ArticleIEEE transactions on bio-medical engineering2012
System identification of physiological systems using short data segments.
Article in IEEE transactions on bio-medical engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The Simultaneous Model-Based Estimation of Joint, Muscle, and Tendon Stiffness is Highly Sensitive to the Tendon Force-Strain Relationship.IEEE transactions on bio-medical engineering · 2024Article
- Leveraging Joint Mechanics Simplifies the Neural Control of Movement.Frontiers in integrative neuroscience · 2022Article
- Frontal plane ankle stiffness increases with weight-bearing.Journal of biomechanics · 2021Article
- On predictions in critical care: The individual prognostication fallacy in elderly patients.Journal of critical care · 2021Article
- Estimating Human Wrist Stiffness during a Tooling Task.Sensors (Basel, Switzerland) · 2020Article
- On neuromechanical approaches for the study of biological and robotic grasp and manipulation.Journal of neuroengineering and rehabilitation · 2017Review
- Mechanisms contributing to reduced knee stiffness during movement.Experimental brain research · 2017Article
- Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions.Frontiers in computational neuroscience · 2017Article
- Robot-aided assessment of lower extremity functions: a review.Journal of neuroengineering and rehabilitation · 2016Review
- Using a System Identification Approach to Investigate Subtask Control during Human Locomotion.Frontiers in computational neuroscience · 2016Article
- Modeling and simulating the neuromuscular mechanisms regulating ankle and knee joint stiffness during human locomotion.Journal of neurophysiology · 2015Article
- The dynamic effect of muscle activation on knee stiffness.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2014Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
System identification of physiological systems poses unique challenges, especially when the structure of the system under study is uncertain. Nonparametric techniques can be useful for identifying system structure, but these typically assume stationarity and require large amounts of data. Both of these requirements are often not easily obtained in the study of physiological systems. Ensemble methods for time-varying nonparametric estimation have been developed to address the issue of stationarity, but these require an amount of data that can be prohibitive for many experimental systems. To address this issue, we developed a novel algorithm that uses multiple short data segments. Using simulation studies, we showed that this algorithm produces system estimates with lower variability than previous methods when limited data are present. Furthermore, we showed that the new algorithm generates time-varying system estimates with lower total error than an ensemble method. Thus, this algorithm is well suited for the identification of physiological systems that vary with time or from which only short segments of stationary data can be collected.
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Registered trials
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.