Estimates of Acausal Joint Impedance Models
Identifieur interne : 001591 ( Pmc/Curation ); précédent : 001590; suivant : 001592Estimates of Acausal Joint Impedance Models
Auteurs : David. T. Westwick ; Eric J. PerreaultSource :
- IEEE transactions on bio-medical engineering [ 0018-9294 ] ; 2012.
Abstract
Estimates of joint or limb impedance are commonly used in the study of how the nervous system controls posture and movement, and how that control is altered by injury to the neural or musculoskeletal systems. Impedance characterizes the dynamic relationship between an imposed perturbation of joint position and the torques generated in response. While there are many practical reasons for estimating impedance rather than its inverse, admittance, it is an acausal representation of the limb mechanics that can lead to difficulties in interpretation or use. The purpose of this study was to explore the acausal nature of nonparametric estimates of joint impedance representations to determine how they are influenced by common experimental and computational choices. This was accomplished by deriving discrete-time realizations of first-and second-order derivatives to illustrate two key difficulties in the physical interpretation of impedance impulse response functions. These illustrations were provided using both simulated and experimental data. It was found that the shape of the impedance impulse response depends critically on the selected sampling rate, and on the bandwidth and noise characteristics of the position perturbation used during the estimation process. These results provide important guidelines for designing experiments in which nonparametric estimates of impedance will be obtained, especially when those estimates are to be used in a multistep identification process.
Url:
DOI: 10.1109/TBME.2012.2213339
PubMed: 22907963
PubMed Central: 3601445
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PMC:3601445Le document en format XML
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<front><div type="abstract" xml:lang="en"><p id="P1">Estimates of joint or limb impedance are commonly used in the study of how the nervous system controls posture and movement, and how that control is altered by injury to the neural or musculoskeletal systems. Impedance characterizes the dynamic relationship between an imposed perturbation of joint position and the torques generated in response. While there are many practical reasons for estimating impedance rather than its inverse, admittance, it is an acausal representation of the limb mechanics that can lead to difficulties in interpretation or use. The purpose of this study was to explore the acausal nature of nonparametric estimates of joint impedance representations to determine how they are influenced by common experimental and computational choices. This was accomplished by deriving discrete-time realizations of first-and second-order derivatives to illustrate two key difficulties in the physical interpretation of impedance impulse response functions. These illustrations were provided using both simulated and experimental data. It was found that the shape of the impedance impulse response depends critically on the selected sampling rate, and on the bandwidth and noise characteristics of the position perturbation used during the estimation process. These results provide important guidelines for designing experiments in which nonparametric estimates of impedance will be obtained, especially when those estimates are to be used in a multistep identification process.</p>
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<journal-id journal-id-type="nlm-ta">IEEE Trans Biomed Eng</journal-id>
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<title-group><article-title>Estimates of Acausal Joint Impedance Models</article-title>
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<contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Westwick</surname>
<given-names>David. T.</given-names>
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<role>Member IEEE</role>
<aff id="A1">Department of Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada</aff>
<email>dwestwic@ucalgary.ca</email>
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<contrib contrib-type="author"><name><surname>Perreault</surname>
<given-names>Eric J.</given-names>
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<role>Member IEEE</role>
<aff id="A2">Department of Biomedical Engineering and the Department of Physical Medicine and Rehabilitation, Northwestern University, Evanston, IL 60208 USA, and also with the Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Chicago, IL 60611 USA</aff>
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<pub-date pub-type="nihms-submitted"><day>20</day>
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<year>2013</year>
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<pub-date pub-type="epub"><day>15</day>
<month>8</month>
<year>2012</year>
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<pub-date pub-type="ppub"><month>10</month>
<year>2012</year>
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<pub-date pub-type="pmc-release"><day>01</day>
<month>10</month>
<year>2013</year>
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<volume>59</volume>
<issue>10</issue>
<fpage>2913</fpage>
<lpage>2921</lpage>
<permissions><copyright-statement>Copyright ©2012 IEEE.</copyright-statement>
<copyright-year>2012</copyright-year>
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<abstract><p id="P1">Estimates of joint or limb impedance are commonly used in the study of how the nervous system controls posture and movement, and how that control is altered by injury to the neural or musculoskeletal systems. Impedance characterizes the dynamic relationship between an imposed perturbation of joint position and the torques generated in response. While there are many practical reasons for estimating impedance rather than its inverse, admittance, it is an acausal representation of the limb mechanics that can lead to difficulties in interpretation or use. The purpose of this study was to explore the acausal nature of nonparametric estimates of joint impedance representations to determine how they are influenced by common experimental and computational choices. This was accomplished by deriving discrete-time realizations of first-and second-order derivatives to illustrate two key difficulties in the physical interpretation of impedance impulse response functions. These illustrations were provided using both simulated and experimental data. It was found that the shape of the impedance impulse response depends critically on the selected sampling rate, and on the bandwidth and noise characteristics of the position perturbation used during the estimation process. These results provide important guidelines for designing experiments in which nonparametric estimates of impedance will be obtained, especially when those estimates are to be used in a multistep identification process.</p>
</abstract>
<kwd-group><title>Index Terms</title>
<kwd>Discrete-time</kwd>
<kwd>joint dynamics</kwd>
<kwd>parametric model</kwd>
<kwd>sampling</kwd>
<kwd>system identification</kwd>
<kwd>time domain</kwd>
<kwd>two-sided impulse response</kwd>
</kwd-group>
<funding-group><award-group><funding-source country="United States">National Institute of Neurological Disorders and Stroke : NINDS</funding-source>
<award-id>R01 NS053813 || NS</award-id>
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