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Neural correlates of elbow joint kinematic variability
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Title
Neural correlates of elbow joint kinematic variability
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ETD_1873
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http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000051879
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eng
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theses
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Biomedical Engineering
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(authority = ETD-LCSH)
Topic
Human mechanics
Subject
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(authority = ETD-LCSH)
Topic
Joints--Range of motion
Subject
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(authority = ETD-LCSH)
Topic
Elbow--Movements
Abstract
A fundamental tenet of motor control is that point-to-point reaching motions follow an approximately straight line trajectory with a bell-shaped velocity profile. However, these abstractions are not universally observed. Previous work in our lab revealed that most spatiotemporal elbow trajectories do not necessarily conform to a straight-line, which is believed to be ‘natural’ human motion. Instead, spatiotemporal trajectories are best characterized by a small set of simple, analytic functions including both linear and non-linear waveforms. Here, I suggest that the differences observed in elbow kinematics are a direct consequence of varying motor planning, which is represented by the electromyography (EMG).
Fourteen healthy subjects were asked to perform several self-paced, untargeted elbow articulations that maximize smoothness within a comfortable range of motion; EMG of the biceps and kinematic traces were recorded simultaneously. Kinematic traces were modeled by a set of simple, monotonic functions, while EMG traces were reconstructed by parabolic waveforms, via a parameterized curve-fitting method. EMG traces (r-EMG) and their parabolic reconstructions (p-EMG) were used independently to predict adherence to each of 3 kinematic types. It was hypothesized that the p-EMG and r-EMG from the kinematic adherence group (r2 > 0.9979) would exhibit statistical and parametric differences from the departure group (r2 < 0.9951) of the same kinematic type.
Both r-EMG and p-EMG were useful in predicting adherence to global kinematic morphology with high sensitivity and specificity across subjects. Coupling the substantial predictive value and the similar information content (87.80% of the decisions were identical) of both EMG modalities implied that p-EMG can be used as a simple, informative approximant of r-EMG of the biceps during self-paced, untargeted elbow flexions. The features selected for classification were robust across subjects along with the predictive value, suggesting there is degeneracy in the neural command. Degeneracy in the neural command matches the widespread observation of highly stereotyped kinematics. Elbow trajectories most commonly adhered to sigmoid morphology. Future work should develop a comprehensive depiction of the neural control of voluntary movements.
Fourteen healthy subjects were asked to perform several self-paced, untargeted elbow articulations that maximize smoothness within a comfortable range of motion; EMG of the biceps and kinematic traces were recorded simultaneously. Kinematic traces were modeled by a set of simple, monotonic functions, while EMG traces were reconstructed by parabolic waveforms, via a parameterized curve-fitting method. EMG traces (r-EMG) and their parabolic reconstructions (p-EMG) were used independently to predict adherence to each of 3 kinematic types. It was hypothesized that the p-EMG and r-EMG from the kinematic adherence group (r2 > 0.9979) would exhibit statistical and parametric differences from the departure group (r2 < 0.9951) of the same kinematic type.
Both r-EMG and p-EMG were useful in predicting adherence to global kinematic morphology with high sensitivity and specificity across subjects. Coupling the substantial predictive value and the similar information content (87.80% of the decisions were identical) of both EMG modalities implied that p-EMG can be used as a simple, informative approximant of r-EMG of the biceps during self-paced, untargeted elbow flexions. The features selected for classification were robust across subjects along with the predictive value, suggesting there is degeneracy in the neural command. Degeneracy in the neural command matches the widespread observation of highly stereotyped kinematics. Elbow trajectories most commonly adhered to sigmoid morphology. Future work should develop a comprehensive depiction of the neural control of voluntary movements.
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electronic resource
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vii, 45 p. : ill.
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M.S.
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Includes bibliographical references (p. 44-45)
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by Gautam Siddarth Natarajan
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Natarajan
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Gautam Siddarth
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1986-
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Gautam Siddarth Natarajan
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Craelius
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William
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William Craelius
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Shoane
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George
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George Shoane
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Kim
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Nam-Hun
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Nam-Hun Kim
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Rutgers University
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Graduate School - New Brunswick
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2009
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2009-10
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xx
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Rutgers University Electronic Theses and Dissertations
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ETD
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Graduate School - New Brunswick Electronic Theses and Dissertations
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doi:10.7282/T3MK6D34
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ETD graduate
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The author owns the copyright to this work
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Copyright protected
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Open
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Natarajan
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Gautam
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Gautam Natarajan
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Rutgers University. Graduate School - New Brunswick
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
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