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RISS 인기검색어
- 검색키워드
- 저자 : van Paassen, Marinus M. (검색결과 5 건)
- 무료
- 기관 내 무료
- 유료
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A Framework for Biodynamic Feedthrough Analysis—Part II: Validation and Application
Venrooij, Joost,van Paassen, Marinus M.,Mulder, Mark,Abbink, David A.,Mulder, Max,van der Helm, Frans C. T.,Bulthoff, Heinrich H. IEEE 2014 IEEE transactions on cybernetics Vol.44 No.9
<P>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.</P>
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A Framework for Biodynamic Feedthrough Analysis—Part I: Theoretical Foundations
Venrooij, Joost,van Paassen, Marinus M.,Mulder, Mark,Abbink, David A.,Mulder, Max,van der Helm, Frans C. T.,Bulthoff, Heinrich H. IEEE 2014 IEEE transactions on cybernetics Vol.44 No.9
<P>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.</P>
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A Biodynamic Feedthrough Model Based on Neuromuscular Principles
Venrooij, Joost,Abbink, David A.,Mulder, Mark,van Paassen, Marinus M.,Mulder, Max,van der Helm, Frans C. T.,Bü,lthoff, Heinrich H. IEEE 2014 IEEE transactions on cybernetics Vol.44 No.7
<P>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).</P>
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Mathematical Biodynamic Feedthrough Model Applied to Rotorcraft
Venrooij, Joost,Mulder, Mark,Abbink, David A.,van Paassen, Marinus M.,Mulder, Max,van der Helm, Frans C. T.,Bulthoff, Heinrich H. IEEE 2014 IEEE transactions on cybernetics Vol.44 No.7
<P>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.</P>
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