ArticlePloS one2019
Direct estimation of the parameters of a delayed, intermittent activation feedback model of postural sway during quiet standing.
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 9 papers.
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Who cites it
9 citing papers in PubMed.
- Estimating continuous and intermittent feedback models of postural control using the least squares method.Biological cybernetics · 2025Article
- How the brain can be trained to achieve an intermittent control strategy for stabilizing quiet stance by means of reinforcement learning.Biological cybernetics · 2024Article
- Time-delay estimation in biomechanical stability: a scoping review.Frontiers in human neuroscience · 2024Article
- Sensorimotor Time Delay Estimation by EMG Signal Processing in People Living with Spinal Cord Injury.Sensors (Basel, Switzerland) · 2023Article
- Article
- A review of center of pressure (COP) variables to quantify standing balance in elderly people: Algorithms and open-access code.Physiological reports · 2021Review
- Response to perturbation during quiet standing resembles delayed state feedback optimized for performance and robustness.Scientific reports · 2021Article
- Dynamic Systems, Contextual Influences, and Multiple Timescales: Emotion Regulation as a Resilience Resource.The Gerontologist · 2021Article
- Rolling balance board of adjustable geometry as a tool to assess balancing skill and to estimate reaction time delay.Journal of the Royal Society, Interface · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
Human postural sway during quiet standing has been characterized as a proportional-integral-derivative controller with intermittent activation. In the model, patterns of sway result from both instantaneous, passive, mechanical resistance and delayed, intermittent resistance signaled by the central nervous system. A Kalman-Filter framework was designed to directly estimate from experimental data the parameters of the model's stochastic delay differential equations with discrete dynamic switching conditions. Simulations showed that all parameters could be estimated over a variety of possible data-generating configurations with varying degrees of bias and variance depending on their empirical identification. Applications to experimental data reveal distributions of each parameter that correspond well to previous findings, suggesting that many useful, physiological measures may be extracted from sway data. Individuals varied in degree and type of deviation from theoretical expectations, ranging from harmonic oscillation to non-equilibrium Langevin dynamics.
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Registered trials
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