Classification of resistance to passive motion using minimum probability of error criterion
Identifieur interne : 002930 ( Main/Exploration ); précédent : 002929; suivant : 002931Classification of resistance to passive motion using minimum probability of error criterion
Auteurs : C. Chan [États-Unis] ; T. Manry [États-Unis] ; V. Kondraske [États-Unis]Source :
- Annals of Biomedical Engineering [ 0090-6964 ] ; 1987-11-01.
Abstract
Abstract: Neurologists diagnose many muscular and nerve disorders by classifying the resistance to passive motion of patients' limbs. Over the past several years, a computer-based instrument has been developed for automated measurement and parameterization of this resistance. In the device, a voluntarily relaxed lower extremity is moved at constant velocity by a motorized driver. The torque exerted on the extremity by the machine is sampled, along with the angle of the extremity. In this paper a computerized technique is described for classifying a patient's condition as ‘Normal’ or ‘Parkinson disease’ (rigidity), from the torque versus angle curve for the knee joint. A Legendre polynomial, fit to the curve, is used to calculate a set of eight normally distributed features of the curve. The minimum probability of error approach is used to classify the curve as being from a normal or Parkinson disease patient. Data collected from 44 different subjects was processed and the results were compared with an independent physician's subjective assessment of rigidity. There is agreement in better than 95% of the cases, when all of the features are used.
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DOI: 10.1007/BF02364250
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Chan</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><placeName><region type="state">Texas</region></placeName><wicri:cityArea>Department of Electrical Engineering, University of Texas at Arlington, 76019, Arlington</wicri:cityArea></affiliation></author><author><name sortKey="Manry, T" sort="Manry, T" uniqKey="Manry T" first="T." last="Manry">T. Manry</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><placeName><region type="state">Texas</region></placeName><wicri:cityArea>Department of Electrical Engineering, University of Texas at Arlington, 76019, Arlington</wicri:cityArea></affiliation></author><author><name sortKey="Kondraske, V" sort="Kondraske, V" uniqKey="Kondraske V" first="V." last="Kondraske">V. Kondraske</name><affiliation wicri:level="2"><country xml:lang="fr">États-Unis</country><placeName><region type="state">Texas</region></placeName><wicri:cityArea>Department of Electrical Engineering, University of Texas at Arlington, 76019, Arlington</wicri:cityArea></affiliation></author></analytic><monogr></monogr><series><title level="j">Annals of Biomedical Engineering</title><title level="j" type="abbrev">Ann Biomed Eng</title><idno type="ISSN">0090-6964</idno><idno type="eISSN">1573-9686</idno><imprint><publisher>Kluwer Academic Publishers</publisher><pubPlace>Dordrecht</pubPlace><date type="published" when="1987-11-01">1987-11-01</date><biblScope unit="volume">15</biblScope><biblScope unit="issue">6</biblScope><biblScope unit="page" from="579">579</biblScope><biblScope unit="page" to="590">590</biblScope></imprint><idno type="ISSN">0090-6964</idno></series><idno type="istex">5F6511ACE4A1B2C0F52B06F1AD637256B3FD3927</idno><idno type="DOI">10.1007/BF02364250</idno><idno type="ArticleID">Art4</idno><idno type="ArticleID">BF02364250</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0090-6964</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: Neurologists diagnose many muscular and nerve disorders by classifying the resistance to passive motion of patients' limbs. Over the past several years, a computer-based instrument has been developed for automated measurement and parameterization of this resistance. In the device, a voluntarily relaxed lower extremity is moved at constant velocity by a motorized driver. The torque exerted on the extremity by the machine is sampled, along with the angle of the extremity. In this paper a computerized technique is described for classifying a patient's condition as ‘Normal’ or ‘Parkinson disease’ (rigidity), from the torque versus angle curve for the knee joint. A Legendre polynomial, fit to the curve, is used to calculate a set of eight normally distributed features of the curve. The minimum probability of error approach is used to classify the curve as being from a normal or Parkinson disease patient. Data collected from 44 different subjects was processed and the results were compared with an independent physician's subjective assessment of rigidity. There is agreement in better than 95% of the cases, when all of the features are used.</div></front></TEI><affiliations><list><country><li>États-Unis</li></country><region><li>Texas</li></region></list><tree><country name="États-Unis"><region name="Texas"><name sortKey="Chan, C" sort="Chan, C" uniqKey="Chan C" first="C." last="Chan">C. Chan</name></region><name sortKey="Kondraske, V" sort="Kondraske, V" uniqKey="Kondraske V" first="V." last="Kondraske">V. Kondraske</name><name sortKey="Manry, T" sort="Manry, T" uniqKey="Manry T" first="T." last="Manry">T. Manry</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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