Admittance-Adaptive Model-Based Approach to Mitigate Biodynamic Feedthrough.

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.

Methods for Multiloop Identification of Visual and Neuromuscular Pilot Responses.

In this paper, identification methods are proposed to estimate the neuromuscular and visual responses of a multiloop pilot model. A conventional and widely used technique for simultaneous identification of the neuromuscular and visual systems makes use of cross-spectral density estimates. This paper shows that this technique requires a specific noninterference hypothesis, often implicitly assumed, that may be difficult to meet during actual experimental designs. A mathematical justification of the necessity of the noninterference hypothesis is given. Furthermore, two methods are proposed that do not have the same limitations. The first method is based on autoregressive models with exogenous inputs, whereas the second one combines cross-spectral estimators with interpolation in the frequency domain. The two identification methods are validated by offline simulations and contrasted to the classic method. The results reveal that the classic method fails when the noninterference hypothesis is not fulfilled; on the contrary, the two proposed techniques give reliable estimates. Finally, the three identification methods are applied to experimental data from a closed-loop control task with pilots. The two proposed techniques give comparable estimates, different from those obtained by the classic method. The differences match those found with the simulations. Thus, the two identification methods provide a good alternative to the classic method and make it possible to simultaneously estimate human's neuromuscular and visual responses in cases where the classic method fails.

A framework for biodynamic feedthrough analysis--part II: validation and application.

Biodynamic feedthrough (BDFT) is a complex phenomenon, that 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, the framework for BDFT analysis, as presented in Part I of this dual publication, is validated and applied. The goal of this framework is twofold. First of all, it provides some common ground between the seemingly large range of different approaches existing in BDFT literature. Secondly, the framework itself allows for gaining new insights into BDFT phenomena. Using recently obtained measurement data, parts of the framework that were not already addressed elsewhere, are validated. As an example of a practical application of the framework, it will be demonstrated how the effects of control device dynamics on BDFT can be understood and accurately predicted. Other ways of employing the framework are illustrated by interpreting the results of three selected studies from the literature using the BDFT framework. The presentation of the BDFT framework is divided into two parts. This paper, Part II, addresses the validation and application of the framework. Part I, which is also published in this journal issue, addresses the theoretical foundations of the framework. The work is presented in two separate papers to allow for a detailed discussion of both the framework's theoretical background and its validation.

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 framework's theoretical background and its validation.

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 model's 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 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.