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.

Interaction between distant neuronal populations is essential for communication within the nervous system and can occur as a highly nonlinear process. To better understand the functional role of neural interactions, it is important to quantify the nonlinear connectivity in the nervous system. We introduce a general approach to measure nonlinear connectivity through phase coupling: the multi-spectral phase coherence (MSPC). Using simulated data, we compare MSPC with existing phase coupling measures, namely n : m synchronization index and bi-phase locking value. MSPC provides a system description, including (i) the order of the nonlinearity, (ii) the direction of interaction, (iii) the time delay in the system, and both (iv) harmonic and (v) intermodulation coupling beyond the second order; which are only partly revealed by other methods. We apply MSPC to analyze data from a motor control experiment, where subjects performed isotonic wrist flexions while receiving movement perturbations. MSPC between the perturbation, EEG and EMG was calculated. Our results reveal directional nonlinear connectivity in the afferent and efferent pathways, as well as the time delay (43 ± 8 ms) between the perturbation and the brain response. In conclusion, MSPC is a novel approach capable to assess high-order nonlinear interaction and timing in the nervous system.

Communication between neuronal populations is facilitated by synchronization of their oscillatory activity. Although nonlinearity has been observed in the sensorimotor system, its nonlinear connectivity has not been widely investigated yet. This study investigates nonlinear connectivity during the human stretch reflex based on neuronal synchronization. Healthy participants generated isotonic wrist flexion while receiving a periodic mechanical perturbation to the wrist. Using a novel cross-frequency phase coupling metric, we estimate directional nonlinear connectivity, including time delay, from the perturbation to brain and to muscle, as well as from brain to muscle. Nonlinear phase coupling is significantly stronger from the perturbation to the muscle than to the brain, with a shorter time delay. The time delay from the perturbation to the muscle is 33 ms, similar to the reported latency of the spinal stretch reflex at the wrist. Source localization of nonlinear phase coupling from the brain to the muscle suggests activity originating from the motor cortex, although its effect on the stretch reflex is weak. As such nonlinear phase coupling between the perturbation and muscle activity is dominated by the spinal reflex loop. This study provides new evidence of nonlinear neuronal synchronization in the stretch reflex at the wrist joint with respect to spinal and transcortical loops.

Biodynamic feedthrough (BDFT) is the feedthrough of vehicle accelerations through the human body, leading to involuntary control device inputs. BDFT is a relevant problem as it reduces control performance in a large range of vehicles under various circumstances. This paper proposes an approach to mitigate BDFT. What differentiates this method from other mitigation approaches is that it accounts for adaptations in the neuromuscular dynamics of the human body. It is known that BDFT is strongly dependent on these dynamics. The approach was tested, as proof-of-concept, in an experiment in a motion simulator where participants were asked to fly a simulated vehicle through a virtual tunnel. By evaluating the performance with and without motion disturbance active and with and without cancellation active, the performance of the cancellation approach was evaluated. Results showed that the cancellation approach was successful. The detrimental effects of BDFT, such as a decrease in control performance and increase in control effort, were largely removed.

For many applications such as steer-by-wire or telemanipulation, it remains unclear what tasks benef t most from accurate rendering of feedback forces. The objective of this study is to understand the extent to which haptic feedback of system dynamics helps performance of free-space telemanipulation tasks. In a human factors study, subjects performed a multisine pursuit task using two virtual slave systems, one with fast and one with slow dynamics. The dynamics of the controlled system were fed back fully, scaled or not at all. It was expected that task execution would improve when the boundaries of the controlled system were made tangible to the human operator by means of force feedback, but only for a slow dynamic system. Results show that, for a slow dynamic system, both full and scaled feedback of system dynamics reduce tracking error and excessive control input, at the expense of increased physical control effort. It is concluded that physically displaying the boundaries of the controlled system contribute to the human operator's understanding of the system, allowing to compensate for the limitations of the controlled dynamics, even if only a fraction of the full feedback is provided.

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).

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.

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.

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.

Deep-sea mining is an envisioned solution to cope with the fast increasing demand for rare-earth metals and decreasing supplies from conventional mines. It could involve a hydraulically actuated suspended grab to excavate metal-rich minerals from the seabed. Due to environmental uncertainties such an operation cannot be automated and should therefore be controlled by teleoperation, which traditionally suffers from sub optimal performance and limited situation awareness. The current study proposes two methods of hap tic feedback, natural force feedback and hap tic shared control, to improve the control of a grab in deep-sea mining. Natural force feedback is offered to improve the transparency of the system, which is hypothesized to improve situation awareness of the operation. Secondly it is hypothesized to reduce control effort by guiding the operator when offering hap tic shared control. Besides the individual effect, combining both hap tic feedback methods should also improve the overall task performance of the operation. A deep-sea mining simulation experiment is conducted to investigate the effect of these two hap tic feedback methods and their combination on operator control behaviour. The results show improvement of situation awareness (i.e. control errors) when offering natural force feedback and a reduction of control effort (i.e. control inputs) when offering hap tic shared control. However the results do not show an increase of task performance (i.e. excavated rock production) for either method. Although reduction of control error and effort will result eventually in long-term performance benefits. Combining both methods is therefore the best hap tic feedback method for improving a deep-sea mining teleoperation using a grab.

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.

Biodynamic feedthrough (BDFT) refers to a phenomenon where vehicle accelerations feed through the human body, causing involuntary limb motions, which may cause involuntary control inputs. Many studies have been devoted to mitigating BDFT effects. In the current paper, the effectiveness of a simple, cheap and widely-used hardware component is studied: the armrest. An experiment was conducted in which the BDFT dynamics were measured with and without armrest for different levels of neuromuscular admittance (i.e., different settings of the limb dynamics). The results show that the effect of the armrest on BDFT dynamics varies, both with frequency and neuromuscular admittance.

In tele-operation, haptic feedback from the remote environment to the human is often limited, which has been shown to negatively influence the performance and required time of tasks. The conventional research focus is on improving the quality of the haptic feedback (transparency), which may have led to significant improvement, but is still imperfect, with many unresolved issues. The present study presents an alternative approach to improve tele-operated tasks: by offering haptic shared control in which both operator and support system apply the required forces at the input (master) device. It is hypothesized that virtual forces from well-designed shared control will improve required time and accuracy, with less control effort, and that these benefits exist for perfect transparency but even more so for imperfect transparency. In an experimental study haptic shared control was designed to aid operators (n=9) with performing a simple bolt-spanner task using a planar (2D, 3DOF) tele-operator setup. The experimental results provided evidence for the hypotheses, showing that the tested tele-manipulation task benefits from haptic shared control, for three different levels of transparency. Essentially, the presence of haptic shared control allows for a worse transparency without compromising required time, and can even improve required time during perfect transparency.

In previous research, a driver support system that uses continuous haptic feedback on the gas pedal to inform drivers of the separation to the lead vehicle was developed. Although haptic feedback has been previously shown to be beneficial, the influence of the underlying biomechanical properties of the driver on the effectiveness of haptic feedback is largely unknown. The goal of this paper is to experimentally determine the biomechanical properties of the ankle-foot complex (i.e., the admittance) while performing a car-following task, thereby separating driver responses to visual feedback from those to designed haptic feedback. An experiment was conducted in a simplified fixed-base driving simulator, where ten participants were instructed to follow a lead vehicle, with and without the support of haptic feedback. During the experiment, the lead vehicle velocity was perturbed, and small stochastic torque perturbations were applied to the pedal. Both perturbations were separated in the frequency domain to allow the simultaneous estimation of frequency response functions of both the car-following control behavior and the biomechanical admittance. For comparison to previous experiments, the admittance was also estimated during three classical motion control tasks (resist forces, relax, and give way to forces). The main experimental hypotheses were that, first, the haptic feedback would encourage drivers to adopt a "give way to force task," resulting in larger admittance compared with other tasks and, second, drivers needed less control effort to realize the same car-following performance. Time- and frequency-domain analyses provided evidence for both hypotheses. The developed methodology allows quantification of the range of admittances that a limb can adopt during vehicle control or while performing a variety of motion control tasks. It thereby allows detailed computational driver modeling and provides valuable information on how to design and evaluate continuous haptic feedback systems.

To automatically align exoskeleton axes to human anatomical axes, we propose to decouple the joint rotations from the joint translations. Decoupling can reduce setup times and painful misalignment forces, at the cost of increased mechanical complexity and movement inertia. The decoupling approach was applied to the Dampace and Limpact exoskeletons.

Human task performance using teleoperator systems depends on the physical and controlled parameters of the system. Two teleoperated grasping tasks-size and stiffness discrimination-were studied to investigate how changes in system parameters influence human capabilities. The device characteristics altered were teleoperator stiffness (size and stiffness discrimination) and teleoperator damping (size discrimination only). It was found that neither teleoperator stiffness nor teleoperator damping influenced size discrimination. Also, teleoperator stiffness did not influence stiffness discrimination. Furthermore, teleoperated performance was compared with direct interaction using bare hands or with the fingers in a bracket. Size discrimination performance was equivalent for these three conditions, but stiffness discrimination performance was lower for teleoperation than for direct interaction.

This paper describes a novel ground development facility that is currently being built at the European Space Agency. The facility can be used to develop and test new man-machine interfaces for tele-control of dexterous space manipulators. Furthermore, the facility allows comparing performance of existing input devices, such as conventional joysticks, with novel devices, such as exoskeletons. The Ground Test-bed allows conducting tele-manipulation experiments with a real robot and to measure performance metrics during remote operations. The experimental comparisons planned to be undertaken with the test-bed are outlined.

This paper introduces a novel type of actuator that is investigated by ESA for force-reflection to a wearable exoskeleton. The actuator consists of a DC motor that is relocated from the joint by means of Bowden cable transmissions. The actuator shall support the development of truly ergonomic and compact wearable man-machine interfaces. Important Bowden cable transmission characteristics are discussed, which dictate a specific hardware design for such an actuator. A first prototype is shown, which was used to analyze these basic characteristics of the transmissions and to proof the overall actuation concept. A second, improved prototype is introduced, which is currently used to investigate the achievable performance as a master actuator in a master-slave control with force-feedback. Initial experimental results are presented, which show good actuator performance in a 4 channel control scheme with a slave joint. The actuator features low movement resistance in free motion and can reflect high torques during hard contact situations. High contact stability can be achieved. The actuator seems therefore well suited to be implemented into the ESA exoskeleton for space-robotic telemanipulation.

This paper describes a theoretical study on the use of an artificial force field in a collision avoidance system to generate force feedback to a neuromuscular arm. The study involves two separate tasks. The first task identifies the intrinsic and reflexive parameters of the human neuromuscular arm model. The second task is to include the neuromuscular arm model in closed-loop offline simulations in order to achieve more insight into the human-machine interaction, when applying haptic feedback. Results indicate that the human neuromuscular arm model responds well to the force feedback generated by the artificial force field and offers the possibility to tune the force field in order to achieve good performance without excessive control activity.

Stability control for walking bipeds has been considered a complex task. Even two-dimensional fore-aft stability in dynamic walking appears to be difficult to achieve. In this paper we prove the contrary, starting from the basic belief that in nature stability control must be the sum of a number of very simple rules. We study the global stability of the simplest walking model by determining the basin of attraction of the Poincare/spl acute/ map of this model. This shows that the walker, although stable, can only handle very small disturbances. It mostly falls, either forward or backward. We show that it is impossible for any form of swing leg control to solve backward falling. For the problem of forward falling, we devise a simple but very effective rule for swing leg action: "You will never fall forward if you put your swing leg fast enough in front of your stance leg. In order to prevent falling backward the next step, the swing leg shouldn't be too far in front." The effectiveness of this rule is demonstrated with our prototype "Mike.".