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  Admittance-Adaptive Model-Based Approach to Mitigate Biodynamic Feedthrough

Venrooij, J., Mulder, M., Mulder, M., Abbink, D., van Paassen, M., van der Helm, F., et al. (2017). Admittance-Adaptive Model-Based Approach to Mitigate Biodynamic Feedthrough. IEEE Transactions on Cybernetics, 47(12), 4169-4181. doi:10.1109/TCYB.2016.2601638.

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Venrooij, J1, Author           
Mulder, M, Author
Mulder, M, Author
Abbink, DA, Author
van Paassen, MM, Author
van der Helm, FCT, Author
Bülthoff, HH1, 2, 3, Author           
Affiliations:
1Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
2Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528701              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Biodynamic feedthrough (BDFT) refers to the feedthrough of vehicle accelerations through the human body, leading to involuntary control device inputs. BDFT impairs control performance in a large range of vehicles under various circumstances. Research shows that BDFT strongly depends on adaptations in the neuromuscular admittance dynamics of the human body. This paper proposes a model-based approach of BDFT mitigation that accounts for these neuromuscular adaptations. The method was tested, as proof-of-concept, in an experiment where participants inside a motion simulator controlled a simulated vehicle through a virtual tunnel. Through evaluating tracking performance and control effort with and without motion disturbance active and with and without cancellation active, the effectiveness of the cancellation was evaluated. Results show that the cancellation approach is successful: the detrimental effects of BDFT were largely removed.

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 Dates: 2017-12
 Publication Status: Issued
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 Identifiers: DOI: 10.1109/TCYB.2016.2601638
BibTex Citekey: VenrooijMMAvvB2016
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Title: IEEE Transactions on Cybernetics
Source Genre: Journal
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Pages: - Volume / Issue: 47 (12) Sequence Number: - Start / End Page: 4169 - 4181 Identifier: -