy volunteers were used who were instructed to simulate four different gait patterns: physiological, crouch, circumduction, and equinus gait. Gait analysis was performed using the smartphone-based markerless system OpenCap and a marker-based motion capture system. We compared the inter-trial variability of both systems and also evaluated if changes in inter-trial variability may depend on the analyzed gait pattern. Compared to the marker-based data, we observed an increase of inter-trial variability for the markerless system ranging from 6.6% to 22.0% for the different gait patterns. Our findings demonstrate that the markerless pose estimation pipelines can introduce additionally variability in the kinematic data across different gait patterns and levels of natural variability. We recommend using averaged waveforms rather than single ones to mitigate this problem. Further, caution is advised when using variability-based metrics in gait and human movement analysis based on markerless data as increased inter-trial variability can lead to misleading results.

Can developmental trajectories in gait variability provide prognostic clues in motor adaptation among children with mild cerebral palsy? A retrospective observational cohort study

Aim

To investigate whether multiple domains of gait variability change during motor maturation and if this change over time could differentiate children with a typical development (TDC) from those with cerebral palsy (CwCP).

Methods

This cross-sectional retrospective study included 42 TDC and 129 CwCP, of which 99 and 30 exhibited GMFCS level I and II, respectively. Participants underwent barefoot 3D gait analysis. Age and parameters of gait variability (coefficient of variation of stride-time, stride length, single limb support time, walking speed, and cadence; as well as meanSD for hip flexion, knee flexion, and ankle dorsiflexion) were used to fit linear models, where the slope of the models could differ between groups to test the hypotheses.

Results

Motor-developmental trajectories of gait variability were able to distinguish between TDC and CwCP for all parameters, except the variability of joint angles. CwCP with GMFCS II also showed significantly higher levels of gait variability compared to those with GMFCS I, these levels were maintained across different ages.

Interpretation

This study showed the potential of gait variability to identify and detect the motor characteristics of high functioning CwCP. In future, such trajectories could provide functional biomarkers for identifying children with mild movement related disorders and support the management of expectations.

Complexity of locomotion activities in an outside-of-the-lab wearable motion capture dataset

Gait complexity is widely used to understand risk factors for injury, rehabilitation, the performance of assistive devices, and other matters of clinical interest. We analyze the complexity of out-of-the-lab locomotion activities via measures that have previously been used in gait analysis literature, as well as measures from other domains of data analysis. We categorize these broadly as quantifying either the intrinsic dimensionality, the variability, or the regularity, periodicity, or self-similarity of the data from a nonlinear dynamical systems perspective. We perform this analysis on a novel full-body motion capture dataset collected in out-of-the-lab conditions for a variety of indoor environments. This is a unique dataset with a large amount (over 24 h total) of data from participants behaving without low-level instructions in out-of-the-lab indoor environments. We show that reasonable complexity measures can yield surprising, and even profoundly contradictory, results. We suggest that future complexity analysis can use these guidelines to be more specific and intentional about what aspect of complexity a quantitative measure expresses. This will become more important as wearable motion capture technology increasingly allows for comparison of ecologically relevant behavior with lab-based measurements.

Are Clinical Impairments Related to Kinematic Gait Variability in Children and Young Adults With Cerebral Palsy?

Intrinsic gait variability (GV), i.e., fluctuations in the regularity of gait patterns between repetitive cycles, is inherent to the sensorimotor system and influenced by factors such as age and pathology. Increased GV is associated with gait impairments in individuals with cerebral palsy (CP) and has been mainly studied based on spatiotemporal parameters. The present study aimed to describe kinematic GV in young people with CP and its associations with clinical impairments [i.e., passive range of motion (pROM), muscle weakness, reduced selective motor control (selectivity), and spasticity]. This retrospective study included 177 participants with CP (age range 5-25 years; Gross Motor Function Classification System I-III) representing 289 clinical gait analyses [n = 172 for unilateral CP (uCP) vs. 117 for bilateral CP (bCP)]. As variability metrics, Root Mean Square Deviation (RMSD) for nine lower-limb kinematic parameters and Gait Standard Deviation (GaitSD) - as composite score of the kinematic parameters - were computed for the affected (unilateral = uCP) and most affected side (bilateral = bCP), respectively, as defined by clinical scores. GaitSD was then computed for the non/less-affected side for between leg comparisons. Uni- and multivariate linear regressions were subsequently performed on GaitSD of the affected/most affected side with all clinical impairments (composite scores) as independent variables. Highest RMSD were found in the transverse plane (hip, pelvis), for distal joints in the sagittal plane (knee, ankle) and for foot progression. GaitSD was not different between uCP and bCP (affected/most affected side) but higher in the non-affected vs. affected side in uCP. GaitSD was associated with age (p < 0.001), gait deviation index (GDI) (p < 0.05), muscle weakness (p < 0.001), selectivity (p < 0.05), and pROM (p < 0.001). After adjustment for age and GDI, GaitSD remained associated with muscle weakness (uCP: p = 0.003, bCP: p < 0.001) and selectivity (bCP: p = 0.024). Kinematic GV can be expressed as global indicator of variability (GaitSD) in young people with CP given the strong correlation of RMSD for lower-limb kinematic parameters. In terms of asymmetry, increased variability of the non-affected vs. affected side may indicate contralateral compensation mechanisms in uCP. Notably muscle weakness (uCP, bCP) and selectivity (bCP) - but not spasticity - were associated with GaitSD. Further studies need to explore the clinical relevance of kinematic GV in CP to support the interpretation of clinical gait analyses and therapeutic decision-making.

Overground Walking in a Fully Immersive Virtual Reality: A Comprehensive Study on the Effects on Full-Body Walking Biomechanics

Virtual reality (VR) is an emerging technology offering tremendous opportunities to aid gait rehabilitation. To this date, real walking with users immersed in virtual environments with head-mounted displays (HMDs) is either possible with treadmills or room-scale (overground) VR setups. Especially for the latter, there is a growing interest in applications for interactive gait training as they could allow for more self-paced and natural walking. This study investigated if walking in an overground VR environment has relevant effects on 3D gait biomechanics. A convenience sample of 21 healthy individuals underwent standard 3D gait analysis during four randomly assigned walking conditions: the real laboratory (RLab), a virtual laboratory resembling the real world (VRLab), a small version of the VRlab (VRLab-), and a version which is twice as long as the VRlab (VRLab+). To immerse the participants in the virtual environment we used a VR-HMD, which was operated wireless and calibrated in a way that the virtual labs would match the real-world. Walking speed and a single measure of gait kinematic variability (GaitSD) served as primary outcomes next to standard spatio-temporal parameters, their coefficients of variant (CV%), kinematics, and kinetics. Briefly described, participants demonstrated a slower walking pattern (-0.09 ± 0.06 m/s) and small accompanying kinematic and kinetic changes. Participants also showed a markedly increased gait variability in lower extremity gait kinematics and spatio-temporal parameters. No differences were found between walking in VRLab+ vs. VRLab-. Most of the kinematic and kinetic differences were too small to be regarded as relevant, but increased kinematic variability (+57%) along with increased percent double support time (+4%), and increased step width variability (+38%) indicate gait adaptions toward a more conservative or cautious gait due to instability induced by the VR environment. We suggest considering these effects in the design of VR-based overground training devices. Our study lays the foundation for upcoming developments in the field of VR-assisted gait rehabilitation as it describes how VR in overground walking scenarios impacts our gait pattern. This information is of high relevance when one wants to develop purposeful rehabilitation tools.

Reliability and sources of variability of 3D kinematics and electromyography measurements to assess newly-acquired gait in toddlers with typical development and unilateral cerebral palsy

The aim was to 1) determine intersession and intertrial reliability and 2) assess three sources of variability (intersubject, intersession and intertrial) of lower limb kinematic and electromyographic (EMG) variables during gait in toddlers with typical development (TD) and unilateral cerebral palsy (UCP) (age <3 years, independent walking experience ≤6 months). Gait kinematics and surface EMG were recorded in 30 toddlers (19 TD and 11 UCP), during two, 3D-motion capture sessions. Standard error of measurement (SEM) between trials (gait cycles) of the same session and between sessions was calculated to assess reliability. Standard deviations (SD) between subjects, sessions and trials were calculated to estimate sources of variability. Sixty-four percent of kinematic SEM-values were acceptable (2°-5°). Frontal plane measurements were most reliable (SEM 2°-4.6°). In toddlers with UCP, EMG variables were most reliable for affected side, distal muscles. Intrinsic (intertrial and intersubject) variability was high, reflecting both motor immaturity and the high variability of toddler gait patterns. In toddlers with UCP, variability was amplified by motor impairment and delayed motor development. 3D gait analysis and surface EMG are partially reliable tools to study individual gait patterns in toddlers in clinical practice and research, although some variables must be interpreted with caution.

Gait Variability and Relationships With Fear, Avoidance, and Pain in Adolescents With Chronic Pain

OBJECTIVE

Some children with chronic pain struggle with fear of pain, avoidance behaviors, and associated disability; however, movement adaptations in the context of chronic pain in childhood is virtually unknown. Variability in adaptive movement responses previously observed between individuals might be largely explained by the presence of problematic psychological drivers (eg, fear, avoidance). The goals of this study were to quantify the variability of gait and examine relationships among pain, fear, avoidance, function (perceived and objective), and gait variability.

METHODS

This study used a cross-sectional design. Eligible patients were between 8 and 17 years of age and had musculoskeletal, neuropathic, or headache pain that was not due to acute trauma (eg, active sprain) or any specific or systemic disease. Participants completed the Numeric Pain Rating Scale, Fear of Pain Questionnaire (FOPQ), Functional Disability Inventory, and 6-Minute Walk Test and received kinematic gait analysis. Relationships were analyzed among these measures, and the self-report and functional measures were examined to determine whether they predicted gait variability (GaitSD).

RESULTS

The 16 participants who were evaluated (13.8 [SD = 2.2] years of age; 13 female) had high Numeric Pain Rating Scale scores (6.2 [SD = 2.1]), FOPQ-Fear scores (25.9 [SD = 12.1]), FOPQ-Avoidance scores (22.8 [SD = 10.2]), and Functional Disability Inventory scores (28.6 [SD = 9.4]) and low 6-Minute Walk Test distance (437.1 m [SD = 144.6]). Participants had greater GaitSD than age-predicted norms. Fear was related to self-selected GaitSD, and avoidance was related to both self-selected and standardized GaitSD. Avoidance predicted 43% and 47% of the variability in self-selected and standardized GaitSD, respectively.

CONCLUSION

GaitSD was significantly related to both fear of pain and avoidance behaviors, suggesting the interplay of these psychological drivers with movement. FOPQ-Avoidance was robust in accounting for GaitSD.

IMPACT

This study offers preliminary evidence in understanding movement adaptations associated with adolescents with chronic pain. They may lend to more directed interventions.

A Decision Support System to Facilitate Identification of Musculoskeletal Impairments and Propose Recommendations Using Gait Analysis in Children With Cerebral Palsy

The identification of musculoskeletal impairments from gait analysis in children with cerebral palsy is a complex task, as is formulating (surgical) recommendations. In this paper, we present how we built a decision support system based on gait kinematics, anthropometrics, and physical examination data. The decision support system was trained to learn the association between these data and the list of impairments and recommendations formulated historically by experienced clinicians. Our aim was 2-fold, train a computational model that would be representative of data-based clinical reasoning in our center, and support new or junior clinicians by providing pre-processed impairments and recommendations with the associated supportive evidence. We present some of the challenges we faced, such as the issues of dimensionality reduction for kinematic data, missing data imputations, class imbalance and choosing an appropriate model evaluation metric. Most models, i.e., one model for each impairments and recommendations, achieved a weighted Brier score lower than 0.20, and sensitivity and specificity greater than 0.70 and 0.80, respectively. The results of the models are accessible through a web-based application which displays the probability predictions as well as the (up to) 5 best predictors.

Prodromal Spinocerebellar Ataxia Type 2 Subjects Have Quantifiable Gait and Postural Sway Deficits

BACKGROUND

The search for valid preclinical biomarkers of cerebellar dysfunction is a key research goal for the upcoming era of early interventional approaches in spinocerebellar ataxias. This study aims to describe novel preclinical biomarkers of subtle gait and postural sway abnormalities in prodromal spinocerebellar ataxia type 2 (pre-SCA2).

METHODS

Thirty pre-SCA2 patients and their matched healthy controls underwent quantitative assessments of gait and postural sway using a wearable sensor-based system and semiquantitative evaluation of cerebellar features by SARA (Scale for the Assessment and Rating of Ataxia) score.

RESULTS

Quantitative analysis of natural gait showed a significantly larger variability of the swing period, toe-off angle and toe-out angle in pre-SCA2, and larger mean coronal and transverse ranges of motion of the trunk at the lumbar location and of the sagittal range of motion of the trunk at the sternum location compared to controls. During tandem gait, pre-SCA2 subjects showed larger lumbar, trunk, and arm ranges of motion than controls. Postural sway analysis showed excessive body oscillation that was increased in tandem stance. Overall, these abnormalities were detected in pre-SCA2 patients without clinical evidence of abnormalities in SARA. The toe-off angle and swing time variability were significantly correlated with the time to ataxia onset, whereas the toe-off angle and transverse range of motion at trunk position during tandem gait were significantly associated with the SARA score.

CONCLUSIONS

This study demonstrates early alteration of gait and postural sway control in prodromal SCA2 using a wearable sensor-based system. This offers new pathophysiological hints into this early disease stage and provides novel potential biomarkers for future clinical trials. © 2020 International Parkinson and Movement Disorder Society.

Opioid-Induced Reductions in Gait Variability in Healthy Volunteers and Individuals with Knee Osteoarthritis

OBJECTIVE

To investigate differences in gait variability induced by two different single-dose opioid formulations and an inert placebo in healthy volunteers and knee osteoarthritis patients.

DESIGN

Experimental, randomized, double-blinded, crossover study of inert placebo (calcium tablets), 50 mg of tapentadol, and 100 mg of tramadol.

SETTING

Laboratory setting.

SUBJECTS

Healthy volunteers and knee osteoarthritis patients.

METHODS

At three visits, separated by seven days, one tablet was administered per visit according to the randomization code. At each visit, a baseline measurement was done before tablet administration, after which hourly measurements were performed for six hours, yielding a total of seven measurements per visit. Gait variability was measured by three-dimensional gait analysis, recorded during six minutes of continuous treadmill walking at self-selected speed. One hundred seventy gait cycles were identified from detection of clear events of the knee joint angle trajectories. Gait variability was assessed as average standard deviations over a gait cycle of the sacrum displacements and accelerations; sagittal plane ankle, knee, and hip joint angles; step widths; and stride times.

RESULTS

Twenty-four opioid-naïve and neurologically intact participants (12 healthy volunteers and 12 knee osteoarthritis patients) were included and completed the experiment. Tapentadol reduced the variability of sacrum displacements and accelerations compared with placebo and tramadol. There were no differences between experimental conditions regarding the variability in lower-extremity joint angle variability, step widths, or stride times.

CONCLUSIONS

In opioid-naïve and neurologically intact individuals, tapentadol seems to reduce movement variability during treadmill walking, compared with placebo and tramadol. This can be interpreted as a loss of adaptability that might increase the risk of falling if the system is perturbed.

Quantification of abnormal upper limb movement during walking in people with acquired brain injury

BACKGROUND

Abnormal upper limb movements frequently affect people with acquired brain injury (ABI) during walking. Three-dimensional motion analysis (3DMA) can quantify upper limb abnormality kinematically, with composite scores condensing multiple joint axes data into a single score.

RESEARCH QUESTION

Are 3DMA-derived composite scores valid (known-groups and convergent validity), reliable and able to quantify speed-related changes in abnormal upper limb movement during walking?

METHODS

This observational study compared 42 adults with ABI and abnormal upper limb movements during walking with 36 healthy controls (HC) at a matched walking speed intention. Participants underwent 3DMA assessment of self-selected and fast walking speeds. Composite scores quantified the affected upper limb's kinematic abnormality. The Arm Posture Score arithmetic mean version (APSam) and 1.96 standard deviation reference-range scaled versions; the Kinematic Deviation Score mean (KDSm) and worst score (KDSw) were evaluated for association with each other and subjective abnormality rating (Pearson's 'r' correlation), test-retest reliability (intra-class correlation coefficient (ICC)), and ability to quantify speed-related changes in abnormal upper limb movement (Cohen's d effect size (ES), % change scores).

RESULTS

Very strong correlations existed between composite scores. The KDSm under-classified upper limb abnormality, whereas the KDSw captured the majority of ABI participants. All scores had moderate-strong correlations with subjective rating of abnormal upper limb movements (r = 0.54 - 0.79) and very strong test-retest reliability (ICCs > 0.81). The APSam demonstrated a 16% (ES = 0.76) walking speed-related increase in upper limb abnormality, whilst decreases were demonstrated in the KDSm 26% (ES 0.90) and KDSw 35% (ES 0.96).

SIGNIFICANCE

The APSam, KDSw, and number of abnormal joint axes comprehensively assess the whole upper limb abnormal movements, accurately classifies abnormality, and quantifies severity. This study illustrated notable presence of abnormal upper limb movements at self-selected walking speed and small increase at fast speeds. However, when scaled to HC variability, the fast walk kinematics became less abnormal due to increased HC movement variability.

Can pedobarography predict the occurrence of heel rocker in children with lower limb spasticity?

BACKGROUND

Pedobarography software calculates the centre-of-pressure trajectory in relation to the foot to quantify foot contact patterns. This study presents two new pedobarography measures using the centre-of-pressure trajectory to assess heel rocker.

METHODS

To validate these pedobarography measures against 3D gait analysis, emed_®-x and Vicon Nexus gait analysis data were captured from 25 children aged 8-16 years (11 male) with unilateral (n = 18) and bilateral (n = 7) cerebral palsy or acquired brain injury. 3D gait analysis identified whether heel rocker was intact (n = 22 feet) or absent (n = 28 feet) based on centre-of-pressure at initial contact and the ankle kinematic curve between 0 and 2% of the gait cycle. Pedobarography measures calculated from the initial centre-of-pressure point were the distance to the heel (point of initial contact) and to the most posterior point of the trajectory (rollback), reported as a percentage of foot length.

FINDINGS

The median point of initial contact in limbs with an intact heel rocker was 9% (range 7-12%) and median rollback was 0% (range 0-0.2%), whereas the median point of initial contact in limbs with an absent heel rocker was 58% (range 8-78%) and rollback was 18% (range 0-40%). Point of initial contact is the more accurate method for predicting heel rocker, with a threshold of 14% of foot length identifying the correct heel rocker status in 94% of cases.

INTERPRETATION

Point of initial contact can assess heel rocker with high accuracy. Both point of initial contact and rollback provide sensitive information on foot strike pattern, enhancing the utility of pedobarography.

The effect of joint translation constraint on within-participant variability of kinematics and kinetics during running in cerebral palsy

BACKGROUND

Biomechanical data in cerebral palsy are inherently variable but no optimal model of translational joint constraint has been identified. The primary aim of this study was to determine which model of translational joint constraint resulted in the lowest within-participant variability of lower limb joint angles and moments. The secondary aim was to determine which model best distinguished known functional groups in Cerebral Palsy.

METHODS

Three models (three degrees of freedom, six degrees of freedom and six degrees of freedom with specified joint translation constraint) were applied to data from running trials of 40 children with cerebral palsy.

FINDINGS

Joint angle standard deviations were largest using the six degrees of freedom model and smallest using the constrained six degrees of freedom model (p < 0.050). For all joints in all planes of motion, joint moment standard deviations were largest using the six degrees of freedom model and smallest using the constrained six degrees of freedom model; standard deviations using the constrained model were smaller than the three degrees of freedom model by 10-30% of moment magnitude (0.01-0.03 Nm/kg; p < 0.001). The six degrees of freedom models distinguished functional subgroups with larger effect size than the three degrees of freedom model only for hip power generation in swing.

INTERPRETATION

A model with specified joint constraint minimized within-participant variability during running and was useful for detecting differences in functional capacity in cerebral palsy.

Patterns of upper limb muscle activation in children with unilateral spastic cerebral palsy: Variability and detection of deviations

BACKGROUND

The aim of this study was two-fold: (1) to quantify the variability of upper limb electromyographic patterns during elbow movements in typically developing children and children with unilateral spastic cerebral palsy, and to compare different amplitude normalization methods; (2) to develop a method using this variability to detect (a) deviations in the patterns of a child with unilateral spastic cerebral palsy from the average patterns of typically developing children, and (b) changes after treatment to reduce muscle activation.

METHODS

Twelve typically developing children ([6.7-15.9yo]; mean 11.0 SD 3.0yo) and six children with unilateral spastic cerebral palsy ([7.9-17.4yo]; mean 12.4 SD 4.0yo) attended two sessions during which they performed elbow extension-flexion and pronation-supination movements. Surface electromyography of the biceps, triceps, brachioradialis, pronator teres, pronator quadratus, and brachialis muscles was recorded. The Likelihood method was used to estimate the inter-trial, inter-session, and inter-subject variability of the electromyography patterns for each time point in the movement cycle. Deviations in muscle patterns from the patterns of typically developing children and changes following treatment were evaluated in a case study of a child with cerebral palsy.

FINDINGS

Normalization of electromyographic amplitude by the mean peak yielded the lowest variability. The variability data were then used in the case study. This method detected higher levels of activation in specific muscles compared with typically developing children, and a reduction in muscle activation after botulinum toxin A injections.

INTERPRETATION

Upper limb surface electromyography pattern analysis can be used for clinical applications in children with cerebral palsy.

Critical review of the use and scientific basis of forensic gait analysis

This review summarizes the scientific basis of forensic gait analysis and evaluates its use in the Netherlands, United Kingdom and Denmark, following recent critique on the admission of gait evidence in Canada. A useful forensic feature is (1) measurable, (2) consistent within and (3) different between individuals. Reviewing the academic literature, this article found that (1) forensic gait features can be quantified or observed from surveillance video, but research into accuracy, validity and reliability of these methods is needed; (2) gait is variable within individuals under differing and constant circumstances, with speed having major influence; (3) the discriminative strength of gait features needs more research, although clearly variation exists between individuals. Nevertheless, forensic gait analysis has contributed to several criminal trials in Europe in the past 15 years. The admission of gait evidence differs between courts. The methods are mainly observer-based: multiple gait analysts (independently) assess gait features on video footage of a perpetrator and suspect. Using gait feature databases, likelihood ratios of the hypotheses that the observed individuals have the same or another identity can be calculated. Automated gait recognition algorithms calculate a difference measure between video clips, which is compared with a threshold value derived from a video gait recognition database to indicate likelihood. However, only partly automated algorithms have been used in practice. We argue that the scientific basis of forensic gait analysis is limited. However, gait feature databases enable its use in court for supportive evidence with relatively low evidential value. The recommendations made in this review are (1) to expand knowledge on inter- and intra-subject gait variabilities, discriminative strength and interdependency of gait features, method accuracies, gait feature databases and likelihood ratio estimations; (2) to compare automated and observer-based gait recognition methods; to design (3) an international standard method with known validity, reliability and proficiency tests for analysts; (4) an international standard gait feature data collection method resulting in database(s); (5) (inter)national guidelines for the admission of gait evidence in court; and (6) to decrease the risk for cognitive and contextual bias in forensic gait analysis. This is expected to improve admission of gait evidence in court and judgment of its evidential value. Several ongoing research projects focus on parts of these recommendations.

Quantifying sources of variability in gait analysis

Measurements from gait analysis are affected by many sources of variability. Schwartz et al. [1] illustrated an experimental design and methods to estimate these variance components. However, the derivation contains errors which could severely bias the estimation of some components. Therefore, in this paper, we presented correction to this method using ANOVA and Likelihood methods. Furthermore, we demonstrated how commonly used reliability indices like CMC and ICC may be derived from the variance components. We advocate the use of the variance components, in preference to reliability indices, because the variance components are easier to interpret, with understandable units.

Undesirable properties of the dimensionless normalisation for spatio-temporal variables

We used theory and empirical data to demonstrate three undesirable properties of the dimensionless normalisation technique for gait spatio-temporal parameters. Firstly, it may not fully remove the correlation between leg length and spatio-temporal parameters. Secondly, it induces spurious correlation among spatio-temporal parameters, which might obscure their true correlation structure. Thirdly, it induces spurious correlation with external covariates, which complicates further statistical modelling. Therefore, depending on the objectives, we propose alternatives. If the objective is to compare datasets but remove the confounding effect of leg length, residualisation may be an alternative, although the generalisability of the residualisation is less well established than dimensionless normalisation. If the objective is to build a regression model, the raw spatio-temporal parameters could be used with leg length, or a function of leg length, as an explicit regressor to avoid spurious correlation. If correlation is the objective, partial correlation can be used instead.