ArticlePloS one2019
Effect of sampling frequency on fractal fluctuations during treadmill walking.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Gait assessment using a 2D video-based motion analysis app in healthy subjects and subjects with lower limb amputation - A pilot study.PloS one · 2025Article
- Comparison of Mean Values and Entropy in Accelerometry Time Series from Two Microtechnology Sensors Recorded at 100 vs. 1000 Hz During Cumulative Tackles in Young Elite Rugby League Players.Sensors (Basel, Switzerland) · 2024Article
- Females Present Reduced Minimum Toe Clearance During Walking As Compared to Males in Active Older Adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2024Article
- The Agreement between Wearable Sensors and Force Plates for the Analysis of Stride Time Variability.Sensors (Basel, Switzerland) · 2024Article
- Simplified Markerless Stride Detection Pipeline (sMaSDP) for Surface EMG Segmentation.Sensors (Basel, Switzerland) · 2023Article
- Differences between Systems Using Optical and Capacitive Sensors in Treadmill-Based Spatiotemporal Analysis of Level and Sloping Gait.Sensors (Basel, Switzerland) · 2022Article
- Measuring Spatiotemporal Parameters on Treadmill Walking Using Wearable Inertial System.Sensors (Basel, Switzerland) · 2021Article
- Fractal auditory stimulation has greater benefit for people with Parkinson's disease showing more random gait pattern.Gait & posture · 2020Article
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Authors and funding
3 authors.
Funding
Abstract
The temporal dynamics of stride-to-stride fluctuations in steady-state walking reveal important information about locomotor control and can be quantified using so-called fractal analyses, notably the detrended fluctuation analysis (DFA). Gait dynamics are often collected during treadmill walking using 3-D motion capture to identify gait events from kinematic data. The sampling frequency of motion capture systems may impact the precision of event detection and consequently impact the quantification of stride-to-stride variability. This study aimed i) to determine if collecting multiple walking trials with different sampling frequency affects DFA values of spatiotemporal parameters during treadmill walking, and ii) to determine the reliability of DFA values across downsampled conditions. Seventeen healthy young adults walked on a treadmill while their gait dynamics was captured using different sampling frequency (60, 120 and 240 Hz) in each condition. We also compared data from the highest sampling frequency to downsampled versions of itself. We applied DFA to the following time series: step length, time and speed, and stride length, time and speed. Reliability between experimental conditions and between downsampled conditions were measured with 1) intraclass correlation estimates and their 95% confident intervals, calculated based on a single-measurement, absolute-agreement, two-way mixed-effects model (ICC 3,1), and 2) Bland-Altman bias and limits of agreement. Both analyses revealed a poor reliability of DFA results between conditions using different sampling frequencies, but a relatively good reliability between original and downsampled spatiotemporal variables. Collectively, our results suggest that using sampling frequencies of 120 Hz or 240 Hz provide similar results, but that using 60 Hz may alter DFA values. We recommend that gait kinematics should be collected at around 120 Hz, which provides a compromise between event detection accuracy and processing time.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.