1,737,268 research outputs found
Persistent fluctuations in stride intervals under fractal auditory stimulation
No full textCopyright @ 2014 Marmelat et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Stride sequences of healthy gait are characterized by persistent long-range correlations, which become anti-persistent in the presence of an isochronous metronome. The latter phenomenon is of particular interest because auditory cueing is generally considered to reduce stride variability and may hence be beneficial for stabilizing gait. Complex systems tend to match their correlation structure when synchronizing. In gait training, can one capitalize on this tendency by using a fractal metronome rather than an isochronous one? We examined whether auditory cues with fractal variations in inter-beat intervals yield similar fractal inter-stride interval variability as isochronous auditory cueing in two complementary experiments. In Experiment 1, participants walked on a treadmill while being paced by either an isochronous or a fractal metronome with different variation strengths between beats in order to test whether participants managed to synchronize with a fractal metronome and to determine the necessary amount of variability for participants to switch from anti-persistent to persistent inter-stride intervals. Participants did synchronize with the metronome despite its fractal randomness. The corresponding coefficient of variation of inter-beat intervals was fixed in Experiment 2, in which participants walked on a treadmill while being paced by non-isochronous metronomes with different scaling exponents. As expected, inter-stride intervals showed persistent correlations similar to self-paced walking only when cueing contained persistent correlations. Our results open up a new window to optimize rhythmic auditory cueing for gait stabilization by integrating fractal fluctuations in the inter-beat intervals.Commission of the European Community and the Netherlands Organisation for Scientific Research
Stride-to-stride fluctuations in transtibial amputees are not affected by changes in push-off mechanics from using different prostheses - Fig 4
No full textChanges in prosthesis push-off work did not correlate with stride-to-stride fluctuation changes within individuals at the sound ankle (a, R2 = 0.134, n = 22, p = 0.0903) or the prosthetic ankle (b, R2 = 0.0417, n = 22, p = 0.362). As stride-to-stride fluctuations result from the interaction of various systems including neural, mechanical, and (in this case) synthetic, we expected that changes to the prosthesis mechanics would result in changes in the stride-to-stride fluctuations. The lack of relation indicates that the mechanical contribution of the limb to stride-to-stride fluctuations may not be a significant contributor. (Δ = High Activity prosthesis value–Low Activity prosthesis value).</p
STRIDE Project H6 Datasets - I-95 Miami
No full text<p>STRIDE Project H6 Datasets - I-95 Miami</p>
CHANGES IN RUNNING GAIT PARAMETERS DURING A 161 KM TRAIL RACE
No full textThe current study examined changes in running speed and technique during a 161 km trail race and their relationship to performance. Sixteen participants were video recorded during continuous running for each of the five 32 km loops of the race. Participant's stride length (SL), stride rate (SR), and speed were calculated. Lap and finish times were also collated from the race results. All variables changed significantly during the race (i.e. Speed↓, Lap time↑, SL↓ and SR↓). Increased consistency in stride rate and length across the five laps, as well as speed, correlated positively with performance. Increased stride length in laps one, two and four correlated positively with performance. Results indicated that fatigue during the race decreased both speed and SL. Better performers ran faster with a longer SL and were able to maintain their initial speed for longer
STRIDE Project J2 Datasets - 119th St & Newberry Rd
No full text<p>STRIDE Project J2 Datasets - 119th St & Newberry Rd</p>
Subject-specific values for stride-to-stride fluctuations (bit/s) and push-off work (J/kg).
No full textIndividual values for each leg (prosthesis side or sound side) and each condition (High Activity or Low Activity prosthesis) are reported. For stride-to-stride fluctuations, values were calculated at the ankle, knee, and hip. (XLSX)</p
STRIDE Project - Enabling the Shared Mobility Revolution - dataset
No full textThis folder contains all the relevant data used (input and output) in the context of the STRIDE Project "Enabling the Shared Mobility Revolution" for the microscopic simulation analysis of curb environments
Stride rate and walking intensity in healthy older adults
No full textPurpose: The study investigated a) walking intensity (stride rate and energy expenditure) under three speed instructions, b) associations between stride rate, age, height and walking intensity, and c) synchronization between stride rate and music tempo during overground walking in a population of healthy older adults. Methods: Twenty-nine participants completed three treadmill walking trials and three overground walking trials at three self-selected speeds. Treadmill ̇O2 was measured using indirect calorimetry. Stride rate and music tempo were recorded during overground walking trials. Results: Mean stride rate exceeded minimum thresholds for moderate-to-vigorous physical activity (MVPA) under slow (111.41 ± 11.93), medium (118.17 ± 11.43) and fast (123.79 ± 11.61) instructions.. A multilevel model showed that stride rate, age and height have a significant effect (p < 0.01) on walking intensity. Conclusions: Healthy older adults achieve MVPA with stride rates that fall below published minima for MVPA. Stride rate, age and height are significant predictors of energy expenditure in this population. Music can be a useful way to guide walking cadence
Contrast agent uncertainty analysis
No full textThe files contain the Matlab code used to generate the data described in the paper Harfield et al. Analysis of the Uncertainty in Microbubble Characterisation. Ultrasound in Medicine and Biology 2016. The spreadsheet used to prepare the plots shown in the manuscript is also included
Raw data for siRNA loaded nanodroplets
No full textThese data relate to the formulation of magnetic and ultrasound responsive nanodroplets described in the publication by Lee et al. 10.1002/adhm.20160124
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