ArticleJournal of the Royal Society, Interface2020
Effect of data length on time delay and embedding dimension for calculating the Lyapunov exponent in walking.
Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Multiple Sclerosis Classification Using the Local Divergence Exponent: Parameters Selection for State-Space Reconstruction.Sensors (Basel, Switzerland) · 2025Article
- A Comprehensive Understanding of Postural Tone Biomechanics: Intrinsic Stiffness, Functional Stiffness, Antagonist Coactivation, and COP Dynamics in Post-Stroke Adults.Sensors (Basel, Switzerland) · 2025Article
- Utilizing Inertial Measurement Units for Detecting Dynamic Stability Variations in a Multi-Condition Gait Experiment.Sensors (Basel, Switzerland) · 2024Article
- Effects of the kinematic variable, time delay and data length on test-retest reliability of the maximal Lyapunov exponent of human walking.Royal Society open science · 2024Article
- Uncovering Subtle Gait Deterioration in People with Early-Stage Multiple Sclerosis Using Inertial Sensors: A 2-Year Multicenter Longitudinal Study.Sensors (Basel, Switzerland) · 2023Article
- Joint Angle Variability Is Altered in Patients with Peripheral Artery Disease after Six Months of Exercise Intervention.Entropy (Basel, Switzerland) · 2022Article
- Cardio-Hypothalamic-Pituitary Coupling during Rest and in Response to Exercise.Entropy (Basel, Switzerland) · 2022Article
- Complexity of locomotion activities in an outside-of-the-lab wearable motion capture dataset.Frontiers in bioengineering and biotechnology · 2022Article
- Gait analysis under the lens of statistical physics.Computational and structural biotechnology journal · 2022Review
- Prediction of fall risk among community-dwelling older adults using a wearable system.Scientific reports · 2021Article
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3 authors.
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Abstract
The Lyapunov exponent (LyE) is a trending measure for characterizing gait stability. Previous studies have shown that data length has an effect on the resultant LyE, but the origin of why it changes is unknown. This study investigates if data length affects the choice of time delay and embedding dimension when reconstructing the phase space, which is a requirement for calculating the LyE. The effect of three different preprocessing methods on reconstructing the gait attractor was also investigated. Lumbar accelerometer data were collected from 10 healthy subjects walking on a treadmill at their preferred walking speed for 30 min. Our results show that time delay was not sensitive to the amount of data used during calculation. However, the embedding dimension had a minimum data requirement of 200 or 300 gait cycles, depending on the preprocessing method used, to determine the steady-state value of the embedding dimension. This study also found that preprocessing the data using a fixed number of strides or a fixed number of data points had significantly different values for time delay compared to a time series that used a fixed number of normalized gait cycles, which have a fixed number of data points per stride. Thus, comparing LyE values should match the method of calculation using either a fixed number of strides or a fixed number of data points.
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