Manual Control Tasks Research Articles

Human Performance Time Model of Spacecraft Control Panel Operation in Simulated Microgravity

Human performance modeling plays an important role in the design and management of human spaceflight missions. Previous studies reported that manual control task time increased in microgravity conditions. The current study aimed to find a modeling method that can quantify and predict the task time of spacecraft control panel operation in the simulated microgravity condition. We proposed the application of a predetermined elemental task method together with an information processing time model to quantify both physical motion time and cognitive time. The time increment due to microgravity was hypothesized to be proportional to physical motion time. The total task time in the microgravity condition could be calculated as the model time from the normal ground condition plus the predicted time increment. Human data were collected from an experiment asking participants to perform six emergency operating procedure tasks in both normal ground and simulated microgravity conditions. The proposed method resulted in good fitness to human data in both conditions, as shown by both regression fitness (R2 values = 0.99) and modeling error measures (root mean square error ≤ 3.3 s; mean absolute percentage error ≤ 16.1%). Although the method has its limitations, the current findings suggest that it has value in aerospace human factors and ergonomics applications.Cao S, Zhang Y, Guo Y, Chen S. Human performance time model of spacecraft control panel operation in simulated microgravity. Aerosp Med Hum Perform. 2017; 88(8):743-751.

Objective Model Selection for Identifying the Human Feedforward Response in Manual Control.

Realistic manual control tasks typically involve predictable target signals and random disturbances. The human controller (HC) is hypothesized to use a feedforward control strategy for target-following, in addition to feedback control for disturbance-rejection. Little is known about human feedforward control, partly because common system identification methods have difficulty in identifying whether, and (if so) how, the HC applies a feedforward strategy. In this paper, an identification procedure is presented that aims at an objective model selection for identifying the human feedforward response, using linear time-invariant autoregressive with exogenous input models. A new model selection criterion is proposed to decide on the model order (number of parameters) and the presence of feedforward in addition to feedback. For a range of typical control tasks, it is shown by means of Monte Carlo computer simulations that the classical Bayesian information criterion (BIC) leads to selecting models that contain a feedforward path from data generated by a pure feedback model: "false-positive" feedforward detection. To eliminate these false-positives, the modified BIC includes an additional penalty on model complexity. The appropriate weighting is found through computer simulations with a hypothesized HC model prior to performing a tracking experiment. Experimental human-in-the-loop data will be considered in future work. With appropriate weighting, the method correctly identifies the HC dynamics in a wide range of control tasks, without false-positive results.

Pilot Stick Input Estimates from Attitude Commands as Indicator of Systemic Changes

Control-theoretic modeling of the human operator dynamic behavior in manual control tasks has a long and rich history. In the last two decades, there has been a renewed interest in modeling the human operator. There has also been significant work on techniques used to identify the pilot model of a given structure. The purpose of this research is to attempt to go beyond identification of a pilot model based on collected experimental data and to develop a predictor of pilot behavior. Two sets of experimental data were analyzed: 1) the effects of an adaptive controller on pilot compensation during control surface failures in cruise and 2) heads-up-display concepts during takeoff and landing. A general linear in-parameter model structure is used to represent a pilot. Three different estimation methods are explored—a gradient descent estimator, a least squares estimator with exponential forgetting, and a least squares estimator with bounded gain forgetting. This paper discusses the accuracy of each of the three methods to estimate pilot longitudinal and lateral stick input from the flight director’s commanded pitch and bank attitudes and the differences in piloting techniques during takeoff, cruise, and landing phases of flight.

Design of Test Signals for Identification of Neuromuscular Admittance

The human neuromuscular system can be seen as a versatile and extremely adaptive actuator. Through co-contraction and reex 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 reex adaptation possible and wrong choice can create a phenomenon analogous to cross-over regression in manual control tasks, and force the human to use only a limited range of the possible reex adaptation. This paper presents a systematic investigation, through a model study, of the inuence of test signals on the range of reex 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.

Design, Realization and Experimental Evaluation of a Haptic Stick for Shared Control Studies

Abstract: Shared control is becoming widely used in many manual control tasks as a mean for improving performance and safety. Designing an effective shared control system requires extensive testing and knowledge of how operators react to the haptic sensations provided by the control device shared with the support system. Commercial general purpose haptic devices may be unfit to reproduce the operational situation typical of the control task under study, like car driving or airplane flying. Thus specific devices are needed for research on specific task; this market niche exists but is characterized by expensive products. This paper presents the development of a complete low cost haptic stick, of its initial characterization and inner loop and impedance control systems design, and finally proposes an evaluation with two test cases: pilot admittance identification with the classical tasks, and an entire haptic experiment. In particular this latter experiment tries to study what happens when a system failure happens in a pilot support system built using a classical embedded controller, compared to a system built following the haptic shared control paradigm.

Human Crossfeed in Dual-Axis Manual Control with Motion Feedback

While many realistic manual control tasks require human operators to control multiple degrees-of-freedomsimultaneously, our understanding of such multi-axis manual control has not moved far beyond considering it simply as the control of multiple fully-independent axes. This investigation aims to further our understanding of multi-axis control by focusing on one phenomenon that is known to occur in such tasks: crossfeed. Crossfeed occurs when operators’ inputs in one controlled axis feed into another controlled degree-of-freedom, thereby affecting overall control performance. A human-in-the-loop experiment, in which operators performed a dual-axis aircraft roll and pitch tracking task with physical motion feedback, was conducted in the SIMONA Research Simulator at TU Delft. Three conditions were tested: the full dual-axis control task, supplemented with reference single-axis roll and pitch tasks. Through the use of independent target and disturbance forcing function signals in both controlled axes, we were able to detect the presence of crossfeed in this dual-axis task from spectral analysis. Furthermore, these signals facilitated the objective identification of the dynamics of the crossfeed contribution, in parallel with estimating operators visual and motion responses. The crossfeed dynamics were found to resemble the well-known dynamics of human operators’ visual responses. The crossfeed contribution was found to explain up to 20% of the measured control inputs, thereby indicating that crossfeed can be a factor of significance in multi-axis manual control.

Pilot behavior modeling and its application to manual control tasks

Abstract: The modified two pilot behavior models are discussed. One of them is the structural model. Its modification allowed to get better agreement in calculation of variance of error and to evaluate the influence of some new task variables (control element gain coefficient, requirements to the accuracy) on pilot – vehicle system parameters. The other model is the composite model of pilot behavior based on neural network approach. This model provides high agreement between the simulated and experimental pilot frequency response characteristics. The structural model is used for development of the criterion for the of flying qualities prediction in lateral channel with taking into account the influence of motion cues on pilot behavior and for the preliminary design of the predictive display. As for the composite model it was used for development of the flying qualities criterion for the pitch control task based on calculation of pilot and pilot aircraft system frequency response parameters. The additional procedure - the preliminary selection of dynamic configurations from the database was proposed what allowed to get high agreement between the predicted flying qualities level evaluated by the pilots in flight tests.

Visuomotor control in patients with Parkinson's disease

Previous studies have suggested that the deteriorated visuomotor control in patients with PD (Parkinson's disease) is due to deficits in various aspects of the sensory-motor processing rather than motor control itself. In the current study, by taking a control-theoretic approach, we systematically examined how PD and antiparkinsonian medication affect visuomotor control and the underlying sensory-motor system.We tested 20 PD patients in both ON and OFF medication states and 20 demographically matched healthy controls with a commonly used manual control task. Specifically, in each 95-s trial, participants were instructed to use a joystick to control a randomly moving target to keep it centered on a computer display. We found that although antiparkinsonian medication improved visuomotor control in PD patients, they still showed significantly decreased control precision (measured by RMS error) and response amplitude (gain) as well as increased response delay (phase lag) compared with healthy controls.Our model-driven analysis revealed that PD impairs the responsiveness and the predicting ability of the sensory–motor system as well as the stability of the neuromuscular system. Taking antiparkinsonian medication improves the responsiveness of the sensory–motor system. More importantly, it improves the ability of the sensory–motor system to make sensory predictions of the current control actions (see Wolpert et al., 1995) to anticipate the input error signals and generate control responses ahead of time up to the level of healthy controls. However, taking antiparkinsonian medication does not improve the stability of the neuromuscular system. These results support the claim that the effect of antiparkinsonian medication on visuomotor control is mainly through improving visual-stimulus-dependent sensory–motor processing.The present study provides the first quantitative examination of the effects of PD and antiparkinsonian medication on the visual-stimulus-dependent sensory–motor and visual-stimulus-independent neuromuscular systems underlying visuomotor control. The findings have practical implications for developing sensitive assessment tools to evaluate the efficacy of different therapies for PD and preliminary screening and training tools for fitness-to-drive in PD patients.

Simultaneous and independent control of a brain-computer interface and contralateral limb movement

Toward expanding the population of potential BCI users to the many individuals with lateralized cortical stroke, we examined whether the cortical hemisphere controlling ongoing movements of the contralateral limb can simultaneously generate signals to control a BCI. A monkey was trained to perform a simultaneous BCI and manual control task designed to test whether one hemisphere could effectively differentiate its output and provide independent control of two tasks. Pairs of well-isolated single units were used to control a BCI cursor in one dimension, while isometric wrist torque of the contralateral forelimb controlled the cursor in a second dimension. The monkey could independently modulate cortical units and contralateral wrist torque regardless of the strength of directional tuning of the units controlling the BCI. When the presented targets required explicit decoupling of unit activity and wrist torque, directionally tuned units exhibited significantly less efficient cursor trajectories compared to when unit activity and wrist torque could remain correlated. The results indicate that neural activity from a single hemisphere can be effectively decoupled to simultaneously control a BCI and ongoing limb movement, suggesting that BCIs may be a viable future treatment for individuals with lateralized cortical stroke.

Action Videogame Play Improves Visual Motor Control

Can action videogame play improve visual motor control? If yes, can it be used in training complex visual motor skills such as driving? Here we took a control-theoretic approach and tested non-video-game players with a typical compensatory manual control task. After playing a driving (Experiment 1) or a first-person shooter (FPS) action videogame (Experiment 2) for only five hours, participants improved significantly in both the control precision (measured as the RMS error) and response amplitude (gain) for their performance on the manual control task. No enhancement on participants’ contrast sensitivity function was observed. We fit the performance data to an extensively validated Crossover Model to further understand how action gaming affects the perceptual system that processes visual information and the neuromuscular system that executes the control command. Our model-driven analysis revealed that playing either a driving or an FPS game improved the perceptual sensitivity to input visual information for online motor control; that playing the FPS game also facilitated anticipating input errors to generate control ahead of time but hurt the stability of the neuromuscular system. In contrast, no effect on the control performance was observed for participants who played a non-action videogame. We then examined whether the improvement in the performance on the manual control task can transfer to daily visual motor control tasks such as driving. We found that lane-keeping performance significantly improved for participants who completed a 40-min training session of the manual control task while no such improvement was observed for participants without training. In summary, the present study provides the first empirical evidence for a causal link between action gaming (for as short as five hours playing) and enhancement in visual motor control. The findings have practical implications for developing training tools to improve performance on daily visual motor control tasks such as driving. Meeting abstract presented at VSS 2015

Mathematical modeling of pilot control response characteristics in studying the manual control tasks

The models of pilot response characteristics based on structural, optimal and neural network approaches are considered. The examples of their use in evaluating the flying qualities as well as influence of some task variables on a pilot—aircraft system are presented.

Pilot Adaptation to Different Classes of Haptic Aids in Tracking Tasks

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.

Transfer of Computer-Based Training to Simulated Driving In Older Adults

We evaluated the transfer of training on computer-based tasks that were specifically designed to tap cognitive abilities that are presumed to be used while driving, namely divided attention, visual monitoring and working memory. In particular, as older adults have been shown to suffer declines in cognitive abilities with advancing age, we asked whether some of these declines could be remediated with training. Using a driving simulator, participants’ driving performance was evaluated in several complex scenarios. Both computer-based training and driving tasks were presented individually and in combination with manual control tasks. We used regression analysis to examine the effects of the training on driving performance. Results revealed limited transfer of training from the computer-based training system to driving.

Effects of controlled element dynamics on human feedforward behavior in ramp-tracking tasks.

In real-life manual control tasks, human controllers are often required to follow a visible and predictable reference signal, enabling them to use feedforward control actions in conjunction with feedback actions that compensate for errors. Little is known about human control behavior in these situations. This paper investigates how humans adapt their feedforward control dynamics to the controlled element dynamics in a combined ramp-tracking and disturbance-rejection task. A human-in-the-loop experiment is performed with a pursuit display and vehicle-like controlled elements, ranging from a single integrator through second-order systems with a break frequency at either 3, 2, or 1 rad/s, to a double integrator. Because the potential benefits of feedforward control increase with steeper ramp segments in the target signal, three steepness levels are tested to investigate their possible effect on feedforward control with the various controlled elements. Analyses with four novel models of the operator, fitted to time-domain data, reveal feedforward control for all tested controlled elements and both (nonzero) tested levels of ramp steepness. For the range of controlled element dynamics investigated, it is found that humans adapt to these dynamics in their feedforward response, with a close to perfect inversion of the controlled element dynamics. No significant effects of ramp steepness on the feedforward model parameters are found.

The relationship between a child's postural stability and manual dexterity.

The neural systems responsible for postural control are separate from the neural substrates that underpin control of the hand. Nonetheless, postural control and eye-hand coordination are linked functionally. For example, a stable platform is required for precise manual control tasks (e.g. handwriting) and thus such skills often cannot develop until the child is able to sit or stand upright. This raises the question of the strength of the empirical relationship between measures of postural stability and manual motor control. We recorded objective computerised measures of postural stability in stance and manual control in sitting in a sample of school children (n = 278) aged 3–11 years in order to explore the extent to which measures of manual skill could be predicted by measures of postural stability. A strong correlation was found across the whole sample between separate measures of postural stability and manual control taken on different days. Following correction for age, a significant but modest correlation was found. Regression analysis with age correction revealed that postural stability accounted for between 1 and 10 % of the variance in manual performance, dependent on the specific manual task. These data reflect an interdependent functional relationship between manual control and postural stability development. Nevertheless, the relatively small proportion of the explained variance is consistent with the anatomically distinct neural architecture that exists for ‘gross’ and ‘fine’ motor control. These data justify the approach of motor batteries that provide separate assessments of postural stability and manual dexterity and have implications for therapeutic intervention in developmental disorders.

Differentiating functions of the lateral and medial prefrontal cortex in motor response inhibition

The right inferior frontal gyrus is generally considered a critical region for motor response inhibition. Recent studies, however, suggest that the role of this cortical area in response inhibition may be overstated and that the contributions of other aspects of the prefrontal cortex are often overlooked. The current study used optical imaging to identify regions of the prefrontal cortex beyond the right inferior frontal gyrus which may serve to support motor response inhibition. Forty-three right-handed healthy adults completed a manual Go/No-Go task while evoked oxygenation of the prefrontal cortex was measured using 16-channel functional near-infrared spectroscopy. During motor response inhibition, the right inferior frontal gyrus, and to a lesser extent the homologous contralateral region, showed increased activation relative to a baseline task. Conversely, the medial prefrontal cortex was significantly deactivated, and the extent of reduced activity in this region was associated with fewer errors on the response inhibition task. These findings suggest a more substantial role of the left inferior frontal gyrus in response inhibition and possibly a distinct function of the middle frontal gyrus subserving error detection on manual motor control tasks.

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.

Manual-Control Analysis Applied to the Money Supply Control Task

The recent procedure implemented by the Federal Reserve Board to control the money supply is formulated in the form of a tracking model as used in the study of manual-control tasks. Using this model, an analysis is made to determine the effect of monetary control on the fluctuations in economic output. The results indicate that monetary control can reduce the amplitude of fluctuations at frequencies near the region of historic business cycles. However, with significant time lags in the control loop, monetary control tends to increase the amplitude of the fluctuations at the higher frequencies. The study outlines how the investigator or student can use the tools developed in the field of manual-control analysis to study the nature of economic fluctuations and to examine different strategies for stabilization.

Modeling Wide-Frequency-Range Pilot Equalization for Control of Aircraft Pitch Dynamics

In continuous manual control tasks, human controllers adapt their control strategy to the dynamics of the controlled element. This compensation for the controlled-element dynamics is performed around the pilot–vehicle system crossover frequency, in order to obtain satisfactory performance of the combined pilot–vehicle system, but is also seen to extend to frequencies well above crossover. For a controlled element representing the linearized pitch dynamics of a small conventional jet aircraft, an extension to the models for pilot equalization described in the literature was found to be needed for the modeling of the adopted pilot equalization dynamics over a wide frequency range. Measured pilot describing functions revealed that pilots use a combination of low-frequency lag and high-frequency lead equalization to compensate for the characteristics of these typical aircraft pitch dynamics around the short-period mode. An additional high-frequency lead term in the pilot equalization transfer function was found to allow for the modeling of these adopted equalization dynamics over a wide frequency range, thereby also yielding a significant increase in the percentage of measured control inputs that is explained by the pilot model. Furthermore, for this controlled element the extended model for the equalization dynamics was found to be important for the interpretation of the changes in pilot control behavior that occur due to the presence of physical motion feedback.

Expertise-Based Performance Measures in a Virtual Training Environment

This paper introduces and validates quantitative performance measures for a rhythmic target-hitting task. These performance measures are derived from a detailed analysis of human performance during a month-long training experiment where participants learned to operate a 2-DOF haptic interface in a virtual environment to execute a manual control task. The motivation for the analysis presented in this paper is to determine measures of participant performance that capture the key skills of the task. This analysis of performance indicates that two quantitative measures—trajectory error and input frequency—capture the key skills of the target-hitting task, as the results show a strong correlation between the performance measures and the task objective of maximizing target hits. The performance trends were further explored by grouping the participants based on expertise and examining trends during training in terms of these measures. In future work, these measures will be used as inputs to a haptic guidance scheme that adjusts its control gains based on a real-time assessment of human performance of the task. Such guidance schemes will be incorporated into virtual training environments for humans to develop manual skills for domains such as surgery, physical therapy, and sports.