Identification of the Feedback Components of the Neuromuscular System in a Pitch Control Task

Damveld, Herman J.; Abbink, David A.; Mulder, M.; Helm, F.C.T. van der; Hosman, Ruud

doi:10.2514/6.2010-7915

Cited by 8 publications

(19 citation statements)

References 29 publications

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“…This is important, as it might suggest that these parameters are related. Regarding the physical system that is modeled, i.e., a set of connected limbs, such a relationship would agree with expectations, as changing admittance is known to involve many muscles across the under-arm, upper-arm, and torso [27].…”

Section: B Bdft Modelmentioning

confidence: 93%

A Biodynamic Feedthrough Model Based on Neuromuscular Principles

Venrooij

Abbink

Mulder

et al. 2014

IEEE Trans. Cybern.

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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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Section: B Bdft Modelmentioning

confidence: 93%

A Biodynamic Feedthrough Model Based on Neuromuscular Principles

Venrooij

Abbink

Mulder

et al. 2014

IEEE Trans. Cybern.

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“…Research has focused on neuromuscular adaptation during disturbancerejection tasks that require humans to adopt different neuromuscular settings in response to force disturbances on the control device [23][24][25]. More recent work has shown that the neuromuscular response in an aircraft tracking task with different dynamics of the control device is highly variable [26,27]. Other studies indicated that the ankle-foot neuromuscular response of car drivers changes when a haptic aid is employed during a car-following task [21].…”

Section: Introductionmentioning

confidence: 97%

“…The pilot neuromuscular and visual responses are estimated by using three different multiloop identification techniques. The first is based on cross-spectral density analysis (CSD-based method) and has been commonly used for identifying pilot responses [21,27]. However, a recent work showed that the CSD-based method might provide a biased estimate of neuromuscular response if a noninterference hypothesis is not fulfilled [28].…”

Section: Introductionmentioning

confidence: 99%

Pilot Adaptation to Different Classes of Haptic Aids in Tracking Tasks

Olivari

Nieuwenhuizen

Bülthoff

et al. 2014

Journal of Guidance, Control, and Dynamics

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Haptic aids have been largely used in manual control tasks to complement the visual information through the sense of touch. To analytically design a haptic aid, adequate knowledge is needed about how pilots adapt their visual response and the biomechanical properties of their arm (i.e., admittance) to a generic haptic aid. In this work, two different haptic aids, a direct haptic aid and an indirect haptic aid, are designed for a target tracking task, with the aim of investigating the pilot response to these aids. The direct haptic aid provides forces on the control device that suggest the right control action to the pilot, whereas the indirect haptic aid provides forces opposite in sign with respect to the direct haptic aid. The direct haptic aid and the indirect haptic aid were tested in an experimental setup with nonpilot participants and compared to a condition without haptic support. It was found that control performance improved with haptic aids. Participants significantly adapted both their admittance and visual response to fully exploit the haptic aids. They were more compliant with the direct haptic aid force, whereas they showed stiffer neuromuscular settings with the indirect haptic aid, as this approach required opposing the haptic forces

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“…This measurement is regularly performed for standard task conditions, such as the Force-Task (FT), in which the human operator is instructed to keep the force on the manipulator constant, the position task (PT), in which the instruction is to keep the manipulator in a set position and relax task (RT), in which the operator should suppress responses to manipulator movement. Using the data from the test signal, measured force on the manipulator and measured manipulator displacement, and possibly aided by EMG measurement, the NMS admittance properties can be identified in several possible approaches Damveld et al (2010) and Venrooij et al (2014). An example of the results of such a measurement is given in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…The choice of a test signal is often based on experience, and often a test signal found in literature or used before is re-used, without inspecting its influence on the subject's (Damveld et al, 2010) behavior. In this paper, design choices for the identification signal are evaluated by simulation of a PT and a FT experiment, and evaluation of the endpoint variance (manipulator position for the PT and manipulator moment for the FT) for consistent variation of the model parameters.…”

Section: Introductionmentioning

confidence: 99%

Design of Test Signals for Identification of Neuromuscular Admittance

2016

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The human neuromuscular system can be seen as a versatile and extremely adaptive actuator. Through co-contraction and reflex modulation, the properties of the neuromuscular system can be modified, leading to a change in movement response to externally applied forces. These properties are normally expressed in the form of the neuromuscular admittance. In a series of standard tasks, the force-, relax-, and position-task admittance of the neuromuscular system can be identified. However, the test signals used in these tasks can also limit the range of reflex adaptation possible and wrong choice can create a phenomenon analogous to crossover regression in manual control tasks, and force the human to use only a limited range of the possible reflex adaptation. This paper presents a systematic investigation, through a model study, of the influence of test signals on the range of reflex adaptation. For this, criteria for test signal acceptability have been developed. The method is applied to the currently used test signals consisting of a high and a low shelf, and enables the selection of the high shelf bandwidth.

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Identification of the Feedback Components of the Neuromuscular System in a Pitch Control Task

Cited by 8 publications

References 29 publications

A Biodynamic Feedthrough Model Based on Neuromuscular Principles

A Biodynamic Feedthrough Model Based on Neuromuscular Principles

Pilot Adaptation to Different Classes of Haptic Aids in Tracking Tasks

Design of Test Signals for Identification of Neuromuscular Admittance

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