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We investigated the acute effects of caffeine supplementation (6 mgï½¥kg-1 ) on 60-m sprint performance and underlying components with a step-to-step ground reaction force measurement in 13 male sprinters. After the first round sprint as a control, caffeine supplementation-induced improvement in 60-m sprint times (7.811 s at the first versus 7.648 s at the second round, 2.05%) were greater compared with the placebo condition (7.769 s at the first versus 7.768 s at the second round, 0.02%). Using average values for every four steps, in the caffeine condition, higher running speed (all six step groups), higher step frequency (5th-16th and 21st-24th step groups), shorter support time (all the step groups except for 13th-16th step) and shorter braking time (9th-24th step groups) were found. Regarding ground reaction forces variables, greater braking mean force (13th-19th step group), propulsive mean force (1st-12th and 17th-20th step groups), and effective vertical mean force (9th-12th step group) were found in the caffeine condition. For the block clearance phase at the sprint start, push-off and reaction times did not change, while higher total anteroposterior mean force, average horizontal external power, and ratio of force were found in the caffeine condition. These results indicate that, compared with placebo, acute caffeine supplementation improved sprint performance regardless of sprint sections during the entire acceleration phase from the start through increases in step frequency with decreases in support time. Moreover, acute caffeine supplementation promoted increases in the propulsive mean force, resulting in the improvement of sprint performance.

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BACKGROUND: Walking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. OBJECTIVES: We used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: (1) identify clusters of walking behaviors in people post-stroke and neurotypical controls and (2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants. METHODS: We gathered data from 81 post-stroke participants across 4 research sites and collected data from 31 control participants. Using sparse K-means clustering, we identified walking clusters based on 17 spatiotemporal and force variables. We analyzed the biomechanical features within each cluster to characterize cluster-specific walking behaviors. We also assessed the generalizability of the clusters using a leave-one-out approach. RESULTS: We identified 4 stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. CONCLUSIONS: Although post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.

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Background: Walking patterns in stroke survivors are highly heterogeneous, which poses a challenge in systematizing treatment prescriptions for walking rehabilitation interventions. Objective: We used bilateral spatiotemporal and force data during walking to create a multi-site research sample to: 1) identify clusters of walking behaviors in people post-stroke and neurotypical controls, and 2) determine the generalizability of these walking clusters across different research sites. We hypothesized that participants post-stroke will have different walking impairments resulting in different clusters of walking behaviors, which are also different from control participants. Methods: We gathered data from 81 post-stroke participants across four research sites and collected data from 31 control participants. Using sparse K-means clustering, we identified walking clusters based on 17 spatiotemporal and force variables. We analyzed the biomechanical features within each cluster to characterize cluster-specific walking behaviors. We also assessed the generalizability of the clusters using a leave-one-out approach. Results: We identified four stroke clusters: a fast and asymmetric cluster, a moderate speed and asymmetric cluster, a slow cluster with frontal plane force asymmetries, and a slow and symmetric cluster. We also identified a moderate speed and symmetric gait cluster composed of controls and participants post-stroke. The moderate speed and asymmetric stroke cluster did not generalize across sites. Conclusions: Although post-stroke walking patterns are heterogenous, these patterns can be systematically classified into distinct clusters based on spatiotemporal and force data. Future interventions could target the key features that characterize each cluster to increase the efficacy of interventions to improve mobility in people post-stroke.

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This study investigated the accuracy of the Insole3 wireless shoe device in estimating several clinically useful spatiotemporal parameters (STPs). Eleven subjects walked at slow (0.8-1.0 m/s) and moderate-paced (1.2-1.4 m/s) speeds. Data were simultaneously recorded using the Insole3 and an industry-standard, three-dimensional motion capture (MOCAP) system. An error analysis compared the resulting STP data from the two systems. The mean bias error (MBE) was generally lower for temporal variables, and somewhat higher, but acceptable, for spatial variables. The MBE for temporally-related cadence and cycle time were the lowest (less than ±0.45%), with 100% (110/110) of slow-paced walking trial values and 99.1% (109/110) of moderate-paced walking trial values within 5% of the MOCAP estimates. The MBE was highest for speed (3.23-4.91%) and stride length (3.68-4.63%), with between 52.7 and 69.1% of trial values falling within the 5% error range. Stance time and swing time ranged between -0.98 and 4.38% error for both walking conditions. The results of this study suggest that the Insole3 is a potential alternative to MOCAP for estimating several STPs, namely cadence, stance time, and cycle time, particularly for use outside of the laboratory setting.

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PURPOSE: Submaximal sprinting allows for larger accumulated work to be reached before the onset of fatigue, compared with maximal efforts. The aim of this study was to investigate the effect of sprint running at 90% to 95% of maximal velocity (Vmax) on sprint performance. METHODS: Recreationally active adults were randomly assigned into a control group (n = 12, 27 [5] y, 172 [9] cm, 72 [15] kg) and a training group (n = 14, 26 [4] y, 171 [9] cm, 69 [11] kg). Both groups completed pretesting and posttesting in form of a 30-m sprint separated by a 6-week period. The training group performed a weekly sprint-training session consisting of 30-m flying sprints at 90% to 95% of Vmax, while the control group performed no intervention training. RESULTS: Significant improvements in the training group were observed for 10- (P = .003), 20- (P = .001), and 30-m sprint time (P = .002). These improvements were accompanied by higher step rate (P = .006) and theoretical Vmax (P = .007) and maximal power (P = .004). Significant between-groups differences were observed for 10- (P = .008), 20- (P < .001), and 30-m sprint time (P < .001), as well as for step rate (P = .015), theoretical Vmax (P = .016), and maximal power (P = .008). All within- and between-groups differences were in the range of trivial to small. CONCLUSION: Sprint running at 90% to 95% of Vmax can enhance 10- to 30-m sprint performance in recreationally active adults.

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The primary purpose of this study was to compare biomechanical gait variables and perceived gait velocity between overground and treadmill walking conditions among typically developing children and adolescents. Twenty children and adolescents (Mage = 11.4, SD = 2.9 years) walked overground and on a treadmill at a matched comfortable walking speed while a 3-D motion analysis system captured spatiotemporal and kinematic gait parameters. In order to compare perceived gait velocities, we acquired data at self-selected comfortable and fastest walking speeds. Paired t-tests comparing the children's speed and gait in these two different walking conditions revealed significantly higher cadence (p < .001) and shorter stride length (p < .002), during treadmill versus overground walking. In addition, treadmill walking showed statistically significant differences in joint kinematics of ankle excursion and pelvic rotation excursions (p < .001). Participants chose slower speeds on the treadmill than for overground walking when they were asked to select their comfortable and fastest walking speeds (p < .001). Our findings suggest that these differences between treadmill and overground walking in cadence, stride length, and perceived gait velocity should be considered whenever a treadmill is used for gait research within the pediatric population. However, the differences we found in gait kinematics between these two walking conditions appear to be relatively trivial and fell within the common error range of kinematic analysis.

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This study elucidated spatiotemporal and ground reaction force determinants of running speed and acceleration for female sprinters during the entire sprinting. Fifteen female sprinters completed 60 m sprints. Kinematic and kinetic variables were measured using force platforms over a 50 m distance from the start. Results demonstrated that higher step frequency (11th-27th steps, r = 0.517-0.717) through shorter support time (12th-27th steps, r = -0.535 to -0.634) could be determinants of running speed. Moreover, increasing step length (1st-10th steps, r = 0.550-0.938), suppressing increases in step frequency (2nd-7th steps, r = -0.639 to -0.870), suppressing decreases in support time (1st-5th steps, r = 0.599-0.709) and increases in flight time (4th-7th steps, r = 0.523-0.649) can be essential for greater running acceleration. Propulsive mean force (1st-5th steps, r = 0.663-0.876) and anteroposterior net mean force (all steps, r = 0.697-0.894) are likely determinants of greater running acceleration. At the maximal speed phase there was no correlation between running speed and the other variables. Differences with previously found male sprint determinants suggest that training targets specific to female sprinters are necessary for improving training designs and race strategy.

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OBJECTIVE: This study aims to investigate the impact of obstacle collision according to the presence or absence of light and the change of gait when using smartphones while walking. STUDY DESIGN/SETTING: A cross-sectional study. SUBJECTS: 24 healthy young people. METHODS: Obstacle collision was measured in participants as they passed through four obstacles at different heights (eyes, waist, knees, ankle level), with the lights turned on. The same was measured with the lights turned off. To measure spatiotemporal variables, GAITRite was used. Obstacle collision was used in the frequency analysis, and the spatiotemporal variables were assessed using one-way ANOVA test. The post-hoc Tukey's test was used to detect spatiotemporal variables differences (p < 0.05). RESULTS: Obstacle collision was the highest at eye level when playing games and messaging while walking. It was also higher when lights were turned off rather than when lights were on. Gait function decreased while walking when messaging or playing games on a smartphone as compared to when walking without a smartphone. CONCLUSION: Understanding the collision rate of various obstacles encountered when using smartphones while walking could contribute to the prevention of accidents.

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Differences in gait with age or knee osteoarthritis have been demonstrated in laboratory studies using optical motion capture (MoCap). While MoCap is accurate and reliable, it is impractical for assessment outside the laboratory. Inertial measurement units (IMUs) may be useful in these situations. Before IMUs are used as a surrogate for MoCap, methods that are reliable, repeatable, and that calculate metrics at similar accuracy to MoCap must be demonstrated. The purpose of this study was to compare spatiotemporal gait parameters and knee range of motion calculated via MoCap to IMU-derived variables and to compare the ability of these tools to discriminate between groups. MoCap and IMU data were collected from young, older, and adults with knee osteoarthritis during overground walking at three self-selected speeds. Walking velocity, stride length, cadence, percent of gait cycle in stance, and sagittal knee range of motion were calculated and compared between tools (MoCap and IMU), between participant groups, and across speed. There were no significant differences between MoCap and IMU outcomes, and root mean square error between tools was ≤0.05 m/s for walking velocity, ≤0.07 m for stride length, ≤0.5 strides/min for cadence, ≤5% for percent of gait cycle in stance, and ≤1.5° for knee range of motion. No interactions were present, suggesting that MoCap and IMU calculated metrics similarly across groups and speeds. These results demonstrate IMUs can accurately calculate spatiotemporal variables and knee range of motion during gait in young and older, asymptomatic and knee osteoarthritis cohorts.

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The aim of this study was to analyze changes in gait variability and symmetry in distance runners. Fourteen competitive athletes ran on an instrumented treadmill for 10,000 m at speeds equivalent to 103% of their season's best time. Spatiotemporal and ground reaction force data were recorded at 1500, 3000, 5000, 7500 and 9500 m. Gait variability and inter-leg symmetry were measured using median absolute deviation (MAD) and the symmetry angle, respectively. There were no overall changes during the running bout for absolute values, symmetry angles or variability, and there were only moderate changes in variability between successive testing distances for three variables. Even with these few changes, variability was low (<4%) at all distances for all variables measured and, on average, the athletes were symmetrical for five of the seven gait variables measured. There were greater mean asymmetry values for flight time (1.1-1.4%) and for impact force (2.0-2.9%), which might have occurred because of muscle latency as the lower limb responded passively to impact during initial contact. Although most athletes were asymmetrical (>1.2%) for at least one variable, no one was asymmetrical for more than four of the seven variables measured. Being asymmetrical in a few variables is therefore not abnormal and not indicative of asymmetrical gait and given many practitioners analyze symmetry (and variability) on an individual, case-study basis, caution should be taken when assessing the need for corrective interventions.

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The aims of this study were to (a) quantify the magnitude of kinematic stride cycle asymmetry in high-level athletic sprinters, (b) explore the association between kinematic asymmetry and maximal sprint running performance, and (c) investigate possible associations between kinematic asymmetry and injury prevalence. Twenty-two competitive sprinters (age 23 ± 3 year, height 1.81 ± 0.06 m, body mass 75.5 ± 5.6 kg, personal best 100 m 10.86 ± 0.22 seconds) performed 2-3 flying sprints over 20 m. Kinematics were recorded in 3D using a motion tracking system with 21 cameras at a 250 Hz sampling rate, allowing assessment of six consecutive steps for each athlete. Information about injuries sustained 1 year prior to and after the experiment was continuously registered (type, location, severity/duration, and time of year occurrence). The results showed that ≥11 of the 22 participating athletes displayed large or very large asymmetry for at least 11 of 14 variables, and all athletes displayed large or very large asymmetry for at least three variables. No correlations between individual magnitudes of asymmetry and sprint performance were significant (trivial to moderate). No significant changes in asymmetry between best and worst trial were observed for any of the analyzed variables. In addition, injured and non-injured athletes did not differ in asymmetry, neither for the time period 1 year prior to nor after the test. In conclusion, kinematic asymmetries in the stride cycle were not associated with neither maximal sprint running performance nor the prevalence of injury among high-level athletic sprinters.

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This study investigated the fractal dynamic properties of stride time (ST), stride length (SL) and stride speed (SS) during walking on a self-paced treadmill (STM) in which the belt speed is automatically controlled by the walking speed. Twelve healthy young subjects participated in the study. The subjects walked at their preferred walking speed under four conditions: STM, STM with a metronome (STM+met), fixed-speed (conventional) treadmill (FTM), and FTM with a metronome (FTM+met). To compare the fractal dynamics between conditions, the mean, variability, and fractal dynamics of ST, SL, and SS were compared. Moreover, the relationship among the variables was examined under each walking condition using three types of surrogates. The mean values of all variables did not differ between the two treadmills, and the variability of all variables was generally larger for STM than for FTM. The use of a metronome resulted in a decrease in variability in ST and SS for all conditions. The fractal dynamic characteristics of SS were maintained with STM, in contrast to FTM, and only the fractal dynamic characteristics of ST disappeared when using a metronome. In addition, the fractal dynamic patterns of the cross-correlated surrogate results were identical to those of all variables for the two treadmills. In terms of the fractal dynamic properties, STM walking was generally closer to overground walking than FTM walking. Although further research is needed, the present results will be useful in research on gait fractal dynamics and rehabilitation.

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The aim of this study was to analyse gait variability and symmetry in race walkers. Eighteen senior and 17 junior athletes race walked on an instrumented treadmill (for 10 km and 5 km, respectively) at speeds equivalent to 103% of season's best time for 20 km and 10 km, respectively. Spatio-temporal and ground reaction force (GRF) data were recorded at 2.5 km, and at 4.5, 6.5 and 8.5 km for a subsection of athletes. Gait variability was measured using median absolute deviation (MAD) whereas inter-leg symmetry was measured using the symmetry angle. Both groups showed low variability for step length (<0.9%), step frequency (<1.1%), contact time (≤1.2%) and vertical peak force values (<5%), and neither variability nor symmetry changed with distance walked. Junior athletes were more variable for both step length (P = 0.004) and loading force (P = 0.003); no differences for gait symmetry were found. Whereas there was little mean asymmetry overall, individual analyses identified asymmetry in several athletes (symmetry angle ≥ 1.2%). Importantly, asymmetrical step lengths were found in 12 athletes and could result from underlying imbalances. Coaches are advised to observe athletes on an individual basis to monitor for both variability and asymmetry.

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BACKGROUND: Patients with Parkinson disease (PD) experience problems such as falls and freezing of gait during walking and turning in daily activities. However, few studies have examined the relationship between simultaneous turning tasks and the severity of PD. AIM: To investigate turning characteristics in patients with PD using three-dimensional (3D) analysis during the timed up and go (TUG) test. METHODS: Thirty individuals performed the TUG test under 3D motion analysis: 10 patients with Hoehn and Yahr (H&Y) stages 2.5 and 3.0 PD (group I), 10 patients with H&Y stage 2.0 PD (group II), and 10 healthy older adult controls. Spatiotemporal and kinematic variables were analyzed during the TUG test with a Vicon 3-D motion analysis system. RESULTS: The walking speed, step length, step length asymmetry index, range of motion of the hip, knee, and shoulder joints, and foot clearance height significantly differed between patients with PD and the controls. The step length and foot clearance height were significantly different between groups I and II. DISCUSSION: The step length and foot clearance are different between the severity levels of PD, and the TUG test may be useful for identifying turning characteristics in patients with PD. CONCLUSIONS: Patients with PD exhibited significant differences in all variables of interest compared to the controls. The step length and foot clearance height as well as the TUG test during the turning phase may be helpful for measuring turning in patients with different severity levels of PD.

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[Purpose] This study attempted to examine the impact on the pattern of walking on both level ground and stairs after restricting the movement of the spine and the trunk of the body by using a spinal orthosis. [Subjects and Methods] Forty healthy males in their 20s were selected as the sample, which was randomly and evenly divided into two groups: (1) the WT group (with a thoracolumbosacral orthosis group) and (2) the WOT group (Without a thoracolumbosacral orthosis group). The spinal orthosis used in this study was a thoracolumbosacral orthosis called a plastic body jacket. [Results] In walking on level ground, step width showed a significant difference, but no statistically significant difference was found between the WT group and the WOT group with respect to the other variables. In walking on stairs, the double stance phase showed a statistically significant difference during stair descent in the WT group compared with the WOT group. [Conclusion] It was proven that wearing a TLSO increased walking stability in the case of walking on level ground and stairs. Hence, it is believed that proper use of a spinal orthosis can play an ancillary role in daily life and therapeutic interventions.