Identification of gait patterns in individuals with cerebral palsy using multiple correspondence analysis

Identifying Potential Factors Associated with High HIV viral load in KwaZulu-Natal, South Africa using Multiple Correspondence Analysis and Random Forest Analysis

Background

Sustainable Human Immunodeficiency Virus (HIV) virological suppression is crucial to achieving the Joint United Nations Programme of HIV/AIDS (UNAIDS) 95–95-95 treatment targets to reduce the risk of onward HIV transmission. Exploratory data analysis is an integral part of statistical analysis which aids variable selection from complex survey data for further confirmatory analysis.

Methods

In this study, we divulge participants’ epidemiological and biological factors with high HIV RNA viral load (HHVL) from an HIV Incidence Provincial Surveillance System (HIPSS) sequential cross-sectional survey between 2014 and 2015 KwaZulu-Natal, South Africa. Using multiple correspondence analysis (MCA) and random forest analysis (RFA), we analyzed the linkage between socio-demographic, behavioral, psycho-social, and biological factors associated with HHVL, defined as ≥400 copies per m/L.

Results

Out of 3956 in 2014 and 3868 in 2015, 50.1% and 41% of participants, respectively, had HHVL. MCA and RFA revealed that knowledge of HIV status, ART use, ARV dosage, current CD4 cell count, perceived risk of contracting HIV, number of lifetime HIV tests, number of lifetime sex partners, and ever diagnosed with TB were consistent potential factors identified to be associated with high HIV viral load in the 2014 and 2015 surveys. Based on MCA findings, diverse categories of variables identified with HHVL were, did not know HIV status, not on ART, on multiple dosages of ARV, with less likely perceived risk of contracting HIV and having two or more lifetime sexual partners.

Conclusion

The high proportion of individuals with HHVL suggests that the UNAIDS 95–95-95 goal of HIV viral suppression is less likely to be achieved. Based on performance and visualization evaluation, MCA was selected as the best and essential exploration tool for identifying and understanding categorical variables’ significant associations and interactions to enhance individual epidemiological understanding of high HIV viral load. When faced with complex survey data and challenges of variables selection in research, exploratory data analysis with robust graphical visualization and reliability that can reveal divers’ structures should be considered.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01625-6.

Three decades of gait index development: A comparative review of clinical and research gait indices

BACKGROUND

A wide variety of indices have been developed to quantify gait performance markers and associate them with their respective pathologies. Indices scores have enabled better decisions regarding patient treatments and allowed for optimized monitoring of the evolution of their condition. The extensive range of human gait indices presented over the last 30 years is evaluated and summarized in this narrative literature review exploring their application in clinical and research environments.

METHODS

The analysis will explore historical and modern gait indices, focusing on the clinical efficacy with respect to their proposed pathology, age range, and associated parameter limits. Features, methods, and clinically acceptable errors are discussed while simultaneously assessing indices advantages and disadvantages. This review analyses all indices published between 1994 and February 2021 identified using the Medline, PubMed, ScienceDirect, CINAHL, EMBASE, and Google Scholar databases.

FINDINGS

A total of 30 indices were identified as noteworthy for clinical and research purposes and another 137 works were included for discussion. The indices were divided in three major groups: observational (13), instrumented (16) and hybrid (1). The instrumented indices were further sub-divided in six groups, namely kinematic- (4), spatiotemporal- (5), kinetic- (2), kinematic- and kinetic- (2), electromyographic- (1) and Inertial Measurement Unit-based indices (2).

INTERPRETATION

This work is one of the first reviews to summarize observational and instrumented gait indices, exploring their applicability in research and clinical contexts. The aim of this review is to assist members of these communities with the selection of the proper index for the group in analysis.

Is the Prevalence of Equinus Foot in Cerebral Palsy Overestimated? Results from a Meta-Analysis of 4814 Feet

Background: Equinus is a common foot deformity in patients with cerebral palsy (CP). However, its prevalence is scarcely reported in the literature. Therefore, we conducted this review to estimate the prevalence of equinus foot in CP. Methods: Eight databases were searched. Our primary outcome was the prevalence of equinus foot in CP patients. Subgroup analysis was conducted based on study design, the laterality of CP, and whether equinus foot was defined or not. Results: The prevalence of equinus foot in CP was 93% (95% CI: 71–99). The prevalence was 99% (95% CI: 55–100), 96% (95% CI: 57–100), and 65% (95% CI: 37–86) in unilateral, both, and bilateral CP, respectively. Based on study design, equinus foot prevalence was 92% (95% CI: 34–100) in case series and 62% (95% CI: 47–74) in cohort studies. Four studies reported definition criteria for equinus foot, with a pooled prevalence rate of equinus foot of 99% (95% CI: 36–100) compared to a rate of 89% (95% CI: 59–98) among studies that lacked a definition criterion. Conclusions: This is the first meta-analysis to address the prevalence of equinus foot in CP patients. Although its prevalence is very high, our findings should be interpreted with caution due to the presence of multiple limitations, such as the lack of standardized definition criteria for equinus foot, the inappropriate study design, the wide confidence interval of equinus foot rate, and the small number of studies investigating it as a primary outcome.

Automatic classification of gait patterns in children with cerebral palsy using fuzzy clustering method

BACKGROUND

Subjective classification of gait pattern in children with cerebral palsy depends on the assessor's experience, while mathematical methods produce virtual groups with no clinical interpretation.

METHODS

In a retrospective study, gait data from 66 children (132 limbs) with a mean age of 9.6 (SD 3.7) years with cerebral palsy and no history of surgery or botulinum toxin injection were reviewed. The gait pattern of each limb was classified in four groups according to Rodda using three methods: 1) a team of experts subjectively assigning a gait pattern, 2) using the plantarflexor-knee extension couple index introduced by Sangeux et al., and 3) employing a fuzzy algorithm to translate the experiences of experts into objective rules and execute a clustering tool. To define fuzzy repeated-measures, 75% of the members in each group were used, and the remaining were used for validation. Eight parameters were objectively extracted from kinematic data for each group and compared using repeated measure ANOVA and post-hoc analysis was performed. Finally, the results of the clustering of the latter two methods were compared to the subjective method.

FINDINGS

The plantarflexor-knee extension couple index achieved 86% accuracy while the fuzzy system yielded a 98% accuracy. The most substantial errors occurred between jump and apparent in both methods.

INTERPRETATION

The presented method is a fast, reliable, and objective fuzzy clustering system to classify gait patterns in cerebral palsy, which produces clinically-relevant results. It can provide a universal common language for researchers.

Comparison of gait characteristics between clinical and daily life settings in children with cerebral palsy

Gait assessments in standardized settings, as part of the clinical follow-up of children with cerebral palsy (CP), may not represent gait in daily life. This study aimed at comparing gait characteristics in laboratory and real life settings on the basis of multiple parameters in children with CP and with typical development (TD). Fifteen children with CP and 14 with TD wore 5 inertial sensors (chest, thighs and shanks) during in-laboratory gait assessments and during 3 days of daily life. Sixteen parameters belonging to 8 distinct domains were computed from the angular velocities and/or accelerations. Each parameter measured in the laboratory was compared to the same parameter measured in daily life for walking bouts defined by a travelled distance similar to the laboratory, using Wilcoxon paired tests and Spearman’s correlations. Most gait characteristics differed between both environments in both groups. Numerous high correlations were found between laboratory and daily life gait parameters for the CP group, whereas fewer correlations were found in the TD group. These results demonstrated that children with CP perform better in clinical settings. Such quantitative evidence may enhance clinicians’ understanding of the gap between capacity and performance in children with CP and improve their decision-making.

The Vojta approach changes thicknesses of abdominal muscles and gait in children with spastic cerebral palsy: A randomized controlled trial, pilot study

BACKGROUND

Children with cerebral palsy (CP) have abnormal postures and gait patterns. Many physiotherapists use the Vojta approach as intervention for children with CP. However, its effects remain unclear.

OBJECTIVE

This study aimed to investigate the effect of the Vojta approach on abdominal muscles and gait in children with spastic CP.

METHODS

Thirteen children with spastic CP were randomly assigned to a general exercise and a Vojta approach group. The interventions were administered in 30 min sessions, 3 times a week for a total of 6 weeks. We used ultrasonography to measure the thicknesses of the abdominal muscles. The gait and foot pressure were measured by GAITRite.

RESULTS

The Vojta approach group showed significant difference in the thicknesses of the rectus abdominis, and external oblique abdominal muscles, which are involved in trunk stability (p< 0.05). There were significant differences in the step width, functional ambulation profile, swing time, stance time, and single support % of cycle as well as foot pressure distribution (p< 0.05).

CONCLUSION

The Vojta approach may be considered as an effective treatment method for improving trunk stability and gait functions of children with spastic CP.

Evaluating the feasibility of two post-hoc correction techniques for mitigating posture-induced measurement errors associated with wearable motion capture

Wearable motion capture systems are commonly used to measure body kinematics outside of laboratory settings. However, commercially available systems are designed to be used with typically developed adult populations, and assume users begin with a typical standing posture. Individuals with cerebral palsy and other neuromuscular pathologies often present atypical postures that can introduce significant errors in kinematics measurements from wearable motion capture. This study examines two post-hoc correction techniques for rectifying posture-induced errors in kinematic data: (1) Direct three-dimensional realignment of the measured body segment orientations, or (2) adding the initial static joint angle to the dynamic joint angle measurements. Gait kinematics were measured for eight able-bodied participants using a commercial wearable motion capture system. Participants walked with a typical gait, simulated crouch gait, and simulated equinus. The resulting kinematics from the uncorrected and post-hoc corrected trials were compared against simultaneously recorded measurements from an optoelectric motion capture system. Both correction techniques significantly decreased the posture-induced errors in lower-limb joint angle measurements. This work establishes a basis for the application of post-hoc correction techniques, aimed at improving the performance of wearable kinematic measurement systems when used with individuals having non-typical postures.

Gait Pattern Differences Among Children With Bilateral Cerebral Palsy

Background: The positive findings from our previous studies, which revealed the link between postural and gait patterns in children with unilateral cerebral palsy (CP) were very encouraging for recognition this relationship in children with bilateral cerebral palsy (CP). Therefore, the objective of this study was to evaluate whether different gait patterns corresponding to postural patterns in children with bilateral CP could be statistically significant according to a cluster analysis. Methods: Fifty-eight participants with bilateral CP and 45 matched children with typical growth and development. The participants walked barefoot along a treadmill at their own pace. Three-dimensional kinematic data were collected using the Measuring System for Motion Analysis. To characterize gait patterns, the Gillette Gait Index (GGI) and its 16 distinct gait parameters were used. The participants were divided into four subgroups according to their postural patterns. Results: A cluster analysis revealed 4 gait patterns corresponding to postural patterns: (1) normal gait pattern corresponded to neutral posture; (2) balanced gait pattern corresponded to balanced posture; (3) lordotic gait pattern corresponded to lordotic postural pattern; (4) swayback gait pattern corresponded to backward-leaning posture. There were significant differences in mean GGI and various clusters in the 8 GGI gait parameters: cadence, mean pelvic tilt; mean pelvic rotation, minimum hip flexion, peak hip abduction in swing; knee flexion at initial contact, and peak dorsiflexion in stance. Conclusion: Our results showed that gait discrepancies among children with bilateral CP were not simply a result of lower limb kinematic deviations in the sagittal plane. Information on different gait patterns could improve early therapy in children with bilateral CP before abnormal gait patterns are fully established.

Systematic review on gait classifications in children with cerebral palsy: An update

BACKGROUND

Gait classification systems (GCSs) aim to aid clinicians and researchers in categorizing the gait of pathological populations, with the intent to improve the communication between them, to support treatment planning and enable the evaluation of patients over time. Throughout the years, various GCSs have been defined for children with cerebral palsy (CP), which were first summarized in a systematic review published in 2007.

RESEARCH QUESTION

The current systematic review aimed to: a) identify GCSs that have been more recently developed, b) appraise their methodological quality and c) specify the most commonly used multiple joint gait patterns for children with CP reported in literature.

METHODS

Four databases (Medline, EMBASE, CINAHL, Web of Science) were searched until July 2017. Several forms of validity and the reliability of these studies were assessed according to the principles of the consensus-based standards for the selection of health measurement instruments checklist or criteria defined in the original review. All published GCSs were also scrutinized in order to identify multiple joint patterns that have reached a predefined level of consensus.

RESULTS

Thirty-six studies were considered in this review, 15 of them being GCSs that were not included in the original review. The validity, reliability and clinical applicability of all GCSs was reported, including 3 studies from the original review. Six multiple joint patterns for children with CP reached a consensus in literature.

CONCLUSION

Since the previous review, obvious progress has been made in the field of GCSs for CP, resulting in improved methodological quality of the majority of published GCSs. This encouraged the applicability of GCSs in clinical or research settings. The six reliable, valid and commonly used multiple joint patterns, emerging from this systematic review, may aid clinical and research applications and create a common language among healthcare providers.

Matching Golfers’ Movement Patterns during a Golf Swing

The golf swing is a multidimensional movement requiring alternative data analysis methods to interpret non-linear relationships in biomechanics data related to golf shot outcomes. The purpose of this study was to use a combined principal component analysis (PCA), fuzzy coding, and multiple correspondence analysis (MCA) data analysis approach to visualise associations within key biomechanics movement patterns and impact parameters in a group of low handicap golfers. Biomechanics data was captured and analysed for 22 golfers when hitting shots with their own driver. Relationships between biomechanics variables were firstly achieved by quantifying principal components, followed by fuzzy coding and finally MCA. Clubhead velocity and ball velocity were included as supplementary data in MCA. A total of 35.9% of inertia was explained by the first factor plane of MCA. Dimension one and two, and subsequent visualisation of MCA results, showed a separation of golfers’ biomechanics (i.e., swing techniques). The MCA plot can be used to simply and quickly identify movement patterns of a group of similar handicap golfers if supported with appropriate descriptive interpretation of the data. This technique also has the potential to highlight mismatched golfer biomechanics variables which could be contributing to weaker impact parameters.

Lower limb extension is improved in fast walking condition in children who walk in crouch gait

Background and purpose: The strategies for walking fast have never been reported in children with cerebral palsy who walk in crouch gait. This study aimed to assess to what extent children who walk in crouch gait are able to increase their gait speed and to report the corresponding three-dimensional kinematic adaptations.Methods: Eleven children and adolescents (aged between 7 and 17 years) with bilateral cerebral palsy, who walk in crouch gait, were asked to walk at their self-selected comfortable speed and then as fast as possible without running. The spatio-temporal and kinematic parameters, as well as the center of mass displacements were compared between walking conditions.Results: Children were able to walk 30% faster than their comfortable speed (+0.30 m/s, p = 0.000) by increasing both cadence (+21 step/min, p = 0.000) and step length (+0.05 m, p = 0.001). During the stance phase, pelvis anteversion (+3 Deg, p = 0.010), hip flexion-extension range of motion (+4 Deg, p = 0.002), and knee extension (+5 Deg, p = 0.000) were increased in fast walking. During fast walking, the center of mass showed larger range of vertical displacements (p < 0.05).Conclusions: Children with cerebral palsy who walk in crouch gait increased their walking speed by adopting a less crouched posture. Compared to comfortable walking speed condition, fast walking could be beneficial in rehabilitation to solicit higher lower limbs range of motion.Implications for rehabilitation:Children who walk in crouch gait can walk 30% fasterFast walking required higher hip and knee extensions during stance phaseFast walking could be an interesting training modality to improve the lower limb range of motion of children who walk in crouch gait.

Automatic recognition of gait patterns in human motor disorders using machine learning: A review

BACKGROUND

automatic recognition of human movement is an effective strategy to assess abnormal gait patterns. Machine learning approaches are mainly applied due to their ability to work with multidimensional nonlinear features.

PURPOSE

to compare several machine learning algorithms employed for gait pattern recognition in motor disorders using discriminant features extracted from gait dynamics. Additionally, this work highlights procedures that improve gait recognition performance.

METHODS

we conducted an electronic literature search on Web of Science, IEEE, and Scopus, using "human recognition", "gait patterns'', and "feature selection methods" as relevant keywords.

RESULTS

analysis of the literature showed that kernel principal component analysis and genetic algorithms are efficient at reducing dimensional features due to their ability to process nonlinear data and converge to global optimum. Comparative analysis of machine learning performance showed that support vector machines (SVMs) exhibited higher accuracy and proper generalization for new instances.

CONCLUSIONS

automatic recognition by combining dimensional data reduction, cross-validation and normalization techniques with SVMs may offer an objective and rapid tool for investigating the subject's clinical status. Future directions comprise the real-time application of these tools to drive powered assistive devices in free-living conditions.

A Mechanical Sensor Designed for Dynamic Joint Angle Measurement

Background. The measurement of the functional range of motion (FROM) of lower limb joints is an essential parameter for gait analysis especially in evaluating rehabilitation programs. Aim. To develop a simple, reliable, and affordable mechanical goniometer (MGR) for gait analysis, with six-degree freedom to dynamically assess lower limb joint angles. Design. Randomized control trials, in which a new MGR was developed for the measurements of FROM of lower limb joints. Setting. Reliability of the designed MGR was evaluated and validated by a motion analysis system (MAS). Population. Thirty healthy subjects participated in this study. Methods. Reliability and validity of the new MGR were tested by intraclass correlation coefficient (ICC), Bland-Altman plots, and linear correlation analysis. Results. The MGR has good inter- and intrarater reliability and validity with ICC ≥ 0.93 (for both). Moreover, measurements made by MGR and MAS were comparable and repeatable with each other, as confirmed by Bland-Altman plots. Furthermore, a very high degree of linear correlation (R ≥ 0.92 for all joint angle measurements) was found between the lower limb joint angles measured by MGR and MAS. Conclusion. A simple, reliable, and affordable MGR has been designed and developed to aid clinical assessment and treatment evaluation of gait disorders.

Classification of upper limb disability levels of children with spastic unilateral cerebral palsy using K-means algorithm

Treatment for cerebral palsy depends upon the severity of the child's condition and requires knowledge about upper limb disability. The aim of this study was to develop a systematic quantitative classification method of the upper limb disability levels for children with spastic unilateral cerebral palsy based on upper limb movements and muscle activation. Thirteen children with spastic unilateral cerebral palsy and six typically developing children participated in this study. Patients were matched on age and manual ability classification system levels I to III. Twenty-three kinematic and electromyographic variables were collected from two tasks. Discriminative analysis and K-means clustering algorithm were applied using 23 kinematic and EMG variables of each participant. Among the 23 kinematic and electromyographic variables, only two variables containing the most relevant information for the prediction of the four levels of severity of spastic unilateral cerebral palsy, which are fixed by manual ability classification system, were identified by discriminant analysis: (1) the Falconer index (CAI _E ) which represents the ratio of biceps to triceps brachii activity during extension and (2) the maximal angle extension (θ _{Extension,max}). A good correlation (Kendall Rank correlation coefficient = -0.53, p = 0.01) was found between levels fixed by manual ability classification system and the obtained classes. These findings suggest that the cost and effort needed to assess and characterize the disability level of a child can be further reduced.

Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).

Prevalence of Joint Gait Patterns Defined by a Delphi Consensus Study Is Related to Gross Motor Function, Topographical Classification, Weakness, and Spasticity, in Children with Cerebral Palsy

During a Delphi consensus study, a new joint gait classification system was developed for children with cerebral palsy (CP). This system, whose reliability and content validity have previously been established, identified 49 distinct joint patterns. The present study aims to provide a first insight toward the construct validity and clinical relevance of this classification system. The retrospective sample of convenience consisted of 286 patients with spastic CP (3-18 years old, GMFCS levels I-III, 166 with bilateral CP). Kinematic and kinetic trials from three-dimensional gait analysis were classified according to the definitions of the Delphi study, and one classified trial was randomly selected for each included limb (n = 446). Muscle weakness and spasticity were assessed for different muscle groups acting around the hip, knee, and ankle. Subsequently, Pearson Chi square tests, Cramer's V, and adjusted standardized residuals were calculated to explore the strength and direction of the associations between the joint patterns, and the different patient-specific characteristics (i.e., age, GMFCS level, and topographical classification) or clinical symptoms (muscle weakness and spasticity). Patient-specific characteristics showed several significant associations with the patterns of different joints, but the strength of most identified associations was weak. Apart from the knee during stance phase and the pelvis in the sagittal plane, the results systematically showed that the patterns with "minor gait deviations" were the most frequently observed. These minor deviations were found significantly more often in limbs with a lower level of spasticity and good muscle strength. Several other pathological joint patterns were moderately associated with weakness or spasticity, including but not limited to "outtoeing" for weakness and "intoeing" for spasticity. For the joints in the sagittal plane, significantly stronger associations were found with muscle weakness and spasticity, possibly because most of the evaluated muscles in this study mainly perform sagittal plane motions. Remarkably, the hip patterns in the coronal plane did not associate significantly with any of the investigated variables. Although further validation is warranted, this study contributes to the construct validity of the joint patterns of the Delphi consensus study, by demonstrating their ability to distinguish between clinically relevant subgroups in CP.

Statistical Parametric Mapping to Identify Differences between Consensus-Based Joint Patterns during Gait in Children with Cerebral Palsy

Experts recently identified 49 joint motion patterns in children with cerebral palsy during a Delphi consensus study. Pattern definitions were therefore the result of subjective expert opinion. The present study aims to provide objective, quantitative data supporting the identification of these consensus-based patterns. To do so, statistical parametric mapping was used to compare the mean kinematic waveforms of 154 trials of typically developing children (n = 56) to the mean kinematic waveforms of 1719 trials of children with cerebral palsy (n = 356), which were classified following the classification rules of the Delphi study. Three hypotheses stated that: (a) joint motion patterns with 'no or minor gait deviations' (n = 11 patterns) do not differ significantly from the gait pattern of typically developing children; (b) all other pathological joint motion patterns (n = 38 patterns) differ from typically developing gait and the locations of difference within the gait cycle, highlighted by statistical parametric mapping, concur with the consensus-based classification rules. (c) all joint motion patterns at the level of each joint (n = 49 patterns) differ from each other during at least one phase of the gait cycle. Results showed that: (a) ten patterns with 'no or minor gait deviations' differed somewhat unexpectedly from typically developing gait, but these differences were generally small (≤3°); (b) all other joint motion patterns (n = 38) differed from typically developing gait and the significant locations within the gait cycle that were indicated by the statistical analyses, coincided well with the classification rules; (c) joint motion patterns at the level of each joint significantly differed from each other, apart from two sagittal plane pelvic patterns. In addition to these results, for several joints, statistical analyses indicated other significant areas during the gait cycle that were not included in the pattern definitions of the consensus study. Based on these findings, suggestions to improve pattern definitions were made.

Gait analysis in children with cerebral palsy

Cerebral palsy (CP) children present complex and heterogeneous motor disorders that cause gait deviations.

Clinical gait analysis (CGA) is needed to identify, understand and support the management of gait deviations in CP. CGA assesses a large amount of quantitative data concerning patients’ gait characteristics, such as video, kinematics, kinetics, electromyography and plantar pressure data.

Common gait deviations in CP can be grouped into the gait patterns of spastic hemiplegia (drop foot, equinus with different knee positions) and spastic diplegia (true equinus, jump, apparent equinus and crouch) to facilitate communication. However, gait deviations in CP tend to be a continuum of deviations rather than well delineated groups. To interpret CGA, it is necessary to link gait deviations to clinical impairments and to distinguish primary gait deviations from compensatory strategies.

CGA does not tell us how to treat a CP patient, but can provide objective identification of gait deviations and further the understanding of gait deviations. Numerous treatment options are available to manage gait deviations in CP. Generally, treatments strive to limit secondary deformations, re-establish the lever arm function and preserve muscle strength.

Additional roles of CGA are to better understand the effects of treatments on gait deviations.

Cite this article: Armand S, Decoulon G, Bonnefoy-Mazure A. Gait analysis in children with cerebral palsy. EFORT Open Rev 2016;1:448-460. DOI: 10.1302/2058-5241.1.000052.

Sagittal gait patterns in cerebral palsy: the plantarflexor-knee extension couple index

The identification of gait patterns in cerebral palsy offers a common language for clinicians and contributes to management algorithms. We describe a quantitative classification of sagittal gait patterns based on the plantarflexor-knee extension couple index. This consists of a scatter plot based on ankle and knee scores, and allows objective identification of the sagittal gait pattern. Sagittal kinematic data from 200 limbs of 100 patients with bilateral spastic cerebral palsy were utilized to validate the algorithm against the assessment of a clinician with expertise in gait pattern identification. A dataset of 776 cerebral palsy patients, 1552 limbs, was used to compare the sagittal gait patterns against k-means statistical clustering. The classification was further explored with respect to the knee kinetics during the middle of stance and physical examination measurements of the gastrocnemius-soleus complex. Two supplementary materials (Appendices 2 and 3) provide in-depth discussion about statistical properties of the plantarflexor-knee extension couple index as well as its relationship with statistical clustering. The plantarflexor-knee extension index achieved 98% accuracy and may be suitable for the computational classification of large patient cohorts and multicentre studies. The sagittal gait patterns were strongly related to k-means statistical clustering and physical examination of the gastrocnemius-soleus complex. Patients in crouch gait had normal soleus and gastrocnemius lengths but spasticity in the gastrocnemius. Patients in jump gait exhibited a short gastrocnemius and soleus and gastrocnemius spasticity. Patients in true equinus presented with a moderately contracted soleus and gastrocnemius and gastrocnemius spasticity. Patients in apparent equinus did not show abnormal physical examination measurements for the gastrocnemius-soleus complex.

A descriptive analysis of the upper limb patterns during gait in individuals with cerebral palsy

Patients with cerebral palsy (CP) are characterized by a large diversity of gait deviations; thus, lower limb movements during gait have been well-analyzed in the literature. However, the question of upper limb movements and, more particularly, arm movements during gait has received less attention for CP patients as a function of the disease type (Hemiplegic, HE or Diplegic, DI). Thus, the aim of this study was to investigate upper limb movements for a large group of CP patients; we used a retrospective search, including upper limb kinematic parameters and 92 CP patients (42 females and 50 males, mean±standard deviation (SD); age: 15.2±6.7 years). The diagnoses consisted of 48 HE and 44 DI. A control group of 15 subjects (7 females and 8 males, age: 18.4±8.4 years) was included in the study to provide normal gait data. For the DI patients and CG, 88 arms and 30 arms were analyzed, respectively. For the HE patients, 48 affected arms and 48 non-affected arms were analyzed. The kinematic parameters selected and analyzed were shoulder elevation angles; elbow flexion angles; thorax tilt and obliquity angles; hand vertical and anterior-posterior movements; and arm angles. Several gait parameters were also analyzed, such as the gait profile score (GPS) and normalized speed. Statistical analyses were performed to compare CG with the affected and non-affected upper limbs of HE patients and with the two upper limbs of DI patients. The results show that HE and DI patients adopt abnormal upper limb movements. However, DI patients have greater shoulder, elbow, thorax and arm angle movements compared with HE patients. However, HE patients adopt different movements between their affected and non-affected arms. Thus, the patients used their upper limbs to optimize their gait more where gait deviations were more important. These observations confirm that the upper limbs must be integrated into rehabilitation programs to improve inter-limb coordination.

Effects of gastrocnemius fascia lengthening on gait pattern in children with cerebral palsy using the gait profile score

The aim of the present study was to investigate the efficacy of the GPS regarding the quantification of changes in gait following the gastrocnemius fascia lengthening in children with CP. Nineteen children with CP were selected and evaluated in the preoperative period (PRE session) and approximately one year postoperatively (POST session; mean 13.1 ± 5.1 months) using 3D gait analysis and computing the GPS and GVSs. As the GPS represents the difference between the patient's data and the average from the reference dataset, the higher the value of GPS is, more compromised gait of the subject. A statistically significant improvement in mean GPS was found in the POST session (PRE: 13.38 ± 5°; POST: 10.26 ± 2.41°; p<0.05), with an improvement close to 23%. Moreover, the GVSs demonstrated statistically significant improvements in ankle dorsi-plantarflexion (PRE: 22.20 ± 16.36°; POST: 11.50 ± 6.57°; p<0.05) and pelvic rotation (PRE: 9.53 ± 3.87°; POST: 6.47 ± 2.98°; p<0.05). A strong correlation (r=0.75; p<0.05) was found between the preoperative GPS and the percentage of GPS improvement. The results demonstrated that the gastrocnemius fascia lengthening produced a global gait pattern improvement, as showed by the GPS value, which decreased after surgery. Besides this, the GVS permitted to better evidence the joints more compromised by the pathology and their improvement due to the surgery, in this case not only the GVS of the ankle joint but also of the pelvis were characterized by higher GVS values.

Gait patterns in hemiplegic patients with equinus foot deformity

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.