Human Control Strategies Research Articles

Investigating the Influence of Varying Surface Conditions on Human Postural Control and Sensory Integration Strategies.

This study investigated the effects of different surface conditions on postural stability in response to unexpected perturbations. Thirty healthy adults underwent balance assessments on flat, incline ramp, balance pad, and balance pad on incline ramp surfaces. The center of pressure (COP) displacement in the mediolateral (ML) and anteroposterior (AP) directions, the velocity, and the area were measured. We found that the flat and ramp conditions resulted in significantly lower COP ML (F(3, 87) = 38.272, p < 0.001, ηp2 = 0.569) and AP displacements (F(3, 87) = 89.177, p < 0.001, ηp2 = 0.755), velocity (F(3, 87) = 89.177, p < 0.001, ηp2 = 0.755), and area (F(3, 87) = 52.659, p < 0.001, ηp2 = 0.645) compared to the balance pad and balance pad on ramp conditions (p < 0.05). The use of a balance pad, particularly on a ramp, significantly increased all the COP measurements, suggesting greater challenges to postural control. Through these findings, we demonstrate the adaptability and limitations of the human postural control system in response to varying surface conditions and perturbations.

Generalizability of foot placement control strategies during unperturbed and perturbed gait.

Control of foot placement is an essential strategy for maintaining balance during walking. During unperturbed, steady-state walking, foot placement can be accurately described as a linear function of the body's centre of mass (CoM) state at midstance. However, it is uncertain if this mapping from CoM state to foot placement generalizes to larger perturbations that could potentially cause falls. Recovery from these perturbations may require reactive control strategies not observed during unperturbed walking. Here, we used unpredictable changes in treadmill belt speed to assess the generalizability of foot placement mappings identified during unperturbed walking. We found that foot placement mappings generalized poorly from unperturbed to perturbed walking and differed for forward perturbation versus backward perturbation. We also used the singular value decomposition of the mapping matrix to reveal that people were more sensitive to backward versus forward perturbations. Together, these results indicate that a single linear mapping cannot describe the foot placement control during both forward and backward losses of balance induced by treadmill belt speed perturbations. Better characterization of human balance control strategies could improve our understanding of why different neuromotor disorders result in heightened fall risk and inform the design of controllers for balance-assisting devices.

Analysis of maintaining human maximal voluntary contraction control strategies through the power grip task in isometric contraction

Power grip force is used as a representative indicator of the ability of the human neuromuscular system. However, people maintain the power grip force via different control strategies depending on the visual feedback that shows the magnitude of the force, the magnitude of the target grip force, and external disturbance. In this study, we investigated the control strategy of maintaining the power grip force in an isometric contraction depending on these conditions by expressing the power grip force as a person’s Maximal Voluntary Contraction (MVC). The participants were asked to maintain the MVC for each condition. Experimental results showed that humans typically control their MVC constant abilities based on proprioception, and maintaining the target MVC becomes relatively difficult as the magnitude of the target MVC increases. In addition, through interactions between the external disturbance and the target MVC, the MVC error increases when the target MVC increases and an external disturbance is applied. When the MVC error reaches a certain level, the offset effect is expressed through visual feedback, helping to reduce the MVC error and maintain it smoothly, revealing a person’s MVC maintenance control strategy for each condition.

Elastic Resistance and Shoulder Movement Patterns: An Analysis of Reaching Tasks Based on Proprioception.

This study departs from the conventional research on horizontal plane reach movements by examining human motor control strategies in vertical plane elastic load reach movements conducted without visual feedback. Here, participants performed shoulder presses with elastic resistances at low, moderate, and high intensities without access to visual information about their hand position, relying exclusively on proprioceptive feedback and synchronizing their movements with a metronome set at a 3 s interval. The results revealed consistent performance symmetry across different intensities in terms of the reach speed (p = 0.254-0.736), return speed (p = 0.205-0.882), and movement distance (p = 0.480-0.919). This discovery underscores the human capacity to uphold bilateral symmetry in movement execution when relying solely on proprioception. Furthermore, this study observed an asymmetric velocity profile where the reach duration remained consistent irrespective of the load (1.15 s), whereas the return duration increased with higher loads (1.39 s-1.45 s). These findings suggest that, in the absence of visual feedback, the asymmetric velocity profile does not result from the execution of the action but rather represents a deliberate deceleration post-reach aimed at achieving the target position as generated by the brain's internal model. These findings hold significant implications for interpreting rehabilitation approaches under settings devoid of visual feedback.

Pick the Right Co-Worker: Online Assessment of Cognitive Ergonomics in Human–Robot Collaborative Assembly

Human-robot collaborative assembly systems enhance the efficiency and productivity of the workplace but may increase the workers&#x2019; cognitive demand. This paper proposes an online and quantitative framework to assess the cognitive workload induced by the interaction with a co-worker, either a human operator or an industrial collaborative robot with different control strategies. The approach monitors the operator&#x2019;s attention distribution and upper-body kinematics benefiting from the input images of a low-cost stereo camera and cutting-edge artificial intelligence algorithms (i.e. head pose estimation and skeleton tracking). Three experimental scenarios with variations in workstation features and interaction modalities were designed to test the performance of our online method against state-of-the-art offline measurements. Results proved that our vision-based cognitive load assessment has the potential to be integrated into the new generation of collaborative robotic technologies. The latter would enable human cognitive state monitoring and robot control strategy adaptation for improving human comfort, ergonomics, and trust in automation.

Bioinspired preactivation reflex increases robustness of walking on rough terrain

Walking on unknown and rough terrain is challenging for (bipedal) robots, while humans naturally cope with perturbations. Therefore, human strategies serve as an excellent inspiration to improve the robustness of robotic systems. Neuromusculoskeletal (NMS) models provide the necessary interface for the validation and transfer of human control strategies. Reflexes play a crucial part during normal locomotion and especially in the face of perturbations, and provide a simple, transferable, and bio-inspired control scheme. Current reflex-based NMS models are not robust to unexpected perturbations. Therefore, in this work, we propose a bio-inspired improvement of a widely used NMS walking model. In humans, different muscles show an increase in activation in anticipation of the landing at the end of the swing phase. This preactivation is not integrated in the used reflex-based walking model. We integrate this activation by adding an additional feedback loop and show that the landing is adapted and the robustness to unexpected step-down perturbations is markedly improved (from 3 to 10 cm). Scrutinizing the effect, we find that the stabilizing effect is caused by changed knee kinematics. Preactivation, therefore, acts as an accommodation strategy to cope with unexpected step-down perturbations, not requiring any detection of the perturbation. Our results indicate that such preactivation can potentially enable a bipedal system to react adequately to upcoming unexpected perturbations and is hence an effective adaptation of reflexes to cope with rough terrain. Preactivation can be ported to robots by leveraging the reflex-control scheme and improves the robustness to step-down perturbation without the need to detect the perturbation. Alternatively, the stabilizing mechanism can also be added in an anticipatory fashion by applying an additional knee torque to the contralateral knee.

A Serious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality.

The study of visuomotor adaptation (VMA) capabilities has been encompassed in various experimental protocols aimed at investigating human motor control strategies and/or cognitive functions. VMA-oriented frameworks can have clinical applications, primarily in the investigation and assessment of neuromotor impairments caused by conditions such as Parkinson's disease or post-stroke, which affect the lives of tens of thousands of people worldwide. Therefore, they can enhance the understanding of the specific mechanisms of such neuromotor disorders, thus being a potential biomarker for recovery, with the aim of being integrated with conventional rehabilitative programs. Virtual Reality (VR) can be entailed in a framework targeting VMA since it allows the development of visual perturbations in a more customizable and realistic way. Moreover, as has been demonstrated in previous works, a serious game (SG) can further increase engagement thanks to the use of full-body embodied avatars. Most studies implementing VMA frameworks have focused on upper limb tasks and have utilized a cursor as visual feedback for the user. Hence, there is a paucity in the literature about VMA-oriented frameworks targeting locomotion tasks. In this article, the authors present the design, development, and testing of an SG-based framework that addresses VMA in a locomotion activity by controlling a full-body moving avatar in a custom VR environment. This workflow includes a set of metrics to quantitatively assess the participants' performance. Thirteen healthy children were recruited to evaluate the framework. Several quantitative comparisons and analyses were run to validate the different types of introduced visuomotor perturbations and to evaluate the ability of the proposed metrics to describe the difficulty caused by such perturbations. During the experimental sessions, it emerged that the system is safe, easy to use, and practical in a clinical setting. Despite the limited sample size, which represents the main limitation of the study and can be compensated for with future recruitment, the authors claim the potential of this framework as a useful instrument for quantitatively assessing either motor or cognitive impairments. The proposed feature-based approach gives several objective parameters as additional biomarkers that can integrate the conventional clinical scores. Future studies might investigate the relation between the proposed biomarkers and the clinical scores for specific disorders such as Parkinson's disease and cerebral palsy.

Dynamics and optimal control of a Zika model with sexual and vertical transmissions.

A new transmission model of Zika virus with three transmission routes including human transmission by mosquito bites, sexual transmission between males and females and vertical transmission is established. The basic reproduction number $ R_{0} $ is derived. When $ R_{0} < 1 $, it is proved that the disease-free equilibrium is globally stable. Furthermore, the optimal control and mitigation methods for transmission of Zika virus are deduced and explored. The MCMC method is used to estimate the parameters and the reasons for the deviation between the actual infection cases and the simulated data are discussed. In addition, different strategies for controlling the spread of Zika virus are simulated and studied. The combination of mosquito control strategies and internal human control strategies is the most effective way in reducing the risk of Zika virus infection.

Structural design and stiffness matching control of bionic variable stiffness joint for human–robot collaboration

The physical compliance of interaction is an important requirement for safe and efficient collaboration between robots and humans, and the realization of human–robot compliance requires robot joints with variable stiffness similar to those of human joints. In this study, based on the tissue structure and driving principle of the human arm muscle ligament, a robot joint with variable stiffness is designed, consisting of an elastic belt and serial elastic actuator in parallel. The variable stiffness of the joint is realized by adjusting the tension length of the elastic belt. Surface electromyography (sEMG) signals of the human arm are used as the characterization quantity of joint stiffness to establish the pseudo-stiffness model of the elbow joint. The stiffness of the robot joints is adjusted in real-time to match the human arm stiffness based on the changes in sEMG signals of the human arm during operation. Real-time compliant interaction of human–robot collaboration is realized based on an end stiffness matching strategy. Additionally, to verify the effectiveness of the human joint stiffness matching-based compliance control strategy, a human–robot cooperative lifting experiment was designed. The bionic variable stiffness joint shows good stiffness adjustment, and the human–robot joint stiffness matching strategy based on human sEMG signals can improve the effectiveness and comfort of human–robot collaboration.

Task-Dependent Adaptations in Closed-Loop Motor Control Based on Electrotactile Feedback

Humans systematically adapt their strategies for closed-loop control based on visual feedback according to the dynamics of the system. Tactile feedback is a key element in many human–machine interfaces, but it is not known if and how well human control adapts to changes in system dynamics when information about the system state is provided using this type of feedback. In this study, 11 participants tracked a pseudorandom trajectory with a virtual, position- or velocity-controlled plant using a joystick. Visual or electrotactile feedback provided the instantaneous error between the target and generated trajectory. Frequency-domain system identification indicated that human control adapted in similar ways to the different control modes (i.e., position/velocity control) for both feedback modalities. For the plant dynamics modeled as gain and integrator, the human controller behaved as a low-pass filter and gain, respectively (under the assumption of quasi-linear behavior). However, while tracking quality was largely similar for both control modes with visual feedback, velocity control enabled substantially worse control with electrotactile feedback compared to position control. Furthermore, for both control modes, the crossover frequency of open-loop transfer functions was lower for electrotactile feedback (0.9 and 1.1 rad/s) than for visual feedback (1.5 and 1.7 rad/s) indicating limited control bandwidth. To summarize, closed-loop control based on electrotactile feedback enables natural adaptations in human control strategy, which is encouraging for tactile feedback-controlled human–machine interfaces, but the lower control bandwidth and lower tracking quality with velocity control may impose functional limitations.

Asynchronous Intermittent Regulation of Human Arm Movement with Markovian Jumping Parameters.

In this paper, the regulation stability problem of the human arm continuous movement is investigated based on Markovian jumping parameters. In particular, the intermittent control mechanism is adopted in the arm movement regulation procedure to model the human intermittent motor control strategy. Furthermore, by taking into account the Markovian jumping parameters with different modes, the asynchronous regulation issue is proposed to model mode mismatch between the motor control and arm movement. On the basis of model transformation, sufficient stability conditions are established during the arm movements, and the desired regulation gain can be obtained by the convex optimization method. In the end, an illustrative example is presented to show the applicability and effectiveness of our developed model and optimized regulation approach.

A user-friendly automatic toolbox for hand kinematic analysis, clinical assessment and postural synergies extraction.

The clinical assessment of the human hand is typically conducted through questionnaires or tests that include objective (e.g., time) and subjective (e.g., grasp quality) outcome measures. However, there are other important indicators that should be considered to quantify grasp and movement quality in addition to the time needed by a subject to execute a task, and this is essential for human and artificial hands that attempt to replicate the human hand properties. The correct estimation of hand kinematics is fundamental for computing these indicators with high fidelity, and a technical background is typically required to perform this analysis. In addition, to understand human motor control strategies as well as to replicate them on artificial devices, postural synergies were widely explored in recent years. Synergies should be analyzed not only to investigate possible modifications due to musculoskeletal and/or neuromuscular disorders, but also to test biomimetic hands. The aim of this work is to present an open source toolbox to perform all-in-one kinematic analysis and clinical assessment of the hand, as well as to perform postural synergies extraction. In the example provided in this work, the tool takes as input the position of 28 retroreflective markers with a diameter of 6mm, positioned on specific anatomical landmarks of the hand and recorded with an optoelectronic motion capture system, and automatically performs 1) hand kinematic analysis (i.e., computation of 23 joint angles); 2) clinical assessment, by computing indicators that allow quantifying movement efficiency (Peak Grip Aperture), smoothness (Normalized Dimensionless Jerk Grasp Aperture) and speed (Peak Velocity of Grasp Aperture), planning capabilities (Time to Peak Grip Aperture), spatial posture (Wrist and Finger Joint Angles) and grasp stability (Posture of Hand Finger Joints), and 3) postural synergies extraction and analysis through the Pareto, Scree and Loadings plots. Two examples are described to demonstrate the applicability of the toolbox: the first one aiming at performing a clinical assessment of a volunteer and the second one aiming at extracting and analyzing the volunteer's postural synergies. The tool allows calculating joint angles with high accuracy (reconstruction errors below 4mm and 3.2mm for the fingers and wrist respectively) and automatically performing clinical assessment and postural synergies extraction. Results can be visually inspected, and data can be saved for any desired post processing analysis. Custom-made protocols to extract joint angles, based on different markersets, could be also integrated in the toolbox. The tool can be easily exploitable in clinical contexts, as it does not require any particular technical knowledge to be used, as confirmed by the usability evaluation conducted (perceived usability = 94.2 ± 5.4). In addition, it can be integrated with the SynGrasp toolbox to perform grasp analysis of underactuated virtual hands based on postural synergies.

TgMIF Promotes Hepatocyte Pyroptosis and Recruitment of Proinflammatory Macrophages During Severe Liver Injury in Acute Toxoplasmosis.

Liver injury is a common complication during infection of Toxoplasma gondii. However, the Toxoplasma effector proteins involved remain unknown. Herein, we identified that T. gondii macrophage migration inhibitory factor (TgMIF) is a critical pathogenic factor of liver injury in acute toxoplasmosis mouse model induced by a less virulent strain, which is widely prevalent in humans. We show that TgMIF is a novel activator of nucleotide-binding oligomerization domain-like receptor pyrin domain containing 3 (NLRP3) inflammasome in hepatocytes, resulting in subsequent pyroptosis. Furthermore, T. gondii promotes the TgMIF-dependent infiltration of Ly6Chi proinflammatory macrophages to release cytokines, leading to hepatocyte apoptosis. Although the intense inflammation induced by TgMIF inhibits the proliferation of intracellular parasites, it results in fatal liver damage. In contrast, parasites with TgMIF gene deletion significantly alleviate liver injury and prolong mice survival. The discovery of novel Toxoplasma virulence factor may expedite the development of human toxoplasmosis control strategies.

Human Control Strategy: Abstraction, Verification, and Replication [25 Years Ago

In this issue, “25 Years Ago” revisits the article “Human Control Strategy: Abstraction, Verification, and Replication,” by Michael C. Nechyba and Yangsheng Xu in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Control Systems Magazine</i> , vol. 17, no. 5, pp. 48Ð61, 1997. Below is an excerpt from the article.

Dermal exposure to synthetic musks: Human health risk assessment, mechanism, and control strategy

Synthetic musks (SMs) have been widely used as odor additives in personal care products (PCPs). Dermal exposure to SMs is the main pathway of the accumulation of these chemicals in human kerateins and poses potential health risks. In this study, in silico methods were established to reduce the human health risk of SMs from dermal exposure by investigating the risk mechanisms, designing lower bioaccumulation ability SMs and suggesting proper PCP ingredients using molecular docking, molecular dynamics simulation, and quantitative structure-activity relationship (QSAR) models. The binding energy, a parameter reflecting the binding ability of SMs and human keratin protein (4ZRY), was used as the indicator to assess the human health risk of SMs. According to the mechanism analysis, total energy was found as the most influential molecular structural feature influencing the bioaccumulation ability of a SM, and as one of the main factors influencing the function (i.e., odor sensitivity) of an SM. The 3D-QSAR models were constructed to control the human health risk of SMs by designing lower-risk SMs derivatives. The phantolide (PHAN)− 58 was determined to be the optimum SM derivative with lower bioaccumulation ability (reduced 17.25%) and improved odor sensitivity (increased 7.91%). A further reduction of bioaccumulation ability of PHAN-58 was found when adding proper body wash ingredients (i.e., alkyl ethoxylate sulfate (AES), dimethyloldimethyl (DMDM), EDTA-Na4, ethylene glycol distearate (EGDS), hydroxyethyl cellulose (HEC), lemon yellow and octyl glucose), leading to a significant reduction of the bioaccumulation ability (42.27%) compared with that of PHAN. Results demonstrated that the proposed theoretical mechanism and control strategies could effectively reduce the human health risk of SMs from dermal exposure.

Human Control Model Estimation in Physical Human-Machine Interaction: A Survey.

The study of human–machine interaction as a unique control system was one of the first research interests in the engineering field, with almost a century having passed since the first works appeared in this area. At the same time, it is a crucial aspect of the most recent technological developments made in application fields such as collaborative robotics and artificial intelligence. Learning the processes and dynamics underlying human control strategies when interacting with controlled elements or objects of a different nature has been the subject of research in neuroscience, aerospace, robotics, and artificial intelligence. The cross-domain nature of this field of study can cause difficulties in finding a guiding line that links motor control theory, modelling approaches in physiological control systems, and identifying human–machine general control models in manipulative tasks. The discussed models have varying levels of complexity, from the first quasi-linear model in the frequency domain to the successive optimal control model. These models include detailed descriptions of physiologic subsystems and biomechanics. The motivation behind this work is to provide a complete view of the linear models that could be easily handled both in the time domain and in the frequency domain by using a well-established methodology in the classical linear systems and control theory.

Sensing small interaction forces through proprioception

Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human–robot interaction (pHRI). In physical human–human interaction (pHHI), small interaction forces are known to convey their intent between the partners for effective motor communication. The aim of this work is to investigate what affects the human’s sensitivity to the externally applied interaction forces. The hypothesis is that one way the small interaction forces are sensed is through the movement of the arm and the resulting proprioceptive signals. A pHRI setup was used to provide small interaction forces to the hand of seated participants in one of four directions, while the participants were asked to identify the direction of the push while blindfolded. The result shows that participants’ ability to correctly report the direction of the interaction force was lower with low interaction force as well as with high muscle contraction. The sensitivity to the interaction force direction increased with the radial displacement of the participant’s hand from the initial position: the further they moved the more correct their responses were. It was also observed that the estimated stiffness of the arm varies with the level of muscle contraction and robot interaction force.

Frequency-dependent force direction elucidates neural control of balance

BackgroundMaintaining upright posture is an unstable task that requires sophisticated neuro-muscular control. Humans use foot–ground interaction forces, characterized by point of application, magnitude, and direction to manage body accelerations. When analyzing the directions of the ground reaction forces of standing humans in the frequency domain, previous work found a consistent pattern in different frequency bands. To test whether this frequency-dependent behavior provided a distinctive signature of neural control or was a necessary consequence of biomechanics, this study simulated quiet standing and compared the results with human subject data.MethodsAiming to develop the simplest competent and neuromechanically justifiable dynamic model that could account for the pattern observed across multiple subjects, we first explored the minimum number of degrees of freedom required for the model. Then, we applied a well-established optimal control method that was parameterized to maximize physiologically-relevant insight to stabilize the balancing model.ResultsIf a standing human was modeled as a single inverted pendulum, no controller could reproduce the experimentally observed pattern. The simplest competent model that approximated a standing human was a double inverted pendulum with torque-actuated ankle and hip joints. A range of controller parameters could stabilize this model and reproduce the general trend observed in experimental data; this result seems to indicate a biomechanical constraint and not a consequence of control. However, details of the frequency-dependent pattern varied substantially across tested control parameter values. The set of parameters that best reproduced the human experimental results suggests that the control strategy employed by human subjects to maintain quiet standing was best described by minimal control effort with an emphasis on ankle torque.ConclusionsThe findings suggest that the frequency-dependent pattern of ground reaction forces observed in quiet standing conveys quantitative information about human control strategies. This study’s method might be extended to investigate human neural control strategies in different contexts of balance, such as with an assistive device or in neurologically impaired subjects.

Mediterranean Spotted Fever: Current Knowledge and Recent Advances.

Mediterranean spotted fever (MSF) is an emerging tick-borne rickettsiosis of the spotted fever group (SFG), endemic in the Mediterranean basin. By virtue of technological innovations in molecular genetics, it has been determined that the causative agent of MSF is Rickettsia conorii subspecies conorii. The arthropod vector of this bacterium is the brown dog tick Rhipicephalus sanguineus. The true nature of the reservoir of R. conorii conorii has not been completely deciphered yet, although many authors theorize that the canine population, other mammals, and the ticks themselves could potentially contribute as reservoirs. Typical symptoms of MSF include fever, maculopapular rash, and a characteristic eschar (“tache noire”). Atypical clinical features and severe multi-organ complications may also be present. All of these manifestations arise from the disseminated infection of the endothelium by R. conorii conorii. Several methods exist for the diagnosis of MSF. Serological tests are widely used and molecular techniques have become increasingly available. Doxycycline remains the treatment of choice, while preventive measures are focused on modification of human behavior and vector control strategies. The purpose of this review is to summarize the current knowledge on the epidemiology, pathogenesis, clinical features, diagnosis, and treatment of MSF.

Public health implication towards rabies elimination in Sri Lanka: A systematic review

Background/ObjectivesSri Lanka has been targeted zero rabies by the end of 2025. Towards the elimination, the country needs more effective, evidence-based strategies and efforts to achieve its ultimate goal. Therefore, we conducted a systematic review of scientific literatures and data to assess current human and animal rabies control and prevention strategies in Sri Lanka. MethodsWe compiled documents regarding current and previous rabies control and prevention activities implemented in the entire country of Sri Lanka. The documents included published literatures issued between 1946 and 2020 from both online databases and university library in Sri Lanka. All the collected documents were screened based on the PRISMA statement and categorized into several types of rabies control and prevention strategies. Official reports including epidemiological data in Sri Lanka were also filed in order to analyze the current trend of rabies control and prevention in the nation. ResultsAs of end December 2020, we found 119 scientific literatures regarding rabies control and prevention in Sri Lanka. Human rabies deaths in Sri Lanka have been reduced for the last half century by successful implementation of mass dog vaccination, animal birth control and awareness raising activities. However, the country is still facing on sporadic rabies cases, limited dog vaccination coverage and insufficient dog population management in the district level. Despite the nationwide standard of dog to human ratio of 1:8, there are huge disparities or unknown of dog ecology in regions. Awareness raising including has been enhancing for both general public and school children. Surveillance system is poorly operated so that simultaneous data analysis for decision-making is impractical. ConclusionsIn order to achieve nationwide rabies elimination, it is highly recommended to implement more effective rabies control and prevention activities and build adequate scientific evidences.