Kinematic Level Research Articles

Interpretable classification for multivariate gait analysis of cerebral palsy

BackgroundThe Gross Motor Function Classification System (GMFCS) is a widely used tool for assessing the mobility of people with Cerebral Palsy (CP). It classifies patients into different levels based on their gross motor function and its level is typically determined through visual evaluation by a trained expert. Although gait analysis is commonly used in CP research, the functional aspects of gait patterns has yet to be fully exploited. By utilizing the gait patterns to predict GMFCS, we can gain a more comprehensive understanding of how CP affects mobility and develop more effective interventions for CP patients.ResultIn this study, we propose a multivariate functional classification method to examine the relationship between kinematic gait measures and GMFCS levels in both normal individuals and CP patients with varying GMFCS levels. A sparse linear functional discrimination framework is utilized to achieve an interpretable prediction model. The method is generalized to handle multivariate functional data and multi-class classification. Our method offers competitive or improved prediction accuracy compared to state-of-the-art functional classification approaches and provides interpretable discriminant functions that can characterize the kinesiological progression of gait corresponding to higher GMFCS levels.ConclusionWe generalize the sparse functional linear discrimination framework to achieve interpretable classification of GMFCS levels using kinematic gait measures. The findings of this research will aid clinicians in diagnosing CP and assigning appropriate GMFCS levels in a more consistent, systematic, and scientifically supported manner.

Lessons learned from matching 3D DEM and experiments at macro, meso and fabric scales for triaxial compression tests on lentils

A series of discrete element method (DEM) triaxial compression simulations on specimens of an anisometric granular material starting from distinct initial fabric anisotropy states are conducted and compared with physical experiments on lentils at different scales, assisted by operando X-ray tomography measurements. A quantitative reproduction of the group of experimental results is achieved by appropriate idealization and determination of particle shape, boundary conditions, contact parameters, and initial state. The reliability of DEM in quantitative representation of macro scale stress–strain response, meso scale strain localization, and micro scale fabric anisotropy evolution is thus comprehensively validated against measurements from physical experiments, which is a step forward from comparisons only at the macro or particle kinematics level. Several key factors that govern realistic DEM simulations are also identified. The friction coefficient between particles during specimen generation, particle shape, and specimen preparation method can significantly affect the initial state of DEM specimens. Differences in initial state at macro and micro scales and boundary conditions can strongly influence the stress–strain response. However, the evolution of fabric anisotropy appears to be insensitive to changes in initial state and boundary conditions.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and people with early Parkinson's disease: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study.

Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson's Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Hierarchical control of manipulator with null-space compliance at the kinematic level

This article proposes a hierarchical control framework with null-space impedance at the kinematic level. The proposed framework aims to overcome the limitations of the prior methods for null-space compliance which rely on the dynamics of the manipulator. Two task-space control laws and a null-space control law at the kinematic level are designed to improve task-space errors and exhibit compliant joint motion behavior. The task-space’s end-effector force tracking uses an adaptive variable impedance control approach to enhance tracking performance. Experimental results conducted on a 7R manipulator demonstrate that the proposed control framework is capable of improving task performance when interaction forces act on the manipulator body.

Multi-modal synergistic quantitative analysis and rehabilitation assessment of lower limbs for exoskeleton

In response to the problem that the traditional lower limb rehabilitation scale assessment method is time-consuming and difficult to use in exoskeleton rehabilitation training, this paper proposes a quantitative assessment method for lower limb walking ability based on lower limb exoskeleton robot training with multimodal synergistic information fusion. The method significantly improves the efficiency and reliability of the rehabilitation assessment process by introducing quantitative synergistic indicators fusing electrophysiological and kinematic level information. First, electromyographic and kinematic data of the lower extremity were collected from subjects trained to walk wearing an exoskeleton. Then, based on muscle synergy theory, a synergistic quantification algorithm was used to construct synergistic index features of electromyography and kinematics. Finally, the electrophysiological and kinematic level information was fused to build a modal feature fusion model and output the lower limb motor function score. The experimental results showed that the correlation coefficients of the constructed synergistic features of electromyography and kinematics with the clinical scale were 0.799 and 0.825, respectively. The results of the fused synergistic features in the K-nearest neighbor (KNN) model yielded higher correlation coefficients ( r = 0.921, P < 0.01). This method can modify the rehabilitation training mode of the exoskeleton robot according to the assessment results, which provides a basis for the synchronized assessment-training mode of "human in the loop" and provides a potential method for remote rehabilitation training and assessment of the lower extremity.

A Deep Reinforcement Learning-Based Path-Following Control Scheme for an Uncertain Under-Actuated Autonomous Marine Vehicle

In this article, a deep reinforcement learning-based path-following control scheme is established for an under-actuated autonomous marine vehicle (AMV) in the presence of model uncertainties and unknown marine environment disturbances is presented. By virtue of light-of-sight guidance, a surge-heading joint guidance method is developed within the kinematic level, thereby enabling the AMV to follow the desired path accurately. Within the dynamic level, model uncertainties and time-varying environment disturbances are taken into account, and the reinforcement learning control method using the twin-delay deep deterministic policy gradient (TD3) is developed for the under-actuated vehicle, where path-following actions are generated via the state space and hybrid rewards. Additionally, actor-critic networks are developed using the long-short time memory (LSTM) network, and the vehicle can successfully make a decision by the aid of historical states, thus enhancing the convergence rate of dynamic controllers. Simulation results and comprehensive comparisons on a prototype AMV demonstrate the remarkable effectiveness and superiority of the proposed LSTM-TD3-based path-following control scheme.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and early Parkinson's disease patients: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. Clinical Trial Registration: ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Safety-Certified Constrained Control of Maritime Autonomous Surface Ships for Automatic Berthing

The berthing of maritime autonomous surface ships (MASSs) is a challenging operation even for an experienced captain due to the required complicated maneuvering at low speeds in a constrained water space. This paper addresses safety-aware automatic berthing of MASSs moving in a constrained water region with stationary and moving obstacles. A safety-critical constrained anti-disturbance control method is proposed for the automatic berthing of MASSs subject to velocity constraints, input constraints, and collision-avoidance constraints, as well as ocean disturbances. At the kinematic level, desired linear velocities and yaw rate are prescribed by incorporating a line-of-sight guidance scheme to achieve position-heading stabilization. At the kinetic level, an anti-disturbance kinetic control law is designed based on an extended state observer. Through converting the input constraints to velocity constraints on guidance signals, the safety-guidance signals are obtained by solving a quadratic programming problem subject to the state, input, and collision-avoidance constraints. It is proven that an MASS controlled by using the proposed method is input-to-state safe in the presence of ocean disturbances. Simulation results are elaborated to substantiate the efficacy of the proposed safety-certified control law for the automatic berthing of an MASS subject to physical constraints and environmental disturbances.

Compensatory articulatory mechanisms preserve intelligibility in prodromal Parkinson's disease

IntroductionDysarthria is highly prevalent in patients with Parkinson's disease (PD) and speech changes have already been detected in patients with prodromal PD on the acoustic level. However, the present study directly tracks underlying articulatory movements with electromagnetic articulography to investigate early speech alterations on the kinematic level in isolated REM sleep behavior disorder (iRBD) and compares them to PD and control speakers. MethodsKinematic data of 23 control speakers, 22 speakers with iRBD, and 23 speakers with PD were collected. Amplitude, duration, and average speed of lower lip, tongue tip, and tongue body movements were analyzed. Naive listeners rated the intelligibility of all speakers. ResultsPatients with iRBD produced tongue tip and tongue body movements that were larger in amplitude and longer in duration compared to control speakers, while remaining intelligible. Compared to patients with iRBD, patients with PD had smaller, longer and slower tongue tip and lower lip movements, accompanied by lower intelligibility. Thus, the data indicate that the lingual system is already affected in prodromal PD. Furthermore, lower lip and especially tongue tip movements slow down and speech intelligibility decreases if motor impairment is more pronounced. ConclusionPatients with iRBD adjust articulatory patterns to counteract incipient motor detriment on speech to maintain their intelligibility level.

Revisiting cosmography via Gaussian process

In this paper, we revisit the kinematical state of our Universe via the cosmographic approach by using Gaussian process, where the minimum assumption is the cosmological principle, i.e. the Friedmann–Lemaître–Robertson–Walker metric. A obviously distinguished feature is that these cosmography parameters are free of any gravity theories and cosmological models. And Gaussian process is independent of any specific parameterized forms of function. Thus by transformations these generic cosmography parameters can be used to constrain a cosmological model and dark energy model directly at the kinematics level of our Universe. As a result, a series of cosmography parameters up to the fifth oder, i.e. the Hubble parameter H(z), the deceleration parameter q(z), the jerk parameter j(z), the snap parameter s(z) and the lerk parameter l(z), evolve with respect to the redshift z are reconstructed from the cosmic observations which include the recently released Pantheon+ SN Ia samples and the observational Hubble data H(z), also dubbed as cosmic chronometers. The result shows the transition redshift from a decelerated expansion to an accelerated expansion z_t=0.652^{+0.054}_{-0.043} which is consistent with the previous results.

Motor Synergies in the Control System of Complex Sports Balance Postures

The paper presents the motor synergies’ structure at the muscular and kinematic levels of their study during performing various sports balance postures. The features of the formation and modification of synergetic modules depending on the motor task are considered. An attempt is made to combine some computational aspects applied according of various concepts of synergetic control. The tools for identifying and analyzing synergy parameters included regression analysis and data factorization methods. It has been established that differing in biomechanical structure balance exercises can be realized using common patterns of kinematic synergies spatial organization, however, at the muscular level, the existence of common spatial activation profiles is not obvious. The presence of several different time patterns of synergy activation in the structure of each balance exercise has been revealed, which may be associated with various motor control strategies in the central nervous system. The structure of kinematic synergies may be influenced by artificial degrees of freedom restriction, unrelated to central control processes. It is shown that the inclusion of the concept of “variables’ area” in the motor control modular organization theory contributes to the convergence of existing motor control concepts based on synergy principle.

Production of Cumulative Pions and Percolation of Strings

Production of pions in high-energy collisions with nuclei in the kinematics prohibited for free nucleons (“cumulative pions”) is studied in the fusing color string model. The model describes the so-called direct mechanism for cumulative production. The other (spectator) mechanism dominates in production of cumulative protons, and is suppressed for pions. In the model, cumulative pions are generated by string fusion, which raises the maximal energy of produced partons above the level of the free nucleon kinematics. Momentum and multiplicity sum rules are used to determine the spectra in the deep fragmentation region. Predicted spectra of cumulative pions exponentially fall with the scaling variable x in the interval 1&lt;x&lt;3 with a slope between 5.1 and 5.6, which agrees well with the raw data obtained in the recent experiment at RHIC involving Cu–Au collisioins. However, the agreement is worse for the so-called unfolded data, presumably taking into account corrections due to the experimental setup and having rather a power-like form.

Neuromuscular assessment of force development, postural, and gait performance under cognitive-motor dual-tasking in healthy older adults and early Parkinson's disease patients: Study protocol for a cross-sectional Mobile Brain/Body Imaging (MoBI) study

Background: Neuromuscular dysfunction is common in older adults and more pronounced in neurodegenerative diseases. In Parkinson's disease (PD), a complex set of factors often prevents the effective performance of activities of daily living that require intact and simultaneous performance of the motor and cognitive tasks. Methods: The cross-sectional study includes a multifactorial mixed-measure design. Between-subject factor grouping the sample will be Parkinson’s Disease (early PD vs. healthy). The within-subject factors will be the task complexity (single- vs. dual-task) in each motor activity, i.e., overground walking, semi-tandem stance, and isometric knee extension, and a walking condition (wide vs. narrow lane) will be implemented for the overground walking activity only. To study dual-task (DT) effects, in each motor activity participants will be given a secondary cognitive task, i.e., a visual discrimination task for the overground walking, an attention task for the semi-tandem, and mental arithmetic for the isometric extension. Analyses of DT effects and underlying neuronal correlates will focus on both gait and cognitive performance where applicable. Based on an a priori sample size calculation, a total N = 42 older adults (55-75 years) will be recruited. Disease-specific changes such as laterality in motor unit behavior and cortical control of movement will be studied with high-density surface electromyography and electroencephalography during static and dynamic motor activities, together with whole-body kinematics. Discussion: This study will be one of the first to holistically address early PD neurophysiological and neuromuscular patterns in an ecologically valid environment under cognitive-motor DT conditions of different complexities. The outcomes of the study aim to identify the biomarker for early PD either at the electrophysiological, muscular or kinematic level or in the communication between these systems. Clinical Trial Registration: ClinicalTrials.Gov, NCT05477654. This study was approved by the Medical Ethical Committee (106/2021).

Distance-Based Elliptical Circumnavigation Control for Non-Holonomic Robots With Event-Triggered Unknown System Dynamics Estimators

How to efficiently collect multi-dimensional information of traffic accidents with high dangers has triggered intensive concerns in intelligent transportation community. This paper provides a viable and continuous observation solution using low-budgeted mobile robots. At the kinematic level, a relative position estimator utilizing available distance data is constructed with an exponential error convergence, removing the dependency of using global position. To proceed, resorting to estimation results, an elliptical encircling guidance rule with a time-varying radius is established to preserve circumnavigation concerning targets. At the kinetic level, a new fuel-saving uncertainty mitigation scheme, i.e., event-triggered unknown system dynamics estimators (ETUSDEs) with the feature of a reduced transmission load and a concise structure are respectively developed in velocity and angular rate subsystems to reconstruct uncertainties with a prescribed decaying rate, where event-triggering conditions are enforced to schedule updating frequency of actuators and measurements in an aperiodic manner instead of a fixed time interval. Then, an event-triggered robust kinetic control protocol is synthesized to achieve an accurate command tracking without incurring Zeno behaviors. Finally, the convergence of entire system is illustrated through input-to-state stable (ISS) criterion. Simulation results are delivered to testify the effectiveness of proposed method.

Output-Feedback Finite-Time Safety-Critical Coordinated Control of Path-Guided Marine Surface Vehicles Based on Neurodynamic Optimization

In the presence of static and moving obstacles, this article investigates an output-feedback finite-time safety-critical coordinated control method of multiple under-actuated marine surface vehicles (MSVs) subject to velocity and input constraints. Specifically, based on robust exact differentiators, a finite-time state observer (FTSO) is first developed to recover the unavailable velocities while estimating the total disturbances containing model uncertainties and environmental disturbances. Next, with the aid of estimated velocities from FTSO, a nominal finite-time guidance law is designed for achieving the distributed formation of MSVs at the kinematic level. By the forward invariance principle, finite-time control barrier functions (FTCBFs) are used to construct the collision-free velocity sets for the multi-MSV system. To unify the control and safety objectives, quadratic optimization problems are formulated under collision-free velocity sets and velocity constraints. To facilitate real-time implementations, one-layer recurrent neural networks are employed to solve the quadratic optimization problem. Then, a nominal finite-time control law based on FTSO is presented at the kinetic level. The optimal control laws are solved within the input constraints. All error signals of the closed-loop system are proved to be uniformly ultimately bounded, and the distributed formation of multiple MSVs is ensured to be safe. Simulation results are provided to demonstrate the effectiveness and superiority of the proposed FTCBF-based method.

Kinematic performance of micro-mobility vehicles during braking: experimental analysis and comparison between e-kick scooters and bikes

According to the Italian legislation, e-kick scooters and bikes are considered a single category of vehicles and can travel on the same infrastructures with the same rules; however, their kinematic behavior is very different.The adoption of a bike as a vehicle for covering short distances i.e., within 5 km is widely known both at the kinematic level and for its use by users. Conversely, e-kick scooters are "unknown" vehicles both for their kinematic characteristics and for their use by users. A handful of studies have shown how the behavior of e-kick scooters and bikes is very different; however, there are not many studies that analyze the different kinematic behavior of e-kick scooters and bikes. This study presents an experimental analysis that evaluates braking behavior by comparing e-kick scooters and traditional bikes according to several vehicle speeds.These analyzes help build a probabilistic mathematical model for estimating the stopping space of e-kick scooters and bikes. The availability of this model is crucial for the design of safe intersections between cycle paths and roads intended for motor vehicle traffic. Moreover, this model may reveal insights that could challenge the recent European regulations that equated e-kick scooters as bikes.

Timbr Foldr – A Design Framework and Material System for Closed Cross-section Curved Folded Structures

This research investigated building components that can be produced and transported in a flat state and transformed to a spatial state without scaffolding on-site. Curved folding was employed to allow for a shape change between flat and spatial bending active structures. Bending generally allows for expressive curvature with simple flat production as well as easy customization. Limitations presented by laborious forming and upscaling of individually bent plates were overcome by large-scale curved folding. The present research builds upon the context but adds a design framework for volumetric curved folded components, a bistable behavior, and comprehensive detailing regarding upscaling and increased structural capacity. The mechanism was studied on a kinematic level, considering geometrical rules of curved folding and the design space. It was also studied on a kinetic level under the consideration of material properties specific to plywood. As a proof of concept, a 1:1 scale demonstrator was built. Finite element modeling software was used to optimize the shape. The demonstrator was fabricated flat, folded up, and locked in its stable configuration by the bistability and bases. It supported twelve people with a self-weight of approximately 300kg.

3D hybrid formation control of an underwater robot swarm: Switching topologies, unmeasurable velocities, and system constraints

This paper addresses formation control of underactuated autonomous underwater vehicles in three-dimensional space, using a hybrid protocol that combines aspects of centralized and decentralized control with constraints that are particular to underwater vehicles, including switching topologies, unmeasurable velocities, and system constraints. Using a distributed leader–follower model, the hybrid formation protocol does not require velocity sensing, access to global information, or static and connected topologies. To handle switching jointly connected networks—that is, to tolerate temporary disconnections—a distributed observer is designed for followers to cooperatively estimate leader states using local measurements and local interactions. On this basis, a compound formation control strategy is proposed to achieve geometric convergence. Firstly, cascaded extended state observers are developed to recover the unmeasurable velocities and unknown dynamic uncertainties induced by internal model uncertainty and external disturbances. Secondly, an improved three-dimensional line-of-sight guidance law at the kinematic level is used to address the underactuated configuration and the nonzero attack and sideslip angles. Thirdly, to overcome potential instability as a result of system constraints, including velocity constraints and input saturations, two adaptive compensators in the dynamic controller are used to address the negative effects of truncation. Using the proposed approach, the estimation errors and formation tracking errors are proved to be uniformly and ultimately bounded. Additionally, the numerical simulation results verify the performance of the approach and demonstrate improvement over both distributed and centralized state-of-the-art approaches.

An adaptive delay-compensated filtering system and the application to path following control for unmanned surface vehicles

Given that the internal states of a system, such as position, velocity, acceleration, and other important factors, naturally obey the integral processes of a physical system in kinematics, this paper presents an adaptive noise filtering system that can reconstruct these system states at the kinematic level. This is done without using any prior knowledge of the statistical properties of measurement noises. In the proposed filtering system here, each noise-contaminated estimated state is filtered by an average filter to compensate for phase delay and amplitude distortion. Unlike existing model-based estimation methods, the dynamic equation is not explicitly used in the proposed method, and the uncertainties in the nonlinear dynamic equation can be isolated. Furthermore, this application is much more straightforward as there are no gains to be processed. To verify our proposed adaptive filtering system, it has been applied to a variable speed path-following control task for unmanned surface vehicles (USVs), where accurate system states must be known. In particular, this paper also proposes a state-constrained finite-time control framework to realize the path-following control objectives. The proposed controller here mainly consists of two parts, i.e., an online state-constrained polynomial planning function and an execution of an algebraic control law. Simulations and experiments have been conducted to validate the effectiveness and reliability of the proposed filtering system and the finite-time controller. The results show that the proposed filtering system considerably outperformed several of conventional observers such as the extended Kalman filter (EKF), the passive observer, as well as the high-order differentiator.

Distributed finite-time performance-prescribed time-varying formation control of autonomous surface vehicles with saturated inputs

This paper studies a time-varying formation control problem of a swarm of autonomous surface vehicles (ASVs) with prescribed constraints. Every ASV suffers from unavailable velocities, saturated inputs, internal uncertainties, and external disturbances. A distributed finite-time performance-prescribed time-varying formation control method is proposed for ASVs. Specifically, an adaptive fuzzy state observer (AFSO) is firstly proposed to recover the unavailable velocity by using saturated inputs and estimated disturbances from the fuzzy logic system. Secondly, a tunnel prescribed performance (TPP) function is designed to limit tracking errors with a concise form and smaller overshoot. At the kinematic level, with TPP-based error transformation, a C1 finite-time time-varying guidance law is proposed by using the smooth switch functions and recovered velocities. Next, a finite-time command filter based on Levant differentiator is presented to smooth the guidance signals. At the kinetic level, a C1 finite-time saturated control law is developed with the estimated velocities and disturbances. Then, it proves that tracking errors of the proposed closed-loop system converge into a small neighborhood around the equilibrium within finite time while evolving under TPP constraints regardless of saturated inputs. Finally, comparison results are provided to demonstrate the effectiveness of the proposed distributed finite-time performance-prescribed time-varying formation control method.