Nonparametric identification of human arm dynamics

Eric J. Perreault; Robert F. Kirsch; Ana Maria Acosta

Nonparametric identification of human arm dynamics

Eric J. Perreault^*, Robert F. Kirsch, Ana Maria Acosta

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Understanding the dynamic response of the human arm to external perturbations is critical for understanding the neural and mechanical factors contributing to postural arm stability and for predicting stability during interactions with the external environment. One means of describing arm dynamics is by estimating the dynamic endpoint stiffness (DES). This paper introduces an efficient nonparametric approach for estimating DES, and uses this technique to characterize changes in DES under different endpoint loading conditions.

Original language	English (US)
Pages (from-to)	1835-1836
Number of pages	2
Journal	Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume	4
State	Published - Dec 1 1997

ASJC Scopus subject areas

Bioengineering

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title = "Nonparametric identification of human arm dynamics",

abstract = "Understanding the dynamic response of the human arm to external perturbations is critical for understanding the neural and mechanical factors contributing to postural arm stability and for predicting stability during interactions with the external environment. One means of describing arm dynamics is by estimating the dynamic endpoint stiffness (DES). This paper introduces an efficient nonparametric approach for estimating DES, and uses this technique to characterize changes in DES under different endpoint loading conditions.",

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AU - Acosta, Ana Maria

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N2 - Understanding the dynamic response of the human arm to external perturbations is critical for understanding the neural and mechanical factors contributing to postural arm stability and for predicting stability during interactions with the external environment. One means of describing arm dynamics is by estimating the dynamic endpoint stiffness (DES). This paper introduces an efficient nonparametric approach for estimating DES, and uses this technique to characterize changes in DES under different endpoint loading conditions.

AB - Understanding the dynamic response of the human arm to external perturbations is critical for understanding the neural and mechanical factors contributing to postural arm stability and for predicting stability during interactions with the external environment. One means of describing arm dynamics is by estimating the dynamic endpoint stiffness (DES). This paper introduces an efficient nonparametric approach for estimating DES, and uses this technique to characterize changes in DES under different endpoint loading conditions.

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