Exoskeleton Application to Military Manual Handling Tasks.

OBJECTIVE: The aim of this review was to determine how exoskeletons could assist Australian Defence Force personnel with manual handling tasks. BACKGROUND: Musculoskeletal injuries due to manual handling are physically damaging to personnel and financially costly to the Australian Defence Force. Exoskeletons may minimize injury risk by supporting, augmenting, and/or amplifying the user's physical abilities. Exoskeletons are therefore of interest in determining how they could support the unique needs of military manual handling personnel. METHOD: Industrial and military exoskeleton studies from 1990 to 2019 were identified in the literature. This included 67 unique exoskeletons, for which Information about their current state of development was tabulated. RESULTS: Exoskeleton support of manual handling tasks is largely through squat/deadlift (lower limb) systems (64%), with the proposed use case for these being load carrying (42%) and 78% of exoskeletons being active. Human-exoskeleton analysis was the most prevalent form of evaluation (68%) with reported reductions in back muscle activation of 15%-54%. CONCLUSION: The high frequency of citations of exoskeletons targeting load carrying reflects the need for devices that can support manual handling workers. Exoskeleton evaluation procedures varied across studies making comparisons difficult. The unique considerations for military applications, such as heavy external loads and load asymmetry, suggest that a significant adaptation to current technology or customized military-specific devices would be required for the introduction of exoskeletons into a military setting. APPLICATION: Exoskeletons in the literature and their potential to be adapted for application to military manual handling tasks are presented.

Shoe-Insole Technology for Injury Prevention in Walking.

Impaired walking increases injury risk during locomotion, including falls-related acute injuries and overuse damage to lower limb joints. Gait impairments seriously restrict voluntary, habitual engagement in injury prevention activities, such as recreational walking and exercise. There is, therefore, an urgent need for technology-based interventions for gait disorders that are cost effective, willingly taken-up, and provide immediate positive effects on walking. Gait control using shoe-insoles has potential as an effective population-based intervention, and new sensor technologies will enhance the effectiveness of these devices. Shoe-insole modifications include: (i) ankle joint support for falls prevention; (ii) shock absorption by utilising lower-resilience materials at the heel; (iii) improving reaction speed by stimulating cutaneous receptors; and (iv) preserving dynamic balance via foot centre of pressure control. Using sensor technology, such as in-shoe pressure measurement and motion capture systems, gait can be precisely monitored, allowing us to visualise how shoe-insoles change walking patterns. In addition, in-shoe systems, such as pressure monitoring and inertial sensors, can be incorporated into the insole to monitor gait in real-time. Inertial sensors coupled with in-shoe foot pressure sensors and global positioning systems (GPS) could be used to monitor spatiotemporal parameters in real-time. Real-time, online data management will enable ‘big-data’ applications to everyday gait control characteristics.

Minimum toe clearance events in divided attention treadmill walking in older and young adults: a cross-sectional study.

BACKGROUND: Falls in older adults during walking frequently occur while performing a concurrent task; that is, dividing attention to respond to other demands in the environment. A particularly hazardous fall-related event is tripping due to toe-ground contact during the swing phase of the gait cycle. The aim of this experiment was to determine the effects of divided attention on tripping risk by investigating the gait cycle event Minimum Toe Clearance (MTC). METHODS: Fifteen older adults (mean 73.1 years) and 15 young controls (mean 26.1 years) performed three walking tasks on motorized treadmill: (i) at preferred walking speed (preferred walking), (ii) while carrying a glass of water at a comfortable walking speed (dual task walking), and (iii) speed-matched control walking without the glass of water (control walking). Position-time coordinates of the toe were acquired using a 3 dimensional motion capture system (Optotrak NDI, Canada). When MTC was present, toe height at MTC (MTC_Height) and MTC timing (MTC_Time) were calculated. The proportion of non-MTC gait cycles was computed and for non-MTC gait cycles, toe-height was extracted at the mean MTC_Time. RESULTS: Both groups maintained mean MTC_Height across all three conditions. Despite greater MTC_Height SD in preferred gait, the older group reduced their variability to match the young group in dual task walking. Compared to preferred speed walking, both groups attained MTC earlier in dual task and control conditions. The older group's MTC_Time SD was greater across all conditions; in dual task walking, however, they approximated the young group's SD. Non-MTC gait cycles were more frequent in the older group across walking conditions (for example, in preferred walking: young - 2.9 %; older - 18.7 %). CONCLUSIONS: In response to increased attention demands older adults preserve MTC_Height but exercise greater control of the critical MTC event by reducing variability in both MTC_Height and MTC_Time. A further adaptive locomotor control strategy to reduce the likelihood of toe-ground contacts is to attain higher mid-swing clearance by eliminating the MTC event, i.e. demonstrating non-MTC gaits cycles.

Effects of walking-induced fatigue on gait function and tripping risks in older adults.

BACKGROUND: Fatigue and ageing contribute to impaired control of walking and are linked to falls. In this project, fatigue was induced by maximum speed walking to examine fatigue effects on lower limb trajectory control and associated tripping risk and overall gait functions of older adults. METHODS: Eleven young (18-35 years) and eleven older adults (>65 years) conducted 5-minute preferred speed treadmill walking prior to and following 6-minute maximum fast walking. Spatio-temporal gait parameters and minimum foot clearance (MFC) were obtained. Maximal muscle strength (hamstrings and quadriceps) was measured on an isokinetic dynamometer. Heart rate (HR) and rating of perceived exertion (RPE) assessed physiological effort and subjective fatigue. Physiological Cost Index computed walking efficiency. RESULTS: Fatigue due to fast walking increased step length, double support time and variability of step width. Only older adults reduced MFC due to fatigue. A trend of longer double support with greater MFC was found in the non-dominant limb. Lower walking efficiency was characterised as the ageing effect. Older adults did not increase HR during fast walking but higher RPE scores were observed. CONCLUSIONS: Older adults can increase tripping risk by 6 minutes of fast walking possibly by both impaired walking efficiency based on cardiac capacity and higher perceived fatigue due to elevated caution level. Regardless of age, increased step width variability due to fatigue was observed, a sign of impaired balance. Longer double support and greater MFC observed in the older adults' non-dominant limb could be an asymmetrical gait adaptation for safety.

The highs and lows of lifting loads: SPM analysis of multi-segmental spine angles in healthy adults during manual handling with increased load.

Introduction: Manual handling personnel and those performing manual handling tasks in non-traditional manual handling industries continue to suffer debilitating and costly workplace injuries. Smart assistive devices are one solution to reducing musculoskeletal back injuries. Devices that provide targeted assistance need to be able to predict when and where to provide augmentation via predictive algorithms trained on functional datasets. The aim of this study was to describe how an increase in load impacts spine kinematics during a ground-to-platform manual handling task. Methods: Twenty-nine participants performed ground-to-platform lifts for six standardised loading conditions (50%, 60%, 70%, 80%, 90%, and 100% of maximum lift capacity). Six thoracic and lumbar spine segments were measured using inertial measurement units that were processed using an attitude-heading-reference filter and normalised to the duration of the lift. The lift was divided into four phases weight-acceptance, standing, lift-to-height and place-on-platform. Statistical significance of sagittal angles from the six spine segments were identified through statistical parametric mapping one-way analysis of variance with repeated measures and post hoc paired t-tests. Results: Two regions of interest were identified during a period of peak flexion and a period of peak extension. There was a significant increase in spine range of motion and peak extension angle for all spine segments when the load conditions were increased (p < 0.001). There was a decrease in spine angles (more flexion) during the weight acceptance to standing phase at the upper thoracic to upper lumbar spine segments for some condition comparisons. A significant increase in spine angles (more extension) during the place-on-platform phase was seen in all spine segments when comparing heavy loads (>80% maximum lift capacity, inclusive) to light loads (<80% maximum lift capacity) (p < 0.001). Discussion: The 50%-70% maximum lift capacity conditions being significantly different from heavier load conditions is representative that the kinematics of a lift do change consistently when a participant's load is increased. The understanding of how changes in loading are reflected in spine angles could inform the design of targeted assistance devices that can predict where and when in a task assistance may be needed, possibly reducing instances of back injuries in manual handling personnel.

Biomechanical characteristics of slipping during unconstrained walking, turning, gait initiation and termination.

Slipping biomechanics was investigated on both non-contaminated and oil-contaminated surfaces during unconstrained straight-line walking ('walking'), turning, gait initiation and termination. In walking, backward slipping was more frequent, whereas forward slipping was more frequent when turning. Stopping and gait initiation engendered only forward and backward slipping, respectively. Based on slip distance and sliding velocity, severity of forward slipping was least in walking than for the other gait tasks, whereas the tasks had similar effects on backward slipping. Relative to the dry surface, heel and foot contact angles reduced and heel contact (HC) velocity increased for all gait tasks on the contaminated surface. Ground reaction forces were generally lower on the contaminated surface, suggesting kinetic adaptation immediately following HC. Required coefficient of friction (RCoF) did not correlate with slip distance suggesting that RCoF may not be a useful kinetic parameter for assessing slipping risk on contaminated surfaces. PRACTITIONER SUMMARY: Slipping is hazardous in everyday locomotion and occupational settings. This study investigated foot control kinematics and kinetics across various gait tasks on both a non-contaminated and an oil-contaminated walking surface. Turning, gait termination and gait initiation were associated with a greater risk of slip-related falls than unconstrained walking.

A comparison of treadmill and overground walking effects on step cycle asymmetry in young and older individuals.

Although lower limb strength becomes asymmetrical with age, past studies of aging effects on gait biomechanics have usually analyzed only one limb. This experiment measured how aging and treadmill surface influenced both dominant and nondominant step parameters in older (mean 74.0 y) and young participants (mean 21.9 y). Step-cycle parameters were obtained from 3-dimensional position/time data during preferred-speed walking for 40 trials along a 10 m walkway and for 10 minutes of treadmill walking. Walking speed (young 1.23 m/s, older 1.24 m/s) and step velocity for the two age groups were similar in overground walking but older adults showed significantly slower walking speed (young 1.26 m/s, older 1.05 m/s) and step velocity on the treadmill due to reduced step length and prolonged step time. Older adults had shorter step length than young adults and both groups reduced step length on the treadmill. Step velocity and length of older adults' dominant limb was asymmetrically larger. Older adults increased the proportion of double support in step time when treadmill walking. This adaptation combined with reduced step velocity and length may preserve balance. The results suggest that bilateral analyses should be employed to accurately describe asymmetric features of gait especially for older adults.

Foot plantar pressure measurement system: a review.

Foot plantar pressure is the pressure field that acts between the foot and the support surface during everyday locomotor activities. Information derived from such pressure measures is important in gait and posture research for diagnosing lower limb problems, footwear design, sport biomechanics, injury prevention and other applications. This paper reviews foot plantar sensors characteristics as reported in the literature in addition to foot plantar pressure measurement systems applied to a variety of research problems. Strengths and limitations of current systems are discussed and a wireless foot plantar pressure system is proposed suitable for measuring high pressure distributions under the foot with high accuracy and reliability. The novel system is based on highly linear pressure sensors with no hysteresis.

Toe clearance and velocity profiles of young and elderly during walking on sloped surfaces.

BACKGROUND: Most falls in older adults are reported during locomotion and tripping has been identified as a major cause of falls. Challenging environments (e.g., walking on slopes) are potential interventions for maintaining balance and gait skills. The aims of this study were: 1) to investigate whether or not distributions of two important gait variables [minimum toe clearance (MTC) and foot velocity at MTC (VelMTC)] and locomotor control strategies are altered during walking on sloped surfaces, and 2) if altered, are they maintained at two groups (young and elderly female groups). METHODS: MTC and VelMTC data during walking on a treadmill at sloped surfaces (+3 degrees , 0 degrees and -3 degrees ) were analysed for 9 young (Y) and 8 elderly (E) female subjects. RESULTS: MTC distributions were found to be positively skewed whereas VelMTC distributions were negatively skewed for both groups on all slopes. Median MTC values increased (Y = 33%, E = 7%) at negative slope but decreased (Y = 25%, E = 15%) while walking on the positive slope surface compared to their MTC values at the flat surface (0 degrees ). Analysis of VelMTC distributions also indicated significantly (p < 0.05) lower minimum and 25th percentile (Q1) values in the elderly at all slopes. CONCLUSION: The young displayed a strong positive correlation between MTC median changes and IQR (interquartile range) changes due to walking on both slopes; however, such correlation was weak in the older adults suggesting differences in control strategies being employed to minimize the risk of tripping.

Feasibility of Using Foot-Ground Clearance Biofeedback Training in Treadmill Walking for Post-Stroke Gait Rehabilitation.

Hemiplegic stroke often impairs gait and increases falls risk during rehabilitation. Tripping is the leading cause of falls, but the risk can be reduced by increasing vertical swing foot clearance, particularly at the mid-swing phase event, minimum foot clearance (MFC). Based on previous reports, real-time biofeedback training may increase MFC. Six post-stroke individuals undertook eight biofeedback training sessions over a month, in which an infrared marker attached to the front part of the shoe was tracked in real-time, showing vertical swing foot motion on a monitor installed in front of the subject during treadmill walking. A target increased MFC range was determined, and participants were instructed to control their MFC within the safe range. Gait assessment was conducted three times: Baseline, Post-training and one month from the final biofeedback training session. In addition to MFC, step length, step width, double support time and foot contact angle were measured. After biofeedback training, increased MFC with a trend of reduced step-to-step variability was observed. Correlation analysis revealed that MFC height of the unaffected limb had interlinks with step length and ankle angle. In contrast, for the affected limb, step width variability and MFC height were positively correlated. The current pilot-study suggested that biofeedback gait training may reduce tripping falls for post-stroke individuals.

The application of support vector machines for detecting recovery from knee replacement surgery using spatio-temporal gait parameters.

Knee osteoarthritis (OA) is one of the leading causes of disability among the elderly which, depending on severity, may require surgical intervention. Knee replacement surgery provides pain relief and improves physical function including gait. However gait dysfunction such as altered spatio-temporal measures may persist after the surgery. In this paper, we investigated the application of support vector machines (SVM) to classify gait patterns indicative of knee OA before surgery based on 12 spatio-temporal gait parameters and investigated whether SVMs could be used to predict gait improvement 2 and 12 months following knee replacement surgery. Test results for the pre-operative data indicated that the SVM could successfully identify individuals with OA gait from the healthy using all of the spatio-temporal parameters with a maximum leave one out accuracy of 100% for the training set and 88.89% for the test set. Findings indicated that three patients still had altered gait patterns 2 months post-knee replacement surgery, but all individuals showed improvement in gait 12 months following surgery. Consequently, the SVM detected improvement in gait function due to surgical intervention at 2 and 12 months following knee replacement which coincided with clinical assessment of the knee. This suggests that spatio-temporal parameters contain important discriminative information which may be used for the identification of pathological gait using an SVM classifier.

Detection of tripping gait patterns in the elderly using autoregressive features and support vector machines.

Elderly tripping falls cost billions annually in medical funds and result in high mortality rates often perpetrated by pulmonary embolism (internal bleeding) and infected fractures that do not heal well. In this paper, we propose an intelligent gait detection system (AR-SVM) for screening elderly individuals at risk of suffering tripping falls. The motivation of this system is to provide early detection of elderly gait reminiscent of tripping characteristics so that preventive measures could be administered. Our system is composed of two stages, a predictor model estimated by an autoregressive (AR) process and a support vector machine (SVM) classifier. The system input is a digital signal constructed from consecutive measurements of minimum toe clearance (MTC) representative of steady-state walking. The AR-SVM system was tested on 23 individuals (13 healthy and 10 having suffered at least one tripping fall in the past year) who each completed a minimum of 10 min of walking on a treadmill at a self-selected pace. In the first stage, a fourth order AR model required at least 64 MTC values to correctly detect all fallers and non-fallers. Detection was further improved to less than 1 min of walking when the model coefficients were used as input features to the SVM classifier. The system achieved a detection accuracy of 95.65% with the leave one out method using only 16 MTC samples, but was reduced to 69.57% when eight MTC samples were used. These results demonstrate a fast and efficient system requiring a small number of strides and only MTC measurements for accurate detection of tripping gait characteristics.

Variability in the foot-ground clearance and step timing of young and older men during single-task and dual-task treadmill walking.

The study's aim was to document ageing effects on gait control by analysing the distributions of both left and right step timing and minimum foot-ground clearance (MFC) in older men (mean 71.1 years) and gender-matched controls (mean 26.3 years). Step durations and MFC were obtained from continuously sampled 3D markers during preferred-speed treadmill walking (single task) for 15 min and a dual-task condition in which participants walked at the same speed and also responded to the same 90 quasi-randomly presented visual reaction time (RT) stimuli. Significantly longer mean and median RTs were observed when treadmill walking compared to the standing-only control condition. Older males had significantly slower mean RTs for the standing and walking tasks (292 ms and 315 ms, respectively) than the younger group (265 ms and 273 ms). Older males walked more slowly, both groups had greater dual-task step durations but the effect was more pronounced in the older group. Older men's step durations were more positively skewed (longer) while the young had more negative skew. MFC was greater in the older group, and, importantly, in both groups right MFC was greater than the left foot. The data provide evidence of right-left limb asymmetry in preferred speed treadmill walking and it was hypothesised that behavioural slowing in locomotion could be a response to increase the safety of limb end-point control.

A comparative study on approximate entropy measure and poincaré plot indexes of minimum foot clearance variability in the elderly during walking.

BACKGROUND: Trip-related falls which is a major problem in the elderly population, might be linked to declines in the balance control function due to ageing. Minimum foot clearance (MFC) which provides a more sensitive measure of the motor function of the locomotor system, has been identified as a potential gait parameter associated with trip-related falls in older population. This paper proposes nonlinear indexes (approximate entropy (ApEn) and Poincaré plot indexes) of MFC variability and investigates the relationship of MFC with derived indexes of elderly gait patterns. The main aim is to find MFC variability indexes that well correlate with balance impairments. METHODS: MFC data during treadmill walking for 14 healthy elderly and 10 elderly participants with balance problems and a history of falls (falls risk) were analysed using a PEAK-2D motion analysis system. ApEn and Poincaré plot indexes of all MFC data sets were calculated and compared. RESULTS: Significant relationships of mean MFC with Poincaré plot indexes (SD1, SD2) and ApEn (r = 0.70, p < 0.05; r = 0.86, p < 0.01; r = 0.74, p < 0.05) were found in the falls-risk elderly group. On the other hand, such relationships were absent in the healthy elderly group. In contrast, the ApEn values of MFC data series were significantly (p < 0.05) correlated with Poincaré plot indexes of MFC in the healthy elderly group, whereas correlations were absent in the falls-risk group. The ApEn values in the falls-risk group (mean ApEn = 0.18 +/- 0.03) was significantly (p < 0.05) higher than that in the healthy group (mean ApEn = 0.13 +/- 0.13). The higher ApEn values in the falls-risk group might indicate increased irregularities and randomness in their gait patterns and an indication of loss of gait control mechanism. ApEn values of randomly shuffled MFC data of falls risk subjects did not show any significant relationship with mean MFC. CONCLUSION: Results have implication for quantifying gait dynamics in normal and pathological conditions, thus could be useful for the early diagnosis of at-risk gait. Further research should provide important information on whether falls prevention intervention can improve the gait performance of falls risk elderly by monitoring the change in MFC variability indexes.

Consensus paper on testing and evaluation of military exoskeletons for the dismounted combatant.

Enhancing the capabilities of the dismounted combatant has been an enduring goal of international military research communities. Emerging developments in exoskeleton technology offers the potential to augment the dismounted combatant's capabilities. However, the ability to determine the value proposition of an exoskeleton in a military context is difficult due to the variety of methods and metrics used to evaluate previous devices. The aim of this paper was to present a standard framework for the evaluation and assessment of exoskeletons for use in the military. A structured and systematic methodology was developed from the end-user perspective and progresses from controlled laboratory conditions (Stage A), to simulated movements specific to the dismounted combatant (Stage B), and real-world military specific tasks (Stage C). A standard set of objective and subjective metrics were described to ensure a holistic assessment on the human response to wearing the exoskeleton and the device's mechanical performance during each stage. A standardised methodology will ensure further advancement of exoskeleton technology and support improved international collaboration across research and industry groups. In doing so, this better enables international military groups to evaluate a system's potential, with the hope of accelerating the maturity and ultimately the fielding of devices to augment the dismounted close combatant and small team capability.

Wavelet-based feature extraction for support vector machines for screening balance impairments in the elderly.

Trip related falls are a prevalent problem in the elderly. Early identification of at-risk gait can help prevent falls and injuries. The main aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum foot clearance (MFC)] in comparison to MFC histogram plot analysis in extracting features for developing a model using support vector machines (SVMs) for screening of balance impairments in the elderly. MFC during walking on a treadmill was recorded on 13 healthy elderly and 10 elderly with a history of tripping falls. Features extracted from MFC histogram and then multiscale exponents between successive wavelet coefficient levels after wavelet decomposition of MFC series were used as inputs to the SVM to classify two gait patterns. The maximum accuracy of classification was found to be 100% for a SVM using a subset of selected wavelet based features, compared to 86.95% accuracy using statistical features. For estimating the relative risk of falls, the posterior probabilities of SVM outputs were calculated. These results suggest superior performance of SVM in the detection of balance impairments based on wavelet-based features and it could also be useful for evaluating for falls prevention intervention.

Effects of wide step walking on swing phase hip muscle forces and spatio-temporal gait parameters.

Human walking can be viewed essentially as a continuum of anterior balance loss followed by a step that re-stabilizes balance. To secure balance an extended base of support can be assistive but healthy young adults tend to walk with relatively narrower steps compared to vulnerable populations (e.g. older adults and patients). It was, therefore, hypothesized that wide step walking may enhance dynamic balance at the cost of disturbed optimum coupling of muscle functions, leading to additional muscle work and associated reduction of gait economy. Young healthy adults may select relatively narrow steps for a more efficient gait. The current study focused on the effects of wide step walking on hip abductor and adductor muscles and spatio-temporal gait parameters. To this end, lower body kinematic data and ground reaction forces were obtained using an Optotrak motion capture system and AMTI force plates, respectively, while AnyBody software was employed for muscle force simulation. A single step of four healthy young male adults was captured during preferred walking and wide step walking. Based on preferred walking data, two parallel lines were drawn on the walkway to indicate 50% larger step width and participants targeted the lines with their heels as they walked. In addition to step width that defined walking conditions, other spatio-temporal gait parameters including step length, double support time and single support time were obtained. Average hip muscle forces during swing were modeled. Results showed that in wide step walking step length increased, Gluteus Minimus muscles were more active while Gracilis and Adductor Longus revealed considerably reduced forces. In conclusion, greater use of abductors and loss of adductor forces were found in wide step walking. Further validation is needed in future studies involving older adults and other pathological populations.

Non-MTC gait cycles: An adaptive toe trajectory control strategy in older adults.

Minimum-toe-clearance (MTC) above the walking surface is a critical representation of toe-trajectory control due to its association with tripping risk. Not all gait cycles exhibit a clearly defined MTC within the swing phase but there have been few previous accounts of the biomechanical characteristics of non-MTC gait cycles. The present report investigated the within-subject non-MTC gait cycle characteristics of 15 older adults (mean 73.1 years) and 15 young controls (mean 26.1 years). Participants performed the following tasks on a motorized treadmill: preferred speed walking, dual task walking (carrying a glass of water) and a dual-task speed-matched control. Toe position-time coordinates were acquired using a 3 dimensional motion capture system. When MTC was present, toe height at MTC (MTCheight) was extracted. The proportion of non-MTC gait cycles was computed for the age groups and individuals. For non-MTC gait cycles an 'indicative' toe height at the individual's average swing phase time (MTCtime) for observed MTC cycles was averaged across multiple non-MTC gait cycles. In preferred-speed walking Young demonstrated 2.9% non-MTC gait cycles and Older 18.7%. In constrained walking conditions both groups increased non-MTC gait cycles and some older adults revealed over 90%, confirming non-MTC gait cycles as an ageing-related phenomenon in lower limb trajectory control. For all participants median indicative toe-height on non-MTC gait cycles was greater than median MTCheight. This result suggests that eliminating the biomechanically hazardous MTC event by adopting more of the higher-clearance non-MTC gait cycles, is adaptive in reducing the likelihood of toe-ground contact.

Support vector machines and other pattern recognition approaches to the diagnosis of cerebral palsy gait.

Accurate identification of cerebral palsy (CP) gait is important for diagnosis as well as for proper evaluation of the treatment outcomes. This paper explores the use of support vector machines (SVM) for automated detection and classification of children with CP using two basic temporal-spatial gait parameters (stride length and cadence) as input features. Application of the SVM method to a children's dataset (68 normal healthy and 88 with spastic diplegia form of CP) and testing on tenfold cross-validation scheme demonstrated that an SVM classifier was able to classify the children groups with an overall accuracy of 83.33% [sensitivity 82.95%, specificity 83.82%, area under the receiver operating curve (AUC-ROC = 0.88)]. Classification accuracy improved significantly when the gait parameters were normalized by the individual leg length and age, leading to an overall accuracy of 96.80% (sensitivity 94.32%, specificity 100%, AUC-ROC area = 0.9924). This accuracy result was, respectively, 3.21% and 1.93% higher when compared to an linear discriminant analysis and an multilayer-perceptron-based classifier. SVM classifier also attains considerably higher ROC area than the other two classifiers. Among the four SVM kernel functions (linear, polynomial, radial basis, and analysis of variance spline) studied, the polynomial and radial basis kernel performed comparably and outperformed the others. Classifier's performance as functions of regularization and kernel parameters was also investigated. The enhanced classification accuracy of the SVM using only two easily obtainable basic gait parameters makes it attractive for identifying CP children as well as for evaluating the effectiveness of various treatment methods and rehabilitation techniques.