907 resultados para Gait speed
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Objetivo: Determinar la distribución por percentiles de salto con contramovimiento (CMJ) en una población escolar de Bogotá, Colombia, perteneciente al estudio Fuprecol. Métodos: Estudio transversal realizado entre 2846 niños y 2754 adolescentes, entre 9 a 17 años de edad, pertenecientes a 18 instituciones educativas oficiales de Bogotá, Colombia. Se evaluó el CMJ, de acuerdo, con lo establecido por la batería de condición física, Fuprecol. Se calcularon, los percentiles (P3, P10, P25, P50, P75, P90 y P97), y curvas centiles por el método LMS, según su sexo y edad. Se realizó una comparación entre los valores de la CMJ observados con estándares internacionales. Resultados: La muestra estuvo constituida por 5.600 niños y adolescentes entre 9 y 17 años; el promedio de edad fue 12,6 ± 2,4 años. En el CMJ, los valores altos, los obtuvieron los niños, franja en la que la media osciló entre 25,1 cm a los 9 años, y 38,6 cm a los 17; para las niñas, la media fluctuó entre 23,2 cm a los 9 años, y 28,6 a los 17; en ambos sexos esos valores aumentan proporcional a la edad. Conclusiones: Se registran percentiles del CMJ de acuerdo con la edad y el sexo, que podrán ser usados como referencia en la evaluación del salto vertical desde edades tempranas.
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Due to the intensive use of mobile phones for diferent purposes, these devices usually contain condential information which must not be accessed by another person apart from the owner of the device. Furthermore, the new generation phones commonly incorporate an accelerometer which may be used to capture the acceleration signals produced as a result of owner s gait. Nowadays, gait identication in basis of acceleration signals is being considered as a new biometric technique which allows blocking the device when another person is carrying it. Although distance based approaches as Euclidean distance or dynamic time warping have been applied to solve this identication problem, they show di±culties when dealing with gaits at diferent speeds. For this reason, in this paper, a method to extract an average template from instances of the gait at diferent velocities is presented. This method has been tested with the gait signals of 34 subjects while walking at diferent motion speeds (slow, normal and fast) and it has shown to improve the performance of Euclidean distance and classical dynamic time warping.
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Objective Adapt the 6 minutes walking test (6MWT) to artificial gait in complete spinal cord injured (SCI) patients aided by neuromuscular electrical stimulation. Method Nine male individuals with paraplegia (AIS A) participated in this study. Lesion levels varied between T4 and T12 and time post injured from 4 to 13 years. Patients performed 6MWT 1 and 6MWT 2. They used neuromuscular electrical stimulation, and were aided by a walker. The differences between two 6MWT were assessed by using a paired t test. Multiple r-squared was also calculated. Results The 6MWT 1 and 6MWT 2 were not statistically different for heart rate, distance, mean speed and blood pressure. Multiple r-squared (r2 = 0.96) explained 96% of the variation in the distance walked. Conclusion The use of 6MWT in artificial gait towards assessing exercise walking capacity is reproducible and easy to apply. It can be used to assess SCI artificial gait clinical performance.
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This work deals with neural network (NN)-based gait pattern adaptation algorithms for an active lower-limb orthosis. Stable trajectories with different walking speeds are generated during an optimization process considering the zero-moment point (ZMP) criterion and the inverse dynamic of the orthosis-patient model. Additionally, a set of NNs is used to decrease the time-consuming analytical computation of the model and ZMP. The first NN approximates the inverse dynamics including the ZMP computation, while the second NN works in the optimization procedure, giving an adapted desired trajectory according to orthosis-patient interaction. This trajectory adaptation is added directly to the trajectory generator, also reproduced by a set of NNs. With this strategy, it is possible to adapt the trajectory during the walking cycle in an on-line procedure, instead of changing the trajectory parameter after each step. The dynamic model of the actual exoskeleton, with interaction forces included, is used to generate simulation results. Also, an experimental test is performed with an active ankle-foot orthosis, where the dynamic variables of this joint are replaced in the simulator by actual values provided by the device. It is shown that the final adapted trajectory follows the patient intention of increasing the walking speed, so changing the gait pattern. (C) Koninklijke Brill NV, Leiden, 2011
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The purpose of this study was to determine the attentional demands of natural and imposed gait, as well as the attentional costs of transitions between the walking and running co-ordination patterns. Seven healthy young men and four healthy young women undertook an auditory probe reaction time task concurrently with self-selected gait (Experiment 1) and imposed walking and running (Experiment 2) at different speeds on a motor-driven treadmill. In Experiment 1, where participants were free to choose their own movement pattern to match the speed of travel of the treadmill, normal gait control was shown to have a significant attentional cost, and hence not be automatic in the classical sense. However, this attentional cost did not differ between the two gait modes or at the transition point. In Experiment 2, where participants were required to maintain specific gait modes regardless of the treadmill speed, the maintenance of walking at speeds normally associated with running was found to have an attentional cost whereas this was not the case for running at normal walking speeds. Collectively the findings support a model of gait control in which the normal switching between gait modes is determined with minimal attention demand and in which it is possible to sustain non-preferred gait modes although, in the case of walking, only at a significant attentional/cognitive cost. © 2002 Elsevier Science B.V. All rights reserved.
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It is currently unclear whether it is the need to maintain metabolic efficiency, the need to keep skeletal loading below critical force levels, or simple mechanical factors that drive the walk-to-run (W R) and run-to-walk (R-W) transitions in human gait. Eighteen adults (9 males and 9 females) locomoted on an instrumented treadmill using their preferred gait. Each completed 2 ascending (W-R) and 2 descending (R-W) series of trials under three levels of loading (0%, 15% and 30% body weight). For each trial, participants locomoted for 60 s at each of 9 different speeds -4 speeds both above and below their preferred transition speed (PTS) plus their PTS. Evidence was sought for critical levels of key kinetic (maximum vertical force, impulse, first peak force, time to first peak force and maximum loading rate), energetic (oxygen consumption, transport cost) and mechanical variables (limb lengths, strength) predictive of the gait transition. Analyses suggested the kinetic variables of time to first peak force and loading rate as the most likely determinants of the W-R and R-W transitions. (C) 2003 Elsevier Science B.V. All rights reserved.
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Objective To investigate the relation between gait parameters and cognitive impairments in subjects with Parkinson’s disease (PD) and Alzheimer’s disease (AD) during the performance of dual tasks. Methods This was a cross-sectional study involving 126 subjects divided into three groups: Parkinson group (n = 43), Alzheimer group (n = 38), and control group (n = 45). The subjects were evaluated using the Timed Up and Go test administered with motor and cognitive distracters. Gait analyses consisted of cadence and speed measurements, with cognitive functions being assessed by the Brief Cognitive Screening Battery and the Clock Drawing Test. Statistical procedures included mixed-design analyses of variance to observe the gait patterns between groups and tasks and the linear regression model to investigate the influence of cognitive functions in this process. A 5% significant level was adopted. Results Regarding the subjects’ speed, the data show a significant difference between group vs task interaction (p = 0.009), with worse performance of subjects with PD in motor dual task and of subjects with AD in cognitive dual task. With respect to cadence, no statistical differences was seen between group vs task interaction (p = 0.105), showing low interference of the clinical conditions on such parameter. The linear regression model showed that up to 45.79%, of the variance in gait can be explained by the interference of cognitive processes. Conclusion Dual task activities affect gait pattern in subjects with PD and AD. Differences between groups reflect peculiarities of each disease and show a direct interference of cognitive processes on complex tasks.
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Introduction: Coordination is a strategy chosen by the central nervous system to control the movements and maintain stability during gait. Coordinated multi-joint movements require a complex interaction between nervous outputs, biomechanical constraints, and pro-prioception. Quantitatively understanding and modeling gait coordination still remain a challenge. Surgeons lack a way to model and appreciate the coordination of patients before and after surgery of the lower limbs. Patients alter their gait patterns and their kinematic synergies when they walk faster or slower than normal speed to maintain their stability and minimize the energy cost of locomotion. The goal of this study was to provide a dynamical system approach to quantitatively describe human gait coordination and apply it to patients before and after total knee arthroplasty. Methods: A new method of quantitative analysis of interjoint coordination during gait was designed, providing a general model to capture the whole dynamics and showing the kinematic synergies at various walking speeds. The proposed model imposed a relationship among lower limb joint angles (hips and knees) to parameterize the dynamics of locomotion of each individual. An integration of different analysis tools such as Harmonic analysis, Principal Component Analysis, and Artificial Neural Network helped overcome high-dimensionality, temporal dependence, and non-linear relationships of the gait patterns. Ten patients were studied using an ambulatory gait device (Physilog®). Each participant was asked to perform two walking trials of 30m long at 3 different speeds and to complete an EQ-5D questionnaire, a WOMAC and Knee Society Score. Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. The outcomes of the eight patients undergoing total knee arthroplasty, recorded pre-operatively and post-operatively at 6 weeks, 3 months, 6 months and 1 year were compared to 2 age-matched healthy subjects. Results: The new method provided coordination scores at various walking speeds, ranged between 0 and 10. It determined the overall coordination of the lower limbs as well as the contribution of each joint to the total coordination. The difference between the pre-operative and post-operative coordination values were correlated with the improvements of the subjective outcome scores. Although the study group was small, the results showed a new way to objectively quantify gait coordination of patients undergoing total knee arthroplasty, using only portable body-fixed sensors. Conclusion: A new method for objective gait coordination analysis has been developed with very encouraging results regarding the objective outcome of lower limb surgery.
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PURPOSE: The aim of this study was to compare the mechanical external work (per kg) and pendular energy transduction at preferred walking speed (PWS) in obese versus normal body mass subjects to investigate whether obese adults adopt energy conserving gait mechanics. METHODS: The mechanical external work (Wext) and the fraction of mechanical energy recovered by the pendular mechanism (Rstep) were computed using kinematic data acquired by an optoelectronic system and were compared in 30 obese (OG; body mass index [BMI] = 39.6 +/- 0.6 kg m(-2); 29.5 +/- 1.3 yr) and 19 normal body mass adults (NG; BMI = 21.4 +/- 0.5 kg m(-2); 31.2 +/- 1.2 yr) walking at PWS. RESULTS: PWS was significantly lower in OG (1.18 +/- 0.02 m s(-1)) than in NG (1.33 +/- 0.02 m s(-1); P <or= 0.001). There was no significant difference in Wext per unit mass between groups (OG: 0.36 +/- 0.03 J kg(-1) m(-1); NG: 0.31 +/- 0.02 J kg(-1) m(-1); P = 0.12). Rstep was significantly lower in OG (68.4% +/- 2.0%) compared with NG (74.4% +/- 1.0%; P = 0.01). In OG only, Wext per unit mass was positively correlated with PWS (r = 0.57; P < 0.001). CONCLUSION: Obese adults do not appear to alter their gait to improve pendular energy transduction and may select slower PWS to reduce mechanical and metabolic work.
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A child's natural gait pattern may be affected by the gait laboratory environment. Wearable devices using body-worn sensors have been developed for gait analysis. The purpose of this study was to validate and explore the use of foot-worn inertial sensors for the measurement of selected spatio-temporal parameters, based on the 3D foot trajectory, in independently walking children with cerebral palsy (CP). We performed a case control study with 14 children with CP aged 6-15 years old and 15 age-matched controls. Accuracy and precision of the foot-worn device were measured using an optical motion capture system as the reference system. Mean accuracy±precision for both groups was 3.4±4.6cm for stride length, 4.3±4.2cm/s for speed and 0.5±2.9° for strike angle. Longer stance and shorter swing phases with an increase in double support were observed in children with CP (p=0.001). Stride length, speed and peak angular velocity during swing were decreased in paretic limbs, with significant differences in strike and lift-off angles. Children with cerebral palsy showed significantly higher inter-stride variability (measured by their coefficient of variation) for speed, stride length, swing and stance. During turning trajectories speed and stride length decreased significantly (p<0.01) for both groups, whereas stance increased significantly (p<0.01) in CP children only. Foot-worn inertial sensors allowed us to analyze gait spatiotemporal data outside a laboratory environment with good accuracy and precision and congruent results with what is known of gait variations during linear walking in children with CP.
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It is established that the ratio between step length (SL) and step frequency (SF) is constant over a large range of walking speed. However, few data are available about the spontaneous variability of this ratio during unconstrained outdoor walking, in particular over a sufficient number of steps. The purpose of the present study was to assess the inter- and intra-subject variability of spatio-temporal gait characteristics [SL, SF and walk ratio (WR=SL/SF)] while walking at different freely selected speeds. Twelve healthy subjects walked three times along a 100-m athletic track at: (1). a slower than preferred speed, (2). preferred speed and (3). a faster than preferred speed. Two professional GPS receivers providing 3D positions assessed the walking speed and SF with high precision (less than 0.5% error). Intra-subject variability was calculated as the variation among eight consecutive 5-s samples. WR was found to be constant at preferred and fast speeds [0.41 (0.04) m.s and 0.41 (0.05) m.s respectively] but was higher at slow speeds [0.44 (0.05) m.s]. In other words, between slow and preferred speed, the speed increase was mediated more by a change in SF than SL. The intra-subject variability of WR was low under preferred [CV, coefficient of variation = 1.9 (0.6)%] and fast [CV=1.8 (0.5)%] speed conditions, but higher under low speed condition [CV=4.1 (1.5)%]. On the other hand, the inter-subject variability of WR was 11%, 10% and 12% at slow, preferred and fast walking speeds respectively. It is concluded that the GPS method is able to capture basic gait parameters over a short period of time (5 s). A specific gait pattern for slow walking was observed. Furthermore, it seems that the walking patterns in free-living conditions exhibit low intra-individual variability, but that there is substantial variability between subjects.
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Background: Mobile-bearing knee replacements have some theoretical advantages over fixed-bearing devices. However, very few randomized controlled clinical trials have been published to date, and studies showed little clinical and subjective advantages for the mobile-bearing using traditional systems of scoring. The choice of the ideal outcome measure to assess total joint replacement remains a complex issue. However, gait analysis provides objective and quantifying evidences of treatment evaluation. Significant methodological advances are currently made in gait analysis laboratories and ambulatory gait devices are now available. The goal of this study was to provide gait parameters as a new objective method to assess total knee arthroplasty outcome between patients with fixed- and mobile-bearing, using an ambulatory device with minimal sensor configuration. Methods: This randomized controlled double-blind study included to date 31 patients: the gait signatures of 12 patients with mobile-bearing were compared to the gait signatures of 19 patients with fixed-bearing pre-operatively and post-operatively at 6 weeks, 3 months and 6 months. Each participant was asked to perform two walking trials of 30m long at his/her preferred speed and to complete a EQ-5D questionnaire, a WOMAC and Knee Society Score (KSS). Lower limbs rotations were measured by four miniature angular rate sensors mounted respectively, on each shank and thigh. Results: Better relative differences between pre-operative and post-operative 3 months and 6 months KSS (122% vs 34% at 3 months, 138% vs 36% at 6 months) and KSS function (154% vs 8% at 3 months, 183% vs 42% at 6 months) scores were observed for the fixed-bearing compared to the mobile-bearing. The same better improvements for fixed-bearing were also found with the range of knee angles (Affected side: 31% vs -5% at 3 months, 47% vs 5% at 6 months), (Unaffected side: 16% vs 5% at 3 months, 15% vs 6% at 6 months) and peak swing speeds of shank (Affected side: 18% vs -2% at 3 months, 30% vs 4% at 6 months), (Unaffected side: 8% vs -3% at 3 months, 7% vs 4% at 6 months). Conclusions: A new method for a portable system for gait analysis has been developed with very encouraging results regarding the objective outcome of total knee arthroplasty using mobile- and fixed-bearings.
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This study tested whether the lower economy of walking in healthy elderly subjects is due to greater gait instability. We compared the energy cost of walking and gait instability (assessed by stride to stride changes in the stride time) in octogenarians (G80, n = 10), 65-yr-olds (G65, n = 10), and young controls (G25, n = 10) walking on a treadmill at six different speeds. The energy cost of walking was higher for G80 than for G25 across the different walking speeds (P < 0.05). Stride time variability at preferred walking speed was significantly greater in G80 (2.31 +/- 0.68%) and G65 (1.93 +/- 0.39%) compared with G25 (1.40 +/- 0.30%; P < 0.05). There was no significant correlation between gait instability and energy cost of walking at preferred walking speed. These findings demonstrated greater energy expenditure in healthy elderly subjects while walking and increased gait instability. However, no relationship was noted between these two variables. The increase in energy cost is probably multifactorial, and our results suggest that gait instability is probably not the main contributing factor in this population. We thus concluded that other mechanisms, such as the energy expenditure associated with walking movements and related to mechanical work, or neuromuscular factors, are more likely involved in the higher cost of walking in elderly people.
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The aim of this study was to examine the effect of an individualized overground walking interval training on gait performance [i.e., speed and energy cost (C(w))] in healthy elderly individuals. Twenty-two older adults were assigned to either a training group (TG; n=12, 73.4+/-3.9yr) or a non-training control group (CG; n=10, 70.9+/-9.6yr). TG participated in a 7-week individualized walking interval training at intensities progressing from 50 to 100% of ventilatory threshold (T (VE)). Aerobic fitness [maximal oxygen uptake (V O(2max)) and T (VE)], preferred walking speed (PWS), gross and net C(w) (GC(w) and NC(w), respectively) and relative effort (%V O(2max)) at PWS measured before training (PWS(1)) were assessed prior and following the intervention. All outcomes were measured on a treadmill. Significant improvements in GC(w) (-8%; P=0.007), NC(w) (-12%; P=0.003), relative effort (%V O(2max): -12%; P<0.001) and PWS (+12%; P<0.001) were observed in TG but not in CG (P>0.71). V O(2max) and T (VE) remained unchanged in both groups (P>0.57). Changes in GC(w) at PWS(1) (difference between GC(w) at PWS(1) measured pre and post intervention) were inversely correlated with changes in PWS (difference between pre and post PWS; r=-0.67; P=0.02). The decreased C(w) at PWS(1), with no concomitant improvement in aerobic fitness, represents the main contributing factor for the reduction of the relative effort at this speed. This also allows elderly people to increase their PWS post training. Therefore, the present walking training may be an effective way to improve walking performance and delay mobility impairment in older adults.