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  A Biodynamic Feedthrough Model Based on Neuromuscular Principles

Venrooij, J., Abbink, D., Mulder, M., van Paassen, M., van der Helm, F., & Bülthoff, H. (2014). A Biodynamic Feedthrough Model Based on Neuromuscular Principles. IEEE Transactions on Cybernetics, 44(7), 1141-1154. doi:10.1109/TCYB.2013.2280028.

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Venrooij, J1, 2, Autor           
Abbink, DA, Autor
Mulder, M, Autor
van Paassen, MM, Autor
van der Helm, FCT, Autor
Bülthoff, HH1, 2, Autor           
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Zusammenfassung: A biodynamic feedthrough (BDFT) model is proposed that describes how vehicle accelerations feed through the human body, causing involuntary limb motions and so involuntary control inputs. BDFT dynamics strongly depend on limb dynamics, which can vary between persons (between-subject variability), but also within one person over time, e.g., due to the control task performed (within-subject variability). The proposed BDFT model is based on physical neuromuscular principles and is derived from an established admittance model---describing limb dynamics---which was extended to include control device dynamics and account for acceleration effects. The resulting BDFT model serves primarily the purpose of increasing the understanding of the relationship between neuromuscular admittance and biodynamic feedthrough. An added advantage of the proposed model is that its parameters can be estimated using a two-stage approach, making the parameter estimation more robust, as the procedure is largely based on the well documented procedure required for the admittance model. To estimate the parameter values of the BDFT model, data are used from an experiment in which both neuromuscular admittance and biodynamic feedthrough are measured. The quality of the BDFT model is evaluated in the frequency and time domain. Results provide strong evidence that the BDFT model and the proposed method of parameter estimation put forward in this paper allows for accurate BDFT modeling across different subjects (accounting for between-subject variability) and across control tasks (accounting for within-subject variability).

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 Datum: 2014-07
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1109/TCYB.2013.2280028
BibTex Citekey: VenrooijAMvvB2013
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Titel: IEEE Transactions on Cybernetics
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 44 (7) Artikelnummer: - Start- / Endseite: 1141 - 1154 Identifikator: -