Publication Detail
The publication detail shows the title, authors (with indicators showing other profiled authors), information on the publishing organization, abstract and a link to the article in PubMed. This abstract is what is used to create the fingerprint of the publication. If any grants are referenced by the publication, they will be listed here as well.
Identification of the plant for upright stance in humans: multiple movement patterns from a single neural strategy.
Tim Kiemel; Alexander J Elahi; John J Jeka (Profiled Author: John J. Jeka)
Department of Kinesiology, University of Maryland, College Park, MD 20742, USA. kiemel@umd.edu
Journal of neurophysiology 2008;100(6):3394-406.
We determined properties of the plant during human upright stance using a closed-loop system identification method originally applied to human postural control by another group. To identify the plant, which was operationally defined as the mapping from muscle activation (rectified EMG signals) to body segment angles, we rotated the visual scene about the axis through the subject's ankles using a sum-of-sines stimulus signal. Because EMG signals from ankle muscles and from hip and lower trunk muscles showed similar responses to the visual perturbation across frequency, we combined EMG signals from all recorded muscles into a single plant input. Body kinematics were described by the trunk and leg angles in the sagittal plane. The phase responses of both angles to visual scene angle were similar at low frequencies and approached a difference of approximately 150 degrees at higher frequencies. Therefore we considered leg and trunk angles as separate plant outputs. We modeled the plant with a two-joint (ankle and hip) model of the body, a second-order low-pass filter from EMG activity to active joint torques, and intrinsic stiffness and damping at both joints. The results indicated that the in-phase (ankle) pattern was neurally generated, whereas the out-of-phase pattern was caused by plant dynamics. Thus a single neural strategy leads to multiple kinematic patterns. Moreover, estimated intrinsic stiffness in the model was insufficient to stabilize the plant.
4 Originating Grant
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1.
Jeka, John J
Mechanistic model of multisensory postural control
30 September 2002 - 31 August 2006
NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
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2.
Jeka, John J
MULTISENSORY INTEGRATION AND HUMAN POSTURAL CONTROL
1 July 1997 - 14 July 2002
NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
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3.
Jeka, John J
Multisensory Integration and Human Postural Control
1 July 1997 - 31 May 2009
NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
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4.
JEKA, JOHN JOSEPH
Multisensory Integration and Human Postural Control
1 July 1997 - 30 June 2011
NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
Scientific Context
This section shows information related to the publication - computed using the fingerprint of the publication - including related publications, related experts and related grants with fingerprints representing significant amounts of overlap between their fingerprint and this publication. The red dots indicate whether those experts or terms appear within the publication, thereby showing potential and actual connections.
Related Publications
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1.
2011Tim Kiemel; Yuanfen Zhang; John J Jeka
The Journal of neuroscience : the official journal of the Society for Neuroscience 2011;31(42):15144-53. -
2.
2012J P Scholz; E Park; J J Jeka; G Schöner; T Kiemel
How visual information links to multijoint coordination during quiet standing.
Experimental brain research. Experimentelle Hirnforschung. Expérimentation cérébrale 2012;222(3):229-39. -
3.
2012Paula F Polastri; José A Barela; Tim Kiemel; John J Jeka
Dynamics of inter-modality re-weighting during human postural control.
Experimental brain research. Experimentelle Hirnforschung. Expérimentation cérébrale 2012;223(1):99-108.

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