Compensatory Tracking Research Articles

Gaze transition entropy as a measure of attention allocation in a dynamic workspace involving automation

Real-world work environments require operators to perform multiple tasks with continual support from an automated system. Eye movement is often used as a surrogate measure of operator attention, yet conventional summary measures such as percent dwell time do not capture dynamic transitions of attention in complex visual workspace. This study analyzed eye movement data collected in a controlled a MATB-II task environment using gaze transition entropy analysis. In the study, human subjects performed a compensatory tracking task, a system monitoring task, and a communication task concurrently. The results indicate that both gaze transition entropy and stationary gaze entropy, measures of randomness in eye movements, decrease when the compensatory tracking task required more continuous monitoring. The findings imply that gaze transition entropy reflects attention allocation of operators performing dynamic operational tasks consistently.

Adapting to Imperfect Automation: The Impact of Experience on Dependence Behavior and Response Strategies

This study examined the impact of experience on individuals’ dependence behavior and response strategies when interacting with imperfect automation. 41 participants used an automated aid to complete a dual-task scenario comprising of a compensatory tracking task and a threat detection task. The entire experiment was divided into four quarters and multi-level models (MLM) were built to investigate the relationship between experience and the dependent variables. Results show that compliance and reliance behaviors and perfor- mance scores significantly increased as participants gained more experience with automation. In addition, as the experiment progressed, a significant number of participants adapted to the automation and resorted to an extreme use response strategy. The findings of this study suggest that automation response strategies are not static and most individual operators eventually follow or discard the automation. Understanding individual response strategies can support the development of individualized automation systems and improve operator training.

Vibrotactile mapping of the upper extremity: Absolute perceived intensity is location-dependent; perception of relative changes is not.

Vibrotactile sensation is an essential part of the sense of touch. In this study, the localized vibrotactile sensation of the arm-shoulder region was quantified in 10 able-bodied subjects. For this analysis, the six relevant dermatomes (C3-T2) and three segments-the lower arm, the upper arm, and the shoulder region were studied. For psychometric evaluation, tasks resulting in the quantification of sensation threshold, just noticeable difference, Weber fraction, and perception of dynamically changing vibrotactile stimuli were performed. We found that healthy subjects could reliably detect vibration in all tested regions at low amplitude (2-6% of the maximal amplitude of commonly used vibrotactors). The detection threshold was significantly lower in the lower arm than that in the shoulder, as well as ventral in comparison with the dorsal. There were no significant differences in Weber fraction (20%) detectable between the studied locations. A compensatory tracking task resulted in a significantly higher average rectified error in the shoulder than that in the upper arm, while delay and correlation coefficient showed no difference between the regions. Here, we presented a conclusive map of the vibrotactile sense of the healthy upper limb. These data give an overview of the sensory bandwidth that can be achieved with vibrotactile stimulation at the arm and may help in the design of vibrotactile feedback interfaces (displays) for the hand/arm/shoulder-region.

Dual-task interference while receiving information on a head mounted display and manual tracking with and without auditory warnings

BackgroundDual-task interference is a concern when users attempt to use head mounted displays (HMD) while performing seated manual control tasks. Auditory warnings of information displayed on the HMD may or may not assist users while multi-tasking. ObjectiveIn this study, we investigated the dual-task interference of words, to be remembered later, presented on a HMD and motor control in a manual tracking task. The word presentations were warned or not warned with auditory signals and the impact of audio warnings were examined. MethodsParticipants were required to perform five tasks: (1) a compensatory tracking task performed alone, (2) a word memory task performed alone, (3) a tracking and word memory task, (4) a word memory task with words preceded by audial signals, and (5) a tracking and word memory task with words preceded by audial signals. In addition, in the dual-tasks, half of the word presentations were paired with directions changes in the tracking task to test for immediate perceptual interference. ResultsThere were significant dual task costs for both mean tracking error and later word recall. Additionally, participants took significantly longer to respond to motion changes paired with word presentations than motion changes not paired with word presentations. However, the impact of auditory warnings on tracking performance was nuanced. ConclusionEven with an in field of view transparent HMD momentary and sustained cognitive dual-task interference remains. Reaction times are affected most in the worst case scenario, when task critical events occur at the same time as a text message. ApplicationThe use of HMDs in time critical manual control tasks (such as operating machinery) should be limited. The use of audial warnings to alert operators to information displayed on an HMD requires further research; it may disrupt appropriate or natural task ordering.

Probabilistic Perspective on Compensatory, Pursuit and Preview Manual Control

Mathematical human control models are widely used in tuning manual control systems and understanding human performance. Human behavior is commonly described using linear time-invariant models, averaging-out all non-linear and time-varying effects, which are gathered into the remnant. These models are limited in their capability to capture particular tracking strategies that an experienced subject may learn to use. In this paper, we consider manual control from a different perspective, namely through investigating the probability densities of the tracking error for different regions of the target signal amplitude. Results show that distinct strategies become apparent for compensatory, pursuit and preview tracking tasks. Effects of these strategies are often averaged-out by current models and can only be captured in situation-dependent models. Modeling this systematic human adaptation not captured in linear models could potentially lead to better model fits and explain/reduce part of the remnant.

Electrotactile and Vibrotactile Feedback Enable Similar Performance in Psychometric Tests and Closed-Loop Control.

Electro- and vibro-tactile stimulation are commonly employed for feedback in closed-loop human-machine interfacing. Although these feedback systems have been extensively investigated individually, they are rarely objectively compared. In this study, two state-of-the-art stimulation units (concentric electrode and C2-tactor) similar in shape and size were compared in psychometric and online control tests. The just noticeable difference and number of discriminable levels for intensity and frequency modulation were determined across values of carrier frequency and intensity, respectively. Next, subjects performed a compensatory tracking task, in which the feedback encoded the momentary tracking error. In the psychometric tests, intensity modulation outperformed frequency modulation and electrotactile stimulation enabled significantly higher resolution than vibrotactile stimulation, for the same carrier frequency. However, for the best-case settings (eletro-tactile: 100 Hz; vibro-tactile: 200 Hz), the two stimulation modalities were equivalent in the psychometric tests and in the online control tests, where the two stimulation methods resulted in similar correlation and deviation between the target and the generated trajectory. Time delay was slightly but significantly lower for the vibrotactile modality. Overall, the present assessment shows that despite psychometric differences between the two stimulation methods, they enable similar online control performance when parameters are optimally selected for each modality.

Predicting Human Control Adaptation from Statistical Variations in Tracking Error and Error Rate

This paper presents the results of an experiment that was performed to verify the ‘supervisory control algorithm’, a well-known model of human operator adaptation to changes in controlled element dynamics. This model proposes that human adaptive behavior is triggered once the magnitudes of the tracking error or error rate exceed certain decision region limits. In the experiment, a compensatory tracking task with a sudden transition in the controlled element dynamics, as also tested in other recent experiments, was performed by six skilled participants. In addition to performing the control task, participants had to indicate with a button press when they detected a controlled element transition. The results indicate that the published detection limits for the ‘supervisory control algorithm’ are too conservative for our experiment data, as measured detections could be related to error or error rate occurrences that exceeded 2-6 times their respective pre-transition standard deviations. The effectiveness of new detection limits proportional to these pre-transition standard deviations was tested. The best match to our experiment data was obtained with limits at 3.9σ, for which in only 9.38% and 11.5% of cases a (false positive) too early detection or a (false negative) missed detection occurred, respectively. Overall, these results demonstrate that human operator adaptation can indeed be effectively predicted from statistical variations in tracking error and error rate.

Training-Associated Superior Visuomotor Integration Performance in Elite Badminton Players after Adjusting for Cardiovascular Fitness

Badminton is recognized as the fastest racket sport in the world based on the speed of the birdie which can travel up to 426 km per hour. On the badminton court, players are not only required to track the moving badminton birdie (visual tracking and information integration) but also must anticipate the exact timing to hit it back (temporal estimation). However, the association of training experience related to visuomotor integration or temporal prediction ability remains unclear. In this study, we tested this hypothesis by examining the association between training experience and visuomotor performances after adjusting for age, education, and cardiovascular fitness levels. Twenty-eight professional badminton players were asked to perform a compensatory tracking task and a time/movement estimation task for measuring visuomotor integration and temporal prediction, respectively. Correlation analysis revealed a strong association between training experience and performance on visuomotor integration, indicating badminton training may be promoted to develop visuomotor integration ability. Furthermore, the regression model suggests training experience explains 32% of visuomotor integration performances. These behavioral findings suggest badminton training may facilitate the perceptual–cognitive performance related to visuomotor integration. Our findings highlight the potential training in visuomotor integration may apply to eye–hand coordination performance in badminton sport.

Usefulness of a psychomotor function test as a cognitive function scale for patients with schizophrenia: A pilot study

As cognitive dysfunction due to schizophrenia is strongly associated with patients' social rehabilitation, cognitive functions have been examined as a therapeutic target. Although the Brief Assessment of Cognition in Schizophrenia (BACS) has been used to evaluate cognitive function, it is difficult to administer in routine clinical practice due to its time-consuming nature. Therefore, a novel tool is needed to facilitate the assessment of cognitive function. In the present study, we examined whether cognitive function can be assessed effectively by testing psychomotor function in patients with schizophrenia. Test batteries consisting of choice reaction time (CRT) and compensatory tracking task (CTT) and the BACS were examined in 20 schizophrenic patients to evaluate the correlation between the scales by Pearson correlation coefficient. Of the test batteries, the CRT was significantly correlated with attention functions, a subtest of the BACS (r = -0.506, p = 0.023), and the CTT was strongly correlated with attention functions (r = -0.716, p < 0.001) and working memory (r = -0.633, p = 0.003). A multiple regression analysis was performed to clarify the association between psychomotor function tests and the total BACS score, and peripheral awareness task, a component of CTT, was independently associated with the total BACS score (β = -0.59, p = 0.004) with an R2 of 0.37. Thus, of the psychomotor function tests, the CRT and the CTT are highly useful in assessing cognitive functions in schizophrenic patients. However, no having large sample size in this study is a limitation.

Online Closed-Loop Control Using Tactile Feedback Delivered Through Surface and Subdermal Electrotactile Stimulation.

AimLimb loss is a dramatic event with a devastating impact on a person’s quality of life. Prostheses have been used to restore lost motor abilities and cosmetic appearance. Closing the loop between the prosthesis and the amputee by providing somatosensory feedback to the user might improve the performance, confidence of the amputee, and embodiment of the prosthesis. Recently, a minimally invasive method, in which the electrodes are placed subdermally, was presented and psychometrically evaluated. The present study aimed to assess the quality of online control with subdermal stimulation and compare it to that achieved using surface stimulation (common benchmark) as well as to investigate the impact of training on the two modalities.MethodsTen able-bodied subjects performed a PC-based compensatory tracking task. The subjects employed a joystick to track a predefined pseudorandom trajectory using feedback on the momentary tracking error, which was conveyed via surface and subdermal electrotactile stimulation. The tracking performance was evaluated using the correlation coefficient (CORR), root mean square error (RMSE), and time delay between reference and generated trajectories.ResultsBoth stimulation modalities resulted in good closed-loop control, and surface stimulation outperformed the subdermal approach. There was significant difference in CORR (86 vs 77%) and RMSE (0.23 vs 0.31) between surface and subdermal stimulation (all p < 0.05). The RMSE of the subdermal stimulation decreased significantly in the first few trials.ConclusionSubdermal stimulation is a viable method to provide tactile feedback. The quality of online control is, however, somewhat worse compared to that achieved using surface stimulation. Nevertheless, due to minimal invasiveness, compactness, and power efficiency, the subdermal interface could be an attractive solution for the functional application in sensate prostheses.

Parameter setting of pilot behavioral dynamic model in aircraft control loop

Subject of Research. The paper considers a flight control system for the longitudinal movement of an aircraft with a human-pilot in a closed loop. Computer simulation setting of the selected pilot behavioral model is carried out in the compensatory tracking mode. The parameters correspond to the optimal behavior of the pilot providing the best aircraft dynamic characteristics. Method. Padé approximation was used when creating a computer program for calculations.Frequency and optimal methods, and handling qualities scale were used for quality assessment of the control system dynamic properties. Main Results. Numerical values of the pilot behavior model parameters are found on the example of a normal aerodynamic scheme, in which the elevator serves as an element of the tail unit. The numerical values estimation of the pilot model parameters is performed. The simulation results are given. Practical Relevance. The proposed approach to the pilot behavior simulating process during piloting simplifies, accelerates, and reduces the cost of an aircraft test program. Software simulation can be used at the test stage and before tests on flight simulators and will give the possibility to identify unsatisfactory handling characteristics of the aircraft and its control system and quickly correct them.

Effects of Target Trajectory Bandwidth on Manual Control Behavior in Pursuit and Preview Tracking

The 1960s crossover model is widely applied to quantitatively predict a human controller's (HC's) manual control behavior. Unfortunately, the theory captures only compensatory tracking behavior and, as such, a limited range of real-world manual control tasks. This article finalizes recent advances in manual control theory toward more general pursuit and preview tracking tasks. It is quantified how HCs adapt their control behavior to a final crucial task variable: the target trajectory bandwidth. Beneficial adaptation strategies are first explored offline with computer simulations, using an extended crossover model theory for pursuit and preview tracking. The predictions are then verified with data from a human-in-the-loop experiment, in which participants tracked a target trajectory with bandwidths of 1.5, 2.5, and 4 rad/s, using compensatory, as well as pursuit and preview displays. In stark contrast to the crossover regression found in compensatory tasks, humans attenuate only their feedforward response when tracking higher-bandwidth trajectories in pursuit tasks, while their behavior is generally invariant in preview tasks. A full quantitative theory is now available to predict HC manual control behavior in tracking tasks, which includes HC adaptation to all key task variables.

Contrasting Age Effects on Complexity of Tracking Force and Force Fluctuations During Monorhythmic Contraction.

This study contrasted the stochastic force component between young and older adults, who performed pursuit tracking/compensatory tracking by exerting in-phase/antiphase forces to match a sinusoidal target. Tracking force was decomposed into the force component containing the target frequency and the nontarget force fluctuations (stochastic component). Older adults with inferior task performance had higher complexity (entropy across time; p = .005) in total force. For older adults, task errors were negatively correlated with force fluctuation complexity (pursuit tracking: r = -.527 to -.551; compensatory tracking: r = -.626 to -.750). Notwithstanding an age-related increase in total force complexity (p = .004), older adults exhibited lower complexity of the stochastic force component than young adults did (low frequency: p = .017; high frequency: p = .035). Those older adults with a higher complexity of stochastic force had better task performance due to the underlying use of a richer gradation strategy to compensate for impaired oscillatory control.

Not All Information Is Equal: Effects of Disclosing Different Types of Likelihood Information on Trust, Compliance and Reliance, and Task Performance in Human-Automation Teaming.

The study examines the effects of disclosing different types of likelihood information on human operators' trust in automation, their compliance and reliance behaviors, and the human-automation team performance. To facilitate appropriate trust in and dependence on automation, explicitly conveying the likelihood of automation success has been proposed as one solution. Empirical studies have been conducted to investigate the potential benefits of disclosing likelihood information in the form of automation reliability, (un)certainty, and confidence. Yet, results from these studies are rather mixed. We conducted a human-in-the-loop experiment with 60 participants using a simulated surveillance task. Each participant performed a compensatory tracking task and a threat detection task with the help of an imperfect automated threat detector. Three types of likelihood information were presented: overall likelihood information, predictive values, and hit and correct rejection rates. Participants' trust in automation, compliance and reliance behaviors, and task performance were measured. Human operators informed of the predictive values or the overall likelihood value, rather than the hit and correct rejection rates, relied on the decision aid more appropriately and obtained higher task scores. Not all likelihood information is equal in aiding human-automation team performance. Directly presenting the hit and correct rejection rates of an automated decision aid should be avoided. The findings can be applied to the design of automated decision aids.

Developing the Mathematical Model of a Pilot in a Control Manual Preview Tracking Task

This paper compares the pilot’s control actions and the pilot-aircraft system characteristics obtained in the compensatory tracking tasks, tracking with pursuit and preview. The model of the pilot’s control actions for all these cases is developed, and its adequacy to the experimental research results is investigated. By mathematical modeling the pilot-aircraft system, an optimal length of the corridor covering the planned trajectory is defined, which allows one to predict its further change. The result of modeling is compared with the results of experimental investigation on the simulator.

Utility of the Compensatory Tracking Task for Objective Differentiation of Hypersomnolence in Depression: A High-Density EEG Investigation.

Hypersomnolence is a common and debilitating symptom in mood disorders. However, objective differentiation of excessive daytime sleepiness (EDS) from non-EDS in depression has not yet been achieved. This study compared performance on the Compensatory Tracking Task (CTT) and concurrently-recorded high-density (hd)EEG theta power in 22 patients with major depressive disorder (MDD) and co-occurring EDS against 22 age- and sex-matched patients with MDD but no EDS, as well as 22 age- and sex-matched healthy controls. Though depressed hypersomnolent participants endorsed feeling sleepier than depressed non-hypersomnolent and healthy control participants prior to starting the CTT, no group differences in CTT performance were observed. Average hdEEG theta power was higher during periods of high error on the CTT compared to periods of low error, but did not differ between the groups. Though the CTT still holds promise as an objective neurobehavioral measure, these results do not indicate a capability to differentiate EDS from non-EDS in mood disorders.

Observers fail to detect that behavior is the control of perception: A computer demonstration of unintended writing.

Perceptual control theory (PCT) approaches the behavior of living systems as though it were a phenomenon of control and systematically assesses the variables that the individual controls using the test for the controlled variable (TCV). PCT may be supported by the minority because the majority of behavior scientists, like most people, can miss the phenomenon of control as it is occurring. An earlier paper reported three studies of a behavior that was known to be a process of control because it had been explicitly instructed. In each case, most observers did not detect the control. Our novel extension of this study used live observation of "actors" and "observers." We tested in pairs 164 participants randomly allocated to each role. The actors completed a two-dimensional compensatory tracking task. To keep a dot at the center of a circle, the movements of a computer mouse needed to vary as the inverse of a disturbance pattern that was an inverted form of the word "hello" in script. The trace of their mouse movements was displayed on the screen-writing the word "hello". As predicted, most observers missed the phenomenon of control; they inferred that the actor's instruction had been to write "hello", rather than to control the dot. In contrast, the actors reported that they had been keeping the dot in the circle and were unaware of having written the word. The TCV analyzes behavior by consistently identifying the controlled variable without relying on heuristic methods used by researchers that can be inaccurate. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Developing Active Manipulators in Aircraft Flight Control

Most haptic interfaces developed for aircraft control provide haptic support as an additional force on the control manipulator. This study revisits the active manipulator, which is a design concept that is different from but complementary to existing haptic interfaces. This control device sends the force that the pilot exerts on it to the aircraft while feeding back the aircraft rotational rate by means of its deflection angle. It is found that, in comparison with the conventional passive manipulator, the active manipulator greatly facilitates target following and disturbance rejection in compensatory tracking tasks. Furthermore, larger improvements in task performance are associated with higher forcing-function bandwidths. These findings are accounted for by the fact that the active manipulator changes the effective controlled-element dynamics into integratorlike dynamics while at the same time integrating disturbance rejection into the neuromuscular system. However, the high-frequency disturbances acting on the aircraft present in feedback about the aircraft state adversely affect the operational effectiveness of the active manipulator. Based on the experimental findings and results from the passivity theory, a lead–lag filter is designed and evaluated, which mitigates this effect without affecting task performance.

UKF-based Identification of Time-Varying Manual Control Behaviour

This paper describes a novel method for time-varying identification of Human Controller (HC) manual control parameters (called UKF-FPV), based on a steady-state (constant state covariance) Unscented Kalman Filter (UKF). This approach requires no a priori assumptions on the shape of HC parameter variations, which is a potential advantage over state-of-the-art methods such as the recently proposed MLE-APV approach, for which a sigmoid-shaped parameter variation is assumed. For a scenario where an HC performs a single-loop compensatory tracking task with time-varying controlled system dynamics, both identification methods are compared using Monte Carlo simulations and human-in-the-loop experiment data. Despite some lag in the HC parameter traces of UKF-FPV, the identification results and the HC model quality-of-fit obtained with both methods were found to match well for both the simulation and experiment data. For the experiment data, UKF-FPV even revealed clear "local" changes in HC parameters not captured by the MLE-APV approach, which confirms that HCs adapt unpredictably even in what are considered time-invariant conditions. Overall, the results show that an identification method that requires no a priori assumptions on HC parameter variations is of critical importance for a complete analysis of time-varying HC behaviour.

Analysis of Human Skill Development in Manual Ramp-Tracking Tasks

Human modelling approaches are typically limited to feedback-only, compensatory tracking tasks. Advances in system identification techniques allow us to consider more realistic tasks that involve feedforward and even precognitive control. In this paper we study the human development of a feedforward control response while learning to accurately follow a ramp-shaped target signal in the presence of a disturbance acting on the controlled element. An experiment was conducted in which two groups of eight subjects each tracked ramps of different steepnesses in a random or ordered fashion. In addition, ordered runs were followed by a ‘surprise’ run with a random ramp steepness. Results show that operators learn rapidly, continue to learn during the entire experiment, and can adapt very quickly to surprise situations. Experiments involving learning operators are challenging, as it is difficult to balance-out all experimental conditions and control for inevitable differences between (groups of) subjects.