Joost Venrooij

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

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 operators 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.

Biodynamic feedthrough is task dependent

Vehicle accelerations may lead to involuntary limb motions. These motions can result into involuntary control inputs when performing a manual control task. This phenomenon is called biodynamic feedthrough (BDFT). This paper aims to show that task interpretation plays an important role in the occurrence of BDFT. Results of an experiment are presented, in which biodynamic feedthrough was measured during three different control tasks. Each control task required the human operator to adapt his/her neuromuscular settings. The results show that the level of biodynamic feedthrough depends on the task the human operator is performing. From further analysis, it can be observed that the experiment results are in good agreement with BDFT measurements found in literature. The comparison confirms that the task interpretation plays an important role in BDFT which cannot be ignored when attempting to understand or mitigate BDFT in practical situations.

A New View on Biodynamic Feedthrough Analysis: Unifying the Effects on Forces and Positions

When performing a manual control task, vehicle accelerations can cause involuntary limb motions, which can result in unintentional control inputs. This phenomenon is called biodynamic feedthrough (BDFT). In the past decades, many studies into BDFT have been performed, but its fundamentals are still only poorly understood. What has become clear, though, is that BDFT is a highly complex process, and its occurrence is influenced by many different factors. A particularly challenging topic in BDFT research is the role of the human operator, which is not only a very complex but also a highly adaptive system. In literature, two different ways of measuring and analyzing BDFT are reported. One considers the transfer of accelerations to involuntary forces applied to the control device (CD); the other considers the transfer of accelerations to involuntary CD deflections or positions. The goal of this paper is to describe an approach to unify these two methods. It will be shown how the results of the two methods relate and how this knowledge may aid in understanding BDFT better as a whole. The approach presented is based on the notion that BDFT dynamics can be described by the combination of two transfer dynamics: 1) the transfer dynamics from body accelerations to involuntary forces and 2) the transfer dynamics from forces to CD deflections. The approach was validated using experimental results.

Multi-loop Pilot Behaviour Identication in Response to Simultaneous Visual and Haptic Stimuli

The goal of this paper is to better understand how the neuromuscular system of a pilot, or more generally an operator, adapts itself to di erent types of haptic aids during a pitch control task. A multi-loop pilot model, capable of describing the human behaviour during a tracking task, is presented. Three di erent identi cation techniques were investigated in order to simultaneously identify neuromuscular admittance and the visual response of a human pilot. In one of them, the various frequency response functions that build up the pilot model are identi ed using multi-inputs linear time-invariant models in ARX form. A second method makes use of cross-spectral densities and diagram block algebra to obtain the desired frequency response estimates. The identi cation techniques were validated using Monte Carlo simulations of a closed-loop control task. Both techniques were compared with the results of another identi cation method well known in literature and based on crossspectral density estimates. All those methods were applied in an experimental setup in which pilots performed a pitch control task with di erent haptic aids. Two di erent haptic aids for tracking task are presented, a Direct Haptic Aid and an Indirect Haptic Aid. The two haptic aids were compared with a baseline condition in which no haptic force was used. The data obtained with the proposed method provide insight in how the pilot adapts his control behavior in relation to di erent haptic feedback schemes. From the experimental results it can be concluded that humans adapt their neuromuscular admittance in relation with di erent haptic aids. Furthermore, the two new identi cation techniques seemed to give more reliable admittance estimates.

Relating biodynamic feedthrough to neuromuscular admittance

When an operator in a moving vehicle is performing a manual control task, the accelerations to which the operator is subjected can result in unintentional control inputs. This biodynamic feedthrough (BDFT) depends on the properties of the control device and of the control limb. Humans can adjust the dynamics properties of their limbs, effectively changing the limb admittance. Previous studies of BDFT did not consider the effect of this adjustment. This paper describes a model for BDFT and an experiment in a moving base simulator with subjects performing a control task with a side stick. During the experiment the neuromuscular admittance was varied by using different control tasks, each requiring a different neuromuscular setting. The non-parametric results of this experiment show that the level of feedthrough is strongly dependent on both the frequency of the disturbance and the neuromuscular admittance. The results furthermore suggest that a relationship can be established between admittance and biodynamic feedthrough.

Mathematical Biodynamic Feedthrough Model Applied to Rotorcraft

Biodynamic feedthrough (BDFT) occurs when vehicle accelerations feed through the human body and cause involuntary control inputs. This paper proposes a model to quantitatively predict this effect in rotorcraft. This mathematical BDFT model aims to fill the gap between the currently existing black box BDFT models and physical BDFT models. The model structure was systematically constructed using asymptote modeling, a procedure described in detail in this paper. The resulting model can easily be implemented in many typical rotorcraft BDFT studies, using the provided model parameters. The models performance was validated in both the frequency and time domain. Furthermore, it was compared with several recent BDFT models. The results show that the proposed mathematical model performs better than typical black box models and is easier to parameterize and implement than a recent physical model.

A Biodynamic Feedthrough Model Based on Neuromuscular Principles

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).

A review of biodynamic feedthrough mitigation techniques

Abstract Biodynamic feedthrough (BDFT) refers to a phenomenon where accelerations cause involuntary limb motions which, when coupled to a control device, can result in unintentional control inputs. Biodynamic feedthrough can occur in many different vehicles and under various conditions, which makes it highly relevant to study its mechanisms. In this paper the possible biodynamic feedthrough mitigation techniques are discussed and evaluated. From these, two solution types are regarded to be the most promising. Measures of the first solution type are already commonly applied and consist of passive measures to restrain and immobilize body parts. The second solution type is the model-based cancellation approach, where use is made of a BDFT model to obtain a canceling signal. The model-based cancellation approach is currently investigated.

A Framework for Biodynamic Feedthrough Analysis Part I: Theoretical Foundations

Biodynamic feedthrough (BDFT) is a complex phenomenon, which has been studied for several decades. However, there is little consensus on how to approach the BDFT problem in terms of definitions, nomenclature, and mathematical descriptions. In this paper, a framework for biodynamic feedthrough analysis is presented. The goal of this framework is two-fold. First, it provides some common ground between the seemingly large range of different approaches existing in the BDFT literature. Second, the framework itself allows for gaining new insights into BDFT phenomena. It will be shown how relevant signals can be obtained from measurement, how different BDFT dynamics can be derived from them, and how these different dynamics are related. Using the framework, BDFT can be dissected into several dynamical relationships, each relevant in understanding BDFT phenomena in more detail. The presentation of the BDFT framework is divided into two parts. This paper, Part I, addresses the theoretical foundations of the framework. Part II, which is also published in this issue, addresses the validation of the framework. The work is presented in two separate papers to allow for a detailed discussion of both the frameworks theoretical background and its validation.

Cancelling biodynamic feedthrough requires a subject and task dependent approach

Vehicle accelerations may feed through the human body, causing involuntary limb motions which may lead to involuntary control inputs. This phenomenon is called biodynamic feedthrough (BDFT). Signal cancellation is a possible way of mitigating biodynamic feedthrough. It makes use of a BDFT model to estimate the involuntary control inputs. The BDFT effects are removed by subtracting the modeled estimate of the involuntary control input from the total control signal, containing both voluntary and involuntary components. The success of signal cancellation hinges on the accuracy of the BDFT model used. In this study the potential of signal cancellation is studied by making use of a method called optimal signal cancellation. Here, an identified BDFT model is used off-line to generate an estimate of the involuntary control inputs based on the accelerations present. Results show that reliable signal cancellation requires BDFT models that are both subject and task dependent. The task dependency is of particular importance: failing to adapt the model to changes in the operators neuromuscular dynamics dramatically decreases the quality of cancellation and can even lead to an increase in unwanted effects. As a reliable and fast on-line identification method of the neuromuscular dynamics of the human operator currently does not exist, real-time signal cancellation is currently not feasible.