801 resultados para walking speed
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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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OBJECTIVE: To compare the mechanical external work (Wext ) and pendular energy transduction (Rstep ) at spontaneous walking speed (Ss ) in individuals with Prader-Willi syndrome (PWS) versus subjects with nonsyndromal obesity (OB) to investigate whether the early onset of obesity allows PWS subjects to adopt energy conserving gait mechanics. DESIGN AND METHODS: Wext and Rstep were computed using kinematic data acquired by an optoelectronic system and compared in 15 PWS (BMI = 39.5 ± 1.8 kg m(-2) ; 26.7 ± 1.5 year) and 15 OB (BMI = 39.3 ± 1.0 kg m(-2) ; 28.7 ± 1.9 year) adults matched for gender, age and BMI and walking at Ss . RESULTS: Ss was significantly lower in PWS (0.98 ± 0.03 m s(-1) ) than in OB (1.20 ± 0.02 m s(-1) ; P < 0.001). There were no significant differences in Wext per kilogram between groups (PWS: 0.37 ± 0.04 J kg(-1) m(-1) ; OB: 0.40 ± 0.05 J kg(-1) m(-1) ; P = 0.66) and in Rstep (PWS: 69.9 ± 2.9%; OB: 67.7 ± 2.4%; P = 0.56). However, Rstep normalized to Froude number (Rstep /Fr) was significantly greater in PWS (6.0 ± 0.6) than in OB (3.8 ± 0.2; P = 0.001). Moreover, Rstep /Fr was inversely correlated with age of obesity onset (r = -0.49; P = 0.006) and positively correlated with obesity duration (r = 0.38; P = 0.036). CONCLUSION: Individuals with PWS seem to alter their gait to improve pendular energy transduction as a result of precocious and chronic adaptation to loading.
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Activity monitors based on accelerometry are used to predict the speed and energy cost of walking at 0% slope, but not at other inclinations. Parallel measurements of body accelerations and altitude variation were studied to determine whether walking speed prediction could be improved. Fourteen subjects walked twice along a 1.3 km circuit with substantial slope variations (-17% to +17%). The parameters recorded were body acceleration using a uni-axial accelerometer, altitude variation using differential barometry, and walking speed using satellite positioning (DGPS). Linear regressions were calculated between acceleration and walking speed, and between acceleration/altitude and walking speed. These predictive models, calculated using the data from the first circuit run, were used to predict speed during the second circuit. Finally the predicted velocity was compared with the measured one. The result was that acceleration alone failed to predict speed (mean r = 0.4). Adding altitude variation improved the prediction (mean r = 0.7). With regard to the altitude/acceleration-speed relationship, substantial inter-individual variation was found. It is concluded that accelerometry, combined with altitude measurement, can assess position variations of humans provided inter-individual variation is taken into account. It is also confirmed that DGPS can be used for outdoor walking speed measurements, opening up new perspectives in the field of biomechanics.
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BACKGROUND: Lower ambulatory performance with aging may be related to a reduced oxidative capacity within skeletal muscle. This study examined the associations between skeletal muscle mitochondrial capacity and efficiency with walking performance in a group of older adults. METHODS: Thirty-seven older adults (mean age 78 years; 21 men and 16 women) completed an aerobic capacity (VO peak) test and measurement of preferred walking speed over 400 m. Maximal coupled (State 3; St3) mitochondrial respiration was determined by high-resolution respirometry in saponin-permeabilized myofibers obtained from percutanous biopsies of vastus lateralis (n = 22). Maximal phosphorylation capacity (ATP) of vastus lateralis was determined in vivo by P magnetic resonance spectroscopy (n = 30). Quadriceps contractile volume was determined by magnetic resonance imaging. Mitochondrial efficiency (max ATP production/max O consumption) was characterized using ATP per St3 respiration (ATP/St3). RESULTS: In vitro St3 respiration was significantly correlated with in vivo ATP (r = .47, p = .004). Total oxidative capacity of the quadriceps (St3*quadriceps contractile volume) was a determinant of VO peak (r = .33, p = .006). ATP (r = .158, p = .03) and VO peak (r = .475, p < .0001) were correlated with preferred walking speed. Inclusion of both ATP/St3 and VO peak in a multiple linear regression model improved the prediction of preferred walking speed (r = .647, p < .0001), suggesting that mitochondrial efficiency is an important determinant for preferred walking speed. CONCLUSIONS: Lower mitochondrial capacity and efficiency were both associated with slower walking speed within a group of older participants with a wide range of function. In addition to aerobic capacity, lower mitochondrial capacity and efficiency likely play roles in slowing gait speed with age.
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OBJECTIVE: Maintenance of good walking speed is essential to independent living. People with musculoskeletal disease often have reduced walking speed. We investigated determinants of slower walking, other than musculoskeletal disease, that might provide valuable additional targets for therapy. METHODS: We analyzed data from the Somerset and Avon Survey of Health, a community based survey of people aged over 35 years. A total of 2703 participants who reported hip or knee pain at baseline (1994/1995) were studied, and reassessed in 2002-2003; 1696 were available for followup, and walking speed was tested in 1074. Walking speed (m/s) was used as outcome measure. Baseline characteristics, including comorbidities and socioeconomic factors, were tested for their ability to predict reduced walking speed using multiple linear regression analysis. RESULTS: Age, female sex, and immobility at baseline were predictive of slower walking speed. Other independent risk factors included the presence of cataract, low socioeconomic status, intermittent claudication, and other cardiovascular conditions. Having a cataract was associated with a decrease of 0.10 m/s (95% CI 0.03, 0.16). Those in social class V had a walking speed 0.22 m/s (95% CI 0.126, 0.31) slower than those in social class I. CONCLUSION: Comorbidities, age, female sex, and lower socioeconomic position determine walking speed in people with joint pain. Issues such as poor vision and social-economic disadvantage may add to the effect of musculoskeletal disease, suggesting the need for a holistic approach to management of these patients.
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Purpose: This study was conducted to devise a new individual calibration method to enhance MTI accelerometer estimation of free-living level walking speed. Method: Five female and five male middle-aged adults walked 400 m at 3.5, 4.5, and 5.5 km(.)h(-1), and 800 in at 6.5 km(.)h(-1) on an outdoor track, following a continuous protocol. Lap speed was controlled by a global positioning system (GPS) monitor. MTI counts-to-speed calibration equations were derived for each trial, for each subject for four such trials with each of four MTI, for each subject for the average MTI. and for the pooled data. Standard errors of the estimate (SEE) with and without individual calibration were compared. To assess accuracy of prediction of free-living walking speed, subjects also completed a self-paced, brisk 3-km walk wearing one of the four MTI, and differences between actual and predicted walking speed with and without individual calibration were examined. Results: Correlations between MTI counts and walking speed were 0.90 without individual calibration, 0.98 with individual calibration for the average MTI. and 0.99 with individual calibration for a specific MTI. The SEE (mean +/- SD) was 0.58 +/- 0.30 km(.)h(-1) without individual calibration, 0.19 +/- 0.09 km h(-1) with individual calibration for the average MTI monitor, and 0.16 +/- 0.08 km(.)h(-1) with individual calibration for a specific MTI monitor. The difference between actual and predicted walking speed on the brisk 3-km walk was 0.06 +/- 0.25 km(.)h(-1) using individual calibration and 0.28 +/- 0.63 km(.)h(-1) without individual calibration (for specific accelerometers). Conclusion: MTI accuracy in predicting walking speed without individual calibration might be sufficient for population-based studies but not for intervention trials. This individual calibration method will substantially increase precision of walking speed predicted from MTI counts.
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PURPOSE: Activity monitoring is considered a highly relevant outcome measure of respiratory rehabilitation. This study aimed to assess the usefulness of a new accelerometric method for characterization of walking activity during a 3-week inpatient rehabilitation program. METHODS: After individual calibration of the accelerometer at different walking speeds, whole-day physical activity was recorded for 15 patients with chronic obstructive pulmonary disease on the first and the last days of the program, and for 10 healthy subjects. Data were expressed as percentage of time spent in inactivity, low level activity, and medium level activity, with the latter corresponding to usual walking speed. RESULTS: The patients spent more time being inactive and less time walking than healthy subjects. At the end of the rehabilitation program, medium level activity had increased from 4% to 7% of total recording time. However, the change was not significant after periods of imposed exercise training were excluded. Walking activity increased to a greater degree among the patients with preserved limb muscle strength at entry to the program. Although health status scores improved, the changes did not correlate with the changes in walking activity. CONCLUSION: The findings lead to the conclusion that this new accelerometric method provides detailed analysis of walking activity during respiratory rehabilitation and may represent an additional useful measure of outcome.
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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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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.
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OBJECTIVE: To describe a method to obtain a profile of the duration and intensity (speed) of walking periods over 24 hours in women under free-living conditions. DESIGN: A new method based on accelerometry was designed for analyzing walking activity. In order to take into account inter-individual variability of acceleration, an individual calibration process was used. Different experiments were performed to highlight the variability of acceleration vs walking speed relationship, to analyze the speed prediction accuracy of the method, and to test the assessment of walking distance and duration over 24-h. SUBJECTS: Twenty-eight women were studied (mean+/-s.d.) age: 39.3+/-8.9 y; body mass: 79.7+/-11.1 kg; body height: 162.9+/-5.4 cm; and body mass index (BMI) 30.0+/-3.8 kg/m(2). RESULTS: Accelerometer output was significantly correlated with speed during treadmill walking (r=0.95, P<0.01), and short unconstrained walks (r=0.86, P<0.01), although with a large inter-individual variation of the regression parameters. By using individual calibration, it was possible to predict walking speed on a standard urban circuit (predicted vs measured r=0.93, P<0.01, s.e.e.=0.51 km/h). In the free-living experiment, women spent on average 79.9+/-36.0 (range: 31.7-168.2) min/day in displacement activities, from which discontinuous short walking activities represented about 2/3 and continuous ones 1/3. Total walking distance averaged 2.1+/-1.2 (range: 0.4-4.7) km/day. It was performed at an average speed of 5.0+/-0.5 (range: 4.1-6.0) km/h. CONCLUSION: An accelerometer measuring the anteroposterior acceleration of the body can estimate walking speed together with the pattern, intensity and duration of daily walking activity.
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PURPOSE: This descriptive article illustrates the application of Global Positioning System (GPS) professional receivers in the field of locomotion studies. The technological challenge was to assess the external mechanical work in outdoor walking. METHODS: Five subjects walked five times during 5 min on an athletic track at different imposed stride frequency (from 70-130 steps x min(-1)). A differential GPS system (carrier phase analysis) measured the variation of the position of the trunk at 5 Hz. A portable indirect calorimeter recorded breath-by-breath energy expenditure. RESULTS: For a walking speed of 1.05 +/- 0.11 m x s(-1), the vertical lift of the trunk (43 +/- 14 mm) induced a power of 46.0 +/- 20.4 W. The average speed variation per step (0.15 +/- 0.03 m x s(-1)) produced a kinetic power of 16.9 +/- 7.2 W. As compared with commonly admitted values, the energy exchange (recovery) between the two energy components was low (39.1 +/- 10.0%), which induced an overestimated mechanical power (38.9 +/- 18.3 W or 0.60 W x kg(-1) body mass) and a high net mechanical efficiency (26.9 +/- 5.8%). CONCLUSION: We assumed that the cause of the overestimation was an unwanted oscillation of the GPS antenna. It is concluded that GPS (in phase mode) is now able to record small body movements during human locomotion, and constitutes a promising tool for gait analysis of outdoor unrestrained walking. However, the design of the receiver and the antenna must be adapted to human experiments and a thorough validation study remains to be conducted.
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PURPOSE: Walking in patients with chronic low back pain (cLBP) is characterized by motor control adaptations as a protective strategy against further injury or pain. The purpose of this study was to compare the preferred walking speed, the biomechanical and the energetic parameters of walking at different speeds between patients with cLBP and healthy men individually matched for age, body mass and height. METHODS: Energy cost of walking was assessed with a breath-by-breath gas analyser; mechanical and spatiotemporal parameters of walking were computed using two inertial sensors equipped with a triaxial accelerometer and gyroscope and compared in 13 men with cLBP and 13 control men (CTR) during treadmill walking at standard (0.83, 1.11, 1.38, 1.67 m s(-1)) and preferred (PWS) speeds. Low back pain intensity (visual analogue scale, cLBP only) and perceived exertion (Borg scale) were assessed at each walking speed. RESULTS: PWS was slower in cLBP [1.17 (SD = 0.13) m s(-1)] than in CTR group [1.33 (SD = 0.11) m s(-1); P = 0.002]. No significant difference was observed between groups in mechanical work (P ≥ 0.44), spatiotemporal parameters (P ≥ 0.16) and energy cost of walking (P ≥ 0.36). At the end of the treadmill protocol, perceived exertion was significantly higher in cLBP [11.7 (SD = 2.4)] than in CTR group [9.9 (SD = 1.1); P = 0.01]. Pain intensity did not significantly increase over time (P = 0.21). CONCLUSIONS: These results do not support the hypothesis of a less efficient walking pattern in patients with cLBP and imply that high walking speeds are well tolerated by patients with moderately disabling cLBP.
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BACKGROUND: Habitual walking speed predicts many clinical conditions later in life, but it declines with age. However, which particular exercise intervention can minimize the age-related gait speed loss is unclear. PURPOSE: Our objective was to determine the effects of strength, power, coordination, and multimodal exercise training on healthy old adults' habitual and fast gait speed. METHODS: We performed a computerized systematic literature search in PubMed and Web of Knowledge from January 1984 up to December 2014. Search terms included 'Resistance training', 'power training', 'coordination training', 'multimodal training', and 'gait speed (outcome term). Inclusion criteria were articles available in full text, publication period over past 30 years, human species, journal articles, clinical trials, randomized controlled trials, English as publication language, and subject age ≥65 years. The methodological quality of all eligible intervention studies was assessed using the Physiotherapy Evidence Database (PEDro) scale. We computed weighted average standardized mean differences of the intervention-induced adaptations in gait speed using a random-effects model and tested for overall and individual intervention effects relative to no-exercise controls. RESULTS: A total of 42 studies (mean PEDro score of 5.0 ± 1.2) were included in the analyses (2495 healthy old adults; age 74.2 years [64.4-82.7]; body mass 69.9 ± 4.9 kg, height 1.64 ± 0.05 m, body mass index 26.4 ± 1.9 kg/m(2), and gait speed 1.22 ± 0.18 m/s). The search identified only one power training study, therefore the subsequent analyses focused only on the effects of resistance, coordination, and multimodal training on gait speed. The three types of intervention improved gait speed in the three experimental groups combined (n = 1297) by 0.10 m/s (±0.12) or 8.4 % (±9.7), with a large effect size (ES) of 0.84. Resistance (24 studies; n = 613; 0.11 m/s; 9.3 %; ES: 0.84), coordination (eight studies, n = 198; 0.09 m/s; 7.6 %; ES: 0.76), and multimodal training (19 studies; n = 486; 0.09 m/s; 8.4 %, ES: 0.86) increased gait speed statistically and similarly. CONCLUSIONS: Commonly used exercise interventions can functionally and clinically increase habitual and fast gait speed and help slow the loss of gait speed or delay its onset.