Effect of a rigid ankle-foot orthosis on hamstring length in children with hemiplagia

Eighteen children with hemiplegia, mean age 8 years 5 months, underwent gait analysis and musculoskeletal modelling using specially designed software. The maximum lengths of the hamstrings were determined for each child walking in and out of an ankle–foot orthosis (AFO). The muscles were deemed to be short if shorter than the normal average – 1SD. In bare feet 8 participants had short medial hamstrings with a higher proportion of these in the less involved individuals. All participants showed an increase in maximum hamstring length when wearing an AFO. In all but one child this was sufficient to restore hamstring length to within normal limits. These finding suggest that hamstring pathology in hemiplegic gait is usually secondary to more distal lower limb pathology

A review of the effectiveness of lower limb orthoses used in cerebral palsy

To produce this review, a systematic literature search was conducted for relevant articles published in the period between the date of the previous ISPO consensus conference report on cerebral palsy (1994) and April 2008. The search terms were 'cerebral and pals* (palsy, palsies), 'hemiplegia', 'diplegia', 'orthos*' (orthoses, orthosis) orthot* (orthotic, orthotics), brace or AFO

Age-related gait standards for healthy children and young people: the GOS-ICH paediatric gait centiles

Objective To develop paediatric gait standards in healthy children and young people. Methods This observational study builds on earlier work to address the lack of population standards for gait measurements in children. Analysing gait in children affected by neurological or musculoskeletal conditions is an important component of paediatric assessment but is often confounded by developmental changes. The standards presented here do not require clinician expertise to interpret and offer an alternative to developmental tables of normalised gait data. Healthy children aged 1-19 years were recruited from community settings in London and Hertfordshire, U.K. The GAITRite ® walkway was used to record measurements for each child for velocity, cadence, step length, base of support, and stance, single and double support (as percentage of gait cycle). We fitted generalized linear additive models for location, scale and shape (gamlss). Results We constructed percentile charts for seven gait variables measured on 624 (321 males) contemporary healthy children using gamlss package in R. A clinical application of gait standards was explored. Conclusion Age-related, gender-specific standards for seven gait variables were developed and are presented here. They have a familiar format and can be used clinically to aid diagnoses, and to monitor change over time for both medical therapy and natural history of the condition. The clinical example demonstrates the potential of the GOS-ICH Paediatric Gait Centiles (GOS-ICH PGC) to enable meaningful interpretation of change in an individual’s performance, and describes characteristic features of gait from a specific population throughout childhood.Peer reviewedFinal Accepted Versio

Automated design of robust discriminant analysis classifier for foot pressure lesions using kinematic data

In the recent years, the use of motion tracking systems for acquisition of functional biomechanical gait data, has received increasing interest due to the richness and accuracy of the measured kinematic information. However, costs frequently restrict the number of subjects employed, and this makes the dimensionality of the collected data far higher than the available samples. This paper applies discriminant analysis algorithms to the classification of patients with different types of foot lesions, in order to establish an association between foot motion and lesion formation. With primary attention to small sample size situations, we compare different types of Bayesian classifiers and evaluate their performance with various dimensionality reduction techniques for feature extraction, as well as search methods for selection of raw kinematic variables. Finally, we propose a novel integrated method which fine-tunes the classifier parameters and selects the most relevant kinematic variables simultaneously. Performance comparisons are using robust resampling techniques such as Bootstrap$632+$and k-fold cross-validation. Results from experimentations with lesion subjects suffering from pathological plantar hyperkeratosis, show that the proposed method can lead to$sim 96$correct classification rates with less than 10% of the original features

Segmentation and classification of gait cycles

Gait abnormalities can be studied by means of instrumented gait analysis. Foot-switches are useful to study the foot-floor contact and for timing the gait phases in many gait disorders, provided that a reliable foot-switch signal may be collected. Considering long walks allows reducing the intra-subject variability, but requires automatic and user-independent methods to analyze a large number of gait cycles. The aim of this work is to describe and validate an algorithm for the segmentation of the foot-switch signal and the classification of the gait cycles. The performance of the algorithm was assessed comparing its results against the manual segmentation and classification performed by a gait analysis expert on the same signal. The performance was found to be equal to 100% for healthy subjects and over 98% for pathological subjects. The algorithm allows determining the atypical cycles (cycles that do not match the standard sequence of gait phases) for many different kinds of pathological gait, since it is not based on pathology-specific template

Absolute agreement and consistency of the OptoGait system and Freemed platform for measuring walking gait

The gait cycle can be divided into four functional rocker units. Although the widespread use of the OptoGait (OG) system and the Freemed (FM) platform, their accuracy has not been tested. An observational study was completed with eighteen healthy volunteers to determine the accuracy of OG and FM for overground walking gait analysis. The pairwise comparison between data obtained from OG, FM and high-speed video analysis revealed significant differences for most of the measurements (p  0.94) for all measures for OG systems compared to video-analysis. When considering FM vs. video-analysis, ICCs showed good absolute agreement for rocker 1 (ICC = 0.86) and 3 (ICC = 0.82), excellent for rocker 2 (ICC = 0.93) and poor (ICC  0.1) while no heteroscedasticity of error was found when using FM (r2 < 0.1). This study indicates that the OG system and the FM platform can provide consistent foot rockers values when walking at a constant velocity. The differences between the systems assessed and their agreement and consistency values advise against their interchangeable use

The Effects of Walking Surface and Vibration on the Gait Pattern and Vibration Perception Threshold of Typically Developing Children and Children with Idiopathic Toe Walking

The aim of the current study is to investigate novel therapeutic/treatment methods and outcome measurement for children with Idiopathic Toe Walking (ITW). Fifteen typically developing (TD) children and 15 children with ITW, aged between 4 to 10 years old, participated. The participants performed a gait exam including 30 barefoot walking trials over three 4-meter walkways before and after a whole-body vibration intervention. Vibration perception threshold tests were also conducted before and after the vibration intervention. In the gait exams, each of the walking surfaces represented a different tactile stimulus and the vibration intervention included standing on a whole body vibration platform for 60 seconds. Kinematics were collected at 100 Hz with a seven-camera 3-D motion analysis system. Walking surface and vibration intervention were the independent variables. Temporal-spatial gait parameters such as velocity, cadence, step length, and step width were measured. Heel rise occurrence (HR32) and vibration perception threshold (VPT) were also calculated as dependent variables. Walking surface significantly altered the gait parameter of both TD children and children with ITW. Vibration intervention altered the VPT scores of both TD children and children with ITW. Manipulated surface and excessive vibration may be important in the development of therapeutic/treatment methods for children with Idiopathic Toe Walking. HR32 is a novel calculation designed to distinguish on aspect of the toe-walking gait pattern. It significantly identified toe-walking patterns and quantified treatment results. Children with ITW appeared to have less toe-walking on the gravel surface. Walking on gravel surface is a potential novel method to reduce toe-walking immediately with no negative after-effects

Surface Electromyography Applied to Gait Analysis: How to Improve Its Impact in Clinics?

Surface electromyography (sEMG) is the main non-invasive tool used to record the electrical activity of muscles during dynamic tasks. In clinical gait analysis, a number of techniques have been developed to obtain and interpret the muscle activation patterns of patients showing altered locomotion. However, the body of knowledge described in these studies is very seldom translated into routine clinical practice. The aim of this work is to analyze critically the key factors limiting the extensive use of these powerful techniques among clinicians. A thorough understanding of these limiting factors will provide an important opportunity to overcome limitations through specific actions, and advance toward an evidence-based approach to rehabilitation based on objective findings and measurements

Multiple gait patterns within the same Winters class in children with hemiplegic cerebral palsy

Abstract Background Previous literature hypothesized that Winters type I are mainly characterized by a hypo-activation of dorsiflexors and type II by hyperactivation of plantarflexors around initial contact. However, it is currently not known if hemiplegic children belonging to the same Winters class really share the same muscle activation patterns, although this information might have relevant clinical implications in the patient management. Methods Gait data of 38 hemiplegic cerebral palsy children (16 Winters type I, 22 Winters type II) were analyzed, focusing on the foot and shank. A 2.5-minute walk test was considered, corresponding to more than 100 gait cycles for each child, analyzing the muscle activation patterns of tibialis anterior and gastrocnemius lateralis. The large stride-to-stride variability of gait data was handled in an innovative way, processing separately: 1) distinct foot-floor contact patterns, and for each specific foot-floor contact pattern 2) distinct muscle “activation modalities”, averaging only across gait cycles with the same number of activations, and obtaining, in both cases, the pattern frequency-of-occurrence. Findings At least 2 representative foot-floor contact patterns within each Winters group, and up to 4–5 distinct muscle activation patterns were documented. Interpretation It cannot be defined a predominant muscle activation pattern specific for a Winters group. For a correct clinical assessment of a hemiplegic child, it is advisable to record and properly analyze gait signals during a longer period of time (2–3 minutes), rather than (subjectively) selecting a few “clean” gait cycles, since these cycles may not be representative of the patient’s gait

Autism Spectrum Disorders Gait Identification Using Ground Reaction Forces

 Autism spectrum disorders (ASD) are a permanent neurodevelopmental disorder that can be identified during the first few years of life and are currently associated with the abnormal walking pattern. Earlier identification of this pervasive disorder could provide assistance in diagnosis and establish rapid quantitative clinical judgment. This paper presents an automated approach which can be applied to identify ASD gait patterns using three-dimensional (3D) ground reaction forces (GRF). The study involved classification of gait patterns of children with ASD and typical healthy children. The GRF data were obtained using two force plates during self-determined barefoot walking. Time-series parameterization techniques were applied to the GRF waveforms to extract the important gait features. The most dominant and correct features for characterizing ASD gait were selected using statistical between-group tests and stepwise discriminant analysis (SWDA). The selected features were grouped into two groups which served as two input datasets to the k-nearest neighbor (KNN) classifier. This study demonstrates that the 3D GRF gait features selected using SWDA are reliable to be used in the identification of ASD gait using KNN classifier with 83.33% performance accuracy.