ArticleGait & posture2018
Effect of parameter selection on entropy calculation for long walking trials.
Article in Gait & posture, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Sampling frequency influences sample entropy of kinematics during walking.Medical & biological engineering & computing · 2019Trial
- The effect of muscle oxygenation on neuromuscular efficiency and force complexity.European journal of applied physiology · 2026Article
- NONAN GaitPrint: An IMU gait database of healthy middle-aged adults.Scientific data · 2025Article
- Article
- Effect of Task Constraints on Neurobiological Systems Involved in Postural Control in Individuals with and without Chronic Ankle Instability.Bioengineering (Basel, Switzerland) · 2024Article
- Individuals With Multiple Sclerosis Exhibit More Regular Center of Mass Accelerations After Physical Therapy.Archives of rehabilitation research and clinical translation · 2024Article
- Visual feedback influences the consistency of the locomotor pattern in Asian elephants (Biology letters · 2023Article
- Multiscale Entropy Algorithms to Analyze Complexity and Variability of Trunk Accelerations Time Series in Subjects with Parkinson's Disease.Sensors (Basel, Switzerland) · 2023Article
- The Fidget Factor and the obesity paradox. How small movements have big impact.Frontiers in sports and active living · 2023Article
- Calculating sample entropy from isometric torque signals: methodological considerations and recommendations.Frontiers in physiology · 2023Article
- The influence of walking speed and effects of signal processing methods on the level of human gait regularity during treadmill walking.BMC sports science, medicine & rehabilitation · 2022Article
- Sample Entropy as a Tool to Assess Lumbo-Pelvic Movements in a Clinical Test for Low-Back-Pain Patients.Entropy (Basel, Switzerland) · 2022Article
- Gait analysis under the lens of statistical physics.Computational and structural biotechnology journal · 2022Review
- Sampling rate influences the regularity analysis of temporal domain measures of walking more than spatial domain measures.Gait & posture · 2021Article
- Entropy Analysis in Gait Research: Methodological Considerations and Recommendations.Annals of biomedical engineering · 2021Review
- Cognitive Loading Produces Similar Change in Postural Stability in Patients With Chronic Ankle Instability and Controls.Athletic training & sports health care · 2020Article
- On the application of entropic half-life and statistical persistence decay for quantification of time dependency in human gait.Journal of biomechanics · 2020Article
- Relative Consistency of Sample Entropy Is Not Preserved in MIX Processes.Entropy (Basel, Switzerland) · 2020Article
- Entropy of Real-World Gait in Parkinson's Disease Determined from Wearable Sensors as a Digital Marker of Altered Ambulatory Behavior.Sensors (Basel, Switzerland) · 2020Article
- Bimanual load carriage alters sway patterns and step width.Applied ergonomics · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
It is sometimes difficult to obtain uninterrupted data sets that are long enough to perform nonlinear analysis, especially in pathological populations. It is currently unclear as to how many data points are needed for reliable entropy analysis. The aims of this study were to determine the effect of changing parameter values of m, r, and N on entropy calculations for long gait data sets using two different modes of walking (i.e., overground versus treadmill). Fourteen young adults walked overground and on a treadmill at their preferred walking speed for one-hour while step time was collected via heel switches. Approximate (ApEn) and sample entropy (SampEn) were calculated using multiple parameter combinations of m, N, and r. Further, r was tested under two cases r*standard deviation and r constant. ApEn differed depending on the combination of r, m, and N. ApEn demonstrated relative consistency except when m=2 and the smallest r values used (rSD=0.015*SD, 0.20*SD; rConstant=0 and 0.003). For SampEn, as r increased, SampEn decreased. When r was constant, SampEn demonstrated excellent relative consistency for all combinations of r, m, and N. When r constant was used, overground walking was more regular than treadmill. However, treadmill walking was found to be more regular when using rSD for both ApEn and SampEn. For greatest relative consistency of step time data, it was best to use a constant r value and SampEn. When using entropy, several r values must be examined and reported to ensure that results are not an artifact of parameter choice.
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Registered trials
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