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A Method to Measure the Relationship Between Biodynamic Feedthrough and Neuromuscular Admittance

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons84279

Venrooij,  J
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Venrooij, J., Abbink DA, Mulder M, van Paassen, M., & Mulder, M. (2011). A Method to Measure the Relationship Between Biodynamic Feedthrough and Neuromuscular Admittance. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 41(4), 1158-1169. doi:10.1109/TSMCB.2011.2112347.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0013-BAB4-F
Abstract
Biodynamic feedthrough (BDFT) refers to a phenomenon where accelerations cause involuntary limb motions, which can result in unintentional control inputs that can substantially degrade manual control. It is known that humans can adapt the dynamics of their limbs by adjusting their neuromuscular settings, and it is likely that these adaptations have a large influence on BDFT. The goal of this paper is to present a method that can provide evidence for this hypothesis. Limb dynamics can be described by admittance, which is the causal dynamic relation between a force input and a position output. This paper presents a method to simultaneously measure BDFT and admittance in a motion-based simulator. The method was validated in an experiment. Admittance was measured by applying a force disturbance signal to the control device; BDFT was measured by applying a motion disturbance signal to the motion simulator. To allow distinguishing between the operator's responses to each disturbance signal, the perturbation signals were separated in the frequency domain. To show the impact of neuromuscular adaptation, subjects were asked to perform three different control tasks, each requiring a different setting of the neuromuscular system (NMS). Results show a dependence of BDFT on neuromuscular admittance: A change in neuromuscular admittance results in a change in BDFT dynamics. This dependence is highly relevant when studying BDFT. The data obtained with the proposed measuring method provide insight in how exactly the settings of the NMS influence the level of BDFT. This information can be used to gain fundamental knowledge on BDFT and also, for example, in the development of a canceling controller.