Evidence map›Paper›PMID 30629508›Full record

ArticleIEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society2019

Feasibility of Incorporating Test-Retest Reliability and Model Diversity in Identification of Key Neuromuscular Pathways During Head Position Tracking.

Ahmed Ramadan, Jongeun Choi, Jacek Cholewicki, N Peter Reeves, John M Popovich, Clark J Radcliffe

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Article in IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Ahmed Ramadan
Jongeun Choi
Jacek Cholewicki
N Peter Reeves
John M Popovich
Clark J Radcliffe

Funding

Systems Science Center for Musculoskeletal CAM TherapiesU19AT006057 · NCCIH · MICHIGAN STATE UNIVERSITY · PI CHOLEWICKI, JACEK, REEVES, NORMAN PETER · 2010 to 2016
$4.6M
NCCIH NIH HHS U19 AT006057
6 · The paper itself

Abstract

To study the complex neuromuscular control pathways in human movement, biomechanical parametric models and system identification methods are employed. Although test-retest reliability is widely used to validate the outcomes of motor control tasks, it was not incorporated in system identification methods. This study investigates the feasibility of incorporating test-retest reliability in our previously published method of selecting sensitive parameters. We consider the selected parameters via this novel approach to be the key neuromuscular parameters, because they meet three criteria: reduced variability, improved goodness of fit, and excellent reliability. These criteria ensure that the parameter variability is below a user-defined value, the number of these parameters is maximized to enhance goodness of fit, and their test-retest reliability is above a user-defined value. We measured variability, the goodness of fit, and reliability using Fisher information matrix, variance accounted for, and intraclass correlation, respectively. We also incorporated model diversity as a fourth optional criterion to narrow down the solution space of key parameters. We applied this approach to the head position tracking tasks in axial rotation and flexion/extension. A total of forty healthy subjects performed the tasks during two visits. With variability and reliability measures ≤0.35 and ≥0.75, respectively, we selected three key parameters out of twelve with the goodness of fit >69%. The key parameters were associated with at least two neuromuscular pathways out of four modeled pathways (visual, proprioceptive, vestibular, and intrinsic), which is a measure of model diversity. Therefore, it is feasible to incorporate reliability and diversity in system identification of key neuromuscular pathways in our application.

Indexed as

Models, NeurologicalAdultAlgorithmsBiomechanical PhenomenaFeasibility StudiesFemaleHead MovementsHealthy VolunteersHumansMaleMiddle AgedNeural PathwaysNeuromuscular MonitoringProprioceptionReproducibility of ResultsVestibule, Labyrinth

Identifiers

PMID30629508
PMCPMC6414318

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