Joint Angle Trajectories Research Articles

A functional analysis-based approach to quantify upper limb impairment level in chronic stroke patients: a pilot study.

The accurate assessment of upper limb motion impairment induced by stroke - which represents one of the primary causes of disability world-wide - is the first step to successfully monitor and guide patients' recovery. As of today, the majority of the procedures relies on clinical scales, which are mostly based on ordinal scaling, operator-dependent, and subject to floor and ceiling effects. In this work, we intend to overcome these limitations by proposing a novel approach to analytically evaluate the level of pathological movement coupling, based on the quantification of movement complexity. To this goal, we consider the variations of functional Principal Components applied to the reconstruction of joint angle trajectories of the upper limb during daily living task execution, and compared these variations between two conditions, i.e. the affected and non-affected arm. A Dissimilarity Index, which codifies the severity of the upper limb motor impairment with respect to the movement complexity of the non-affected arm, is then proposed. This methodology was validated as a proof of concept upon a set of four chronic stroke subjects with mild to moderate arm and hand impairments. As a first step, we evaluated whether the derived outcomes differentiate between the two conditions upon the whole data-set. Secondly, we exploited this concept to discern between different subjects and impairment levels. Results show that: i) differences in terms of movement variability between the affected and nonaffected upper limb are detectable and ii) different impairment profiles can be characterized for single subjects using the proposed approach. Although provisional, these results are very promising and suggest this approach as a basis ingredient for the definition of a novel, operator-independent, sensitive, intuitive and widely applicable scale for the evaluation of upper limb motion impairment.

On the Time-Invariance Properties of Upper Limb Synergies

In this paper, we present a novel approach to dynamically describe human upper limb trajectories, addressing the question on whether and to which extent synergistic multi-joint behavior is observed and preserved over time evolution and across subjects. To this goal, we performed experiments to collect human upper limb joint angle trajectories and organized them in a dataset of daily living tasks. We then characterized the upper limb poses at each time frame through a technique that we named repeated-principal component analysis (R-PCA). We found that, although there is no strong evidence on the predominance of one principal component (PC) over the others, the subspace identified by the first three PCs takes into account most of the motion variability. We evaluated the stability of these results over time, showing that during the reaching phase, there is a strong consistency of these findings across participants. In other words, our results suggest that there is a time-invariant low-dimensional approximation of upper limb kinematics, which can be used to define a suitable reduced dimensionality control space for upper limb robotic devices in motion phases.

The Recognition of Motion Intention of Knee Joint Based on Piezoelectric Signals

Aiming at the human body exoskeleton motion intention recognition process, based on the pressure signals of muscle groups of control, building joint motion information acquisition system, the application of multi-sensor information fusion technique based on neural network, based on the piezoelectric signal muscle as input and output of the joint angle trajectory motion intention model, calculate the joint exercise intention and angle track. Finally, the knee flexion and extension movement as the main object of study, through calculation and practical test, the ideal results are obtained. It shows that the motion signals of the knee joint can be reflected by the piezoelectric signals collected during the motion of the knee joint.

Opioid-Induced Reductions in Gait Variability in Healthy Volunteers and Individuals with Knee Osteoarthritis.

To investigate differences in gait variability induced by two different single-dose opioid formulations and an inert placebo in healthy volunteers and knee osteoarthritis patients. Experimental, randomized, double-blinded, crossover study of inert placebo (calcium tablets), 50 mg of tapentadol, and 100 mg of tramadol. Laboratory setting. Healthy volunteers and knee osteoarthritis patients. At three visits, separated by seven days, one tablet was administered per visit according to the randomization code. At each visit, a baseline measurement was done before tablet administration, after which hourly measurements were performed for six hours, yielding a total of seven measurements per visit. Gait variability was measured by three-dimensional gait analysis, recorded during six minutes of continuous treadmill walking at self-selected speed. One hundred seventy gait cycles were identified from detection of clear events of the knee joint angle trajectories. Gait variability was assessed as average standard deviations over a gait cycle of the sacrum displacements and accelerations; sagittal plane ankle, knee, and hip joint angles; step widths; and stride times. Twenty-four opioid-naïve and neurologically intact participants (12 healthy volunteers and 12 knee osteoarthritis patients) were included and completed the experiment. Tapentadol reduced the variability of sacrum displacements and accelerations compared with placebo and tramadol. There were no differences between experimental conditions regarding the variability in lower-extremity joint angle variability, step widths, or stride times. In opioid-naïve and neurologically intact individuals, tapentadol seems to reduce movement variability during treadmill walking, compared with placebo and tramadol. This can be interpreted as a loss of adaptability that might increase the risk of falling if the system is perturbed.

Dynamic Modelling and Analyzing of a Walking of Humanoid Robot

Abstract This paper focuses on the walking improvement of a biped robot. The zero-moment point (ZMP) method is used to stabilise the walking process of robot. The kinematic model of the humanoid robot is based on Denavit- Hartenberg’s (D-H) method, as presented in this paper. This work deals with the stability analysis of a two-legged robot during double and single foot walking. It seems more difficult to analyse the dynamic behaviour of a walking robot due to its mathematical complexity. In this context most humanoid robots are based on the control model. This method needs to design not only a model of the robot itself but also the surrounding environment. In this paper, a kinematic simulation of the robotic system is performed in MATLAB. Driving torque of the left and right ankle is calculated based on the trajectory of joint angle, the same as angular velocity and angular acceleration. During this process an elmo motion controller is used for all joints. The validity of the dynamic model is tested by comparing obtained results with the simulation results.

Stride-to-stride fluctuations in transtibial amputees are not affected by changes in push-off mechanics from using different prostheses.

Stride-to-stride fluctuations of joint kinematics during walking reflect a highly structured organization that is characteristic of healthy gait. The organization of stride-to-stride fluctuations is disturbed in lower-limb prosthesis users, yet the factors contributing to this difference are unclear. One potential contributor to the changes in stride-to-stride fluctuations is the altered push-off mechanics experienced by passive prosthesis users. The purpose of our study was to determine if changes in push-off mechanics affect stride-to-stride fluctuations in transtibial amputees. Twenty-two unilateral transtibial amputees were enrolled in the 6-week cross-over study, where High and Low Activity (based on the Medicare Functional Classification System) prostheses were worn for three weeks each. Data collection took place at the end of the third week. Participants walked on a treadmill in a motion capture laboratory to quantify stride-to-stride fluctuations of the lower extremity joint angle trajectories using the largest Lyapunov Exponent, and over floor-embedded force platforms to enable calculating push-off work from the prosthesis and the sound limb. Push-off work was 140% greater in the High Activity prosthesis compared to the Low Activity prosthesis (p < 0.001), however no significant change was observed in stride-to-stride fluctuations of the ankle between the two prosthesis types (p = 0.576). There was no significant correlation between changes in prosthesis push-off work and the largest Lyapunov exponent. Though differences in push-off work were observed between the two prosthesis types, stride-to-stride fluctuations remained similar, indicating that prosthesis propulsion mechanics may not be a strong determinant of stride-to-stride fluctuations in unpowered transtibial prosthesis users.

Design, Modeling, and Integration of a Flexible Universal Spatial Robotic Tail

This paper presents the novel design of a bioinspired robot capable of generating spatial loading relative to its base. By looking to nature at how animals utilize their tails, a bioinspired structure is developed that utilizes a redundant serial chain of rigid links to mimic the continuous deformation of a biological tail. Individual links are connected by universal joints to enable a spatial robot workspace capable of generating spatial loading comprised of pitch, yaw, and roll direction contributions. Two sets of three cables are used to create two actuated segments along the robot. A dynamic model of the robot is derived using prescribed cable displacement trajectories as inputs to determine the resulting joint angle trajectories and cable tensions. Sensors are integrated on-board the robot to calculate joint angles and joint velocities in real-time for use in feedback control. The loading capabilities of the robot are analyzed, and an experimental prototype is integrated and demonstrated.

Zhang Dynamics based Tracking Control of Knee Exoskeleton with Timedependent Inertial and Viscous Parameters

Knee exoskeleton plays an important role in robot-assisted rehabilitation for impaired pilots to restore their motor functionality of lower extremity through producing external movement compensation. Tracking control of knee exoskeleton often encounters time-dependent (time-varying) issues reflected in its dynamic behaviors. In many applications, inertial and viscous parameters of knee exoskeletons are measured to be time-dependent due to unexpected mechanical vibrations and contact interactions, which increases difficultly of accurate control of knee exoskeleton to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-dependent (time-varying) inertial and viscous coefficients. Such controller is designed based on Zhang dynamics (ZD) method and utilizes twice Zhang function (ZF) so as to make the tracking error of joint angle exponentially converge to zero. Illustrative simulation examples and experimental validation are presented to show efficiency of this type of controller based on ZD method. Comparisons with gradient dynamic (GD) approach are also presented to demonstrate superiority of ZD-type control strategy for tracking joint angle of knee exoskeleton.

Application of a symbolic motion structure representation algorithm to identify upper extremity kinematic changes during a repetitive task

Efficient and holistic identification of fatigue-induced movement strategies can be limited by large between-subject variability in descriptors of joint angle data. One promising alternative to traditional, or computationally intensive methods is the symbolic motion structure representation algorithm (SMSR), which identifies the basic spatial-temporal structure of joint angle data using string descriptors of temporal joint angle trajectories. This study attempted to use the SMSR to identify changes in upper extremity time series joint angle data during a repetitive goal directed task causing muscle fatigue. Twenty-eight participants (15 M, 13 F) performed a seated repetitive task until fatigued. Upper extremity joint angles were extracted from motion capture for representative task cycles. SMSRs, averages and ranges of several joint angles were compared at the start and end of the repetitive task to identify kinematic changes with fatigue. At the group level, significant increases in the range of all joint angle data existed with large between-subject variability that posed a challenge to the interpretation of these fatigue-related changes. However, changes in the SMSRs across participants effectively summarized the adoption of adaptive movement strategies. This establishes SMSR as a viable, logical, and sensitive method of fatigue identification via kinematic changes, with novel application and pragmatism for visual assessment of fatigue development.

Joint trajectory generator for powered orthosis based on gait modelling using PCA and FFT

SUMMARYIn this work, we propose a method able to find user-oriented gait trajectories that can be used in powered lower limb orthosis applications. Most research related to active orthotic devices focuses on solving hardware issues. However, the problem of generating a set of joint trajectories that are user-oriented still persists. The proposed method uses principal component analysis to extract shared features from a gait dataset, taking into consideration gait-related variables such as joint angle information and the user's anthropometric features, used directly in an orthosis application. The trajectories of joint angles used by the model are represented by a given number of harmonics according to their respective Fourier series analyses. This representation allows better performance of the model, whose capability to generate gait information is validated through experiments using a real active orthotic device, analysing both joint motor energy consumption and user metabolic effort.

Tracking control of time-varying knee exoskeleton disturbed by interaction torque

Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton.

Gait patterns and walking ability after training with a hybrid robotic exoskeleton compared to conventional gait training in early stroke rehabilitation

The hamstrings are often associated with the development of crouch gait, a fatiguing form of walking characterized by excessive hip flexion, knee flexion and ankle dorsiflexion during stance. However, recent studies have called into question whether abnormally active hamstrings induce the limb to move into a crouch posture. The purpose of this study was to directly measure the influence of the hamstrings on limb posture during stance. Nineteen healthy young adults walked on an instrumented treadmill at their preferred speed. A 90 ms pulse train was used to stimulate the medial hamstrings during either terminal swing or loading response of random gait cycles. Induced motion was defined as the difference in joint angle trajectories between stimulated and non-stimulated strides. A dynamic musculoskeletal simulation of normal gait was generated and similarly perturbed by increasing hamstring excitation. The experiments show that hamstring stimulation induced a significant increase in posterior pelvic tilt, knee flexion and ankle dorsiflexion during stance, while having relatively less influence on the hip angular trajectory. The induced motion patterns were similar whether the hamstrings were stimulated during late swing or early stance, and were generally consistent with the direction of induced motion predicted by gait simulation models. Hence, we conclude that overactive hamstrings have the potential to induce the limb to move toward a crouch gait posture.

Skill assessment in upper limb myoelectric prosthesis users: Validation of a clinically feasible method for characterising upper limb temporal and amplitude variability during the performance of functional tasks

Upper limb myoelectric prostheses remain challenging to use and are often abandoned. A proficient user must be able to plan/execute arm movements while activating the residual muscle(s), accounting for delays and unpredictability in prosthesis response. There is no validated, low cost measure of skill in performing such actions. Trial-trial variability of joint angle trajectories measured during functional task performance, linearly normalised by time, shows promise. However, linear normalisation of time introduces errors, and expensive camera systems are required for joint angle measurements.This study investigated whether trial-trial variability, assessed using dynamic time warping (DTW) of limb segment acceleration measured during functional task performance, is a valid measure of user skill. Temporal and amplitude variability of forearm accelerations were determined in (1) seven myoelectric prosthesis users and six anatomically-intact controls and (2) seven anatomically-intact subjects learning to use a prosthesis simulator over repeated sessions.(1): temporal variability showed clear group differences (p<0.05). (2): temporal variability considerably increased on first use of a prosthesis simulator, then declined with training (both p<0.05). Amplitude variability showed less obvious differences. Analysing forearm accelerations using DTW appears to be a valid low-cost method for quantifying movement quality of upper limb prosthesis use during goal-oriented task performance.

Gait assessment system based on novel gait variability measures.

In this paper, a novel gait assessment system based on measures of gait variability reflected through the variability of shapes of gait cycles trajectories is proposed. The presented gait assessment system is based on SVM (support vector machine) classifier and on gait variability-based features calculated from the hip and knee joint angle trajectories recorded using wearable IMUs during walking trials. A system classifier was trained to distinguish healthy gait patterns from the pathological ones. The features were extracted by calculating the distances between the joint trajectories of the individual gait cycles using 4 different distance functions. As result, the system is able to provide a Gait Variability Index (GVI), which is a numeric value that can be used as an indicator of a degree to which a pathological gait pattern is close to a healthy gait pattern. The system and GVI were tested in three experiments, involving subjects suffering from gait disorders caused by different neurological diseases. The results demonstrated that the proposed gait assessment system would be suitable for supporting clinicians in the evaluation of gait performances during the gait rehabilitation procedures.

Tracking control of knee exoskeleton system with time-dependent inertial and viscous parameters

Knee exoskeleton plays an important role in robot-assisted rehabilitation for impaired pilots to restore their motor functionality of lower extremity through producing external movement compensation. Tracking control of knee exoskeleton often encounters time-dependent (time-varying) issues reflected in its dynamic behaviors. In many applications, inertial and viscous parameters of knee exoskeletons are measured to be time-dependent due to unexpected mechanical vibrations and contact interactions, which increases difficultly of accurate control of knee exoskeleton to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-dependent (time-varying) inertial and viscous coefficients. Such controller is designed based on Zhang dynamics (ZD) method so as to make the tracking error of joint angle exponentially converge to zero. Illustrative examples are presented to show efficiency of this type of controller based on ZD method. Comparisons with gradient dynamic (GD) approach are also presented to demonstrate superiority of ZD-type control strategy for tracking joint angle of knee exoskeleton.

An Adaptive Neuromuscular Controller for Assistive Lower-Limb Exoskeletons: A Preliminary Study on Subjects with Spinal Cord Injury.

Versatility is important for a wearable exoskeleton controller to be responsive to both the user and the environment. These characteristics are especially important for subjects with spinal cord injury (SCI), where active recruitment of their own neuromuscular system could promote motor recovery. Here we demonstrate the capability of a novel, biologically-inspired neuromuscular controller (NMC) which uses dynamical models of lower limb muscles to assist the gait of SCI subjects. Advantages of this controller include robustness, modularity, and adaptability. The controller requires very few inputs (i.e., joint angles, stance, and swing detection), can be decomposed into relevant control modules (e.g., only knee or hip control), and can generate walking at different speeds and terrains in simulation. We performed a preliminary evaluation of this controller on a lower-limb knee and hip robotic gait trainer with seven subjects (N = 7, four with complete paraplegia, two incomplete, one healthy) to determine if the NMC could enable normal-like walking. During the experiment, SCI subjects walked with body weight support on a treadmill and could use the handrails. With controller assistance, subjects were able to walk at fast walking speeds for ambulatory SCI subjects—from 0.6 to 1.4 m/s. Measured joint angles and NMC-provided joint torques agreed reasonably well with kinematics and biological joint torques of a healthy subject in shod walking. Some differences were found between the torques, such as the lack of knee flexion near mid-stance, but joint angle trajectories did not seem greatly affected. The NMC also adjusted its torque output to provide more joint work at faster speeds and thus greater joint angles and step length. We also found that the optimal speed-step length curve observed in healthy humans emerged for most of the subjects, albeit with relatively longer step length at faster speeds. Therefore, with very few sensors and no predefined settings for multiple walking speeds or adjustments for subjects of differing anthropometry and walking ability, NMC enabled SCI subjects to walk at several speeds, including near healthy speeds, in a healthy-like manner. These preliminary results are promising for future implementation of neuromuscular controllers on wearable prototypes for real-world walking conditions.

Generating Feasible Solutions for Dynamically Crossing a Wide Ditch by a Biped Robot

The aim of this research work is to generate feasible motion for a biped robot to dynamically cross a wide ditch which is defined as a ditch with width more than or equal to the leg length. We propose an approach to obtain feasible solutions for dynamically crossing the wide ditch considering the dynamic balance of the biped robot, friction between the robot foot and ground, impact on the foot, limitations on the joint actuator torques and angular velocities. The biped robot is modeled as a seven link planar robot with the ditch crossing task consisting of two single support phases and a double support phase. An algorithm is developed to find the joint trajectories and the joint torques in each phase of ditch crossing by formulating the ditch crossing task as a constrained nonlinear optimization problem. In order to make the algorithm converge fast and to give feasible solutions, additional constraints called Adopted Constraints (ACs) are incorporated into the system of constraints. With time being one of the parameters, the developed algorithm adaptively adjusts the time for crossing a wide ditch. The significance of ground reaction force constraints in obtaining feasible solutions for crossing the wide ditch is shown through simulations. Feasible solutions obtained from simulation results provide not only the feasible joint angle trajectories, but also the joint torques required for the selection of actuators for a biped robot crossing the wide ditch.

Economy, Movement Dynamics, and Muscle Activity of Human Walking at Different Speeds

The complex behaviour of human walking with respect to movement variability, economy and muscle activity is speed dependent. It is well known that a U-shaped relationship between walking speed and economy exists. However, it is an open question if the movement dynamics of joint angles and centre of mass and muscle activation strategy also exhibit a U-shaped relationship with walking speed. We investigated the dynamics of joint angle trajectories and the centre of mass accelerations at five different speeds ranging from 20 to 180% of the predicted preferred speed (based on Froude speed) in twelve healthy males. The muscle activation strategy and walking economy were also assessed. The movement dynamics was investigated using a combination of the largest Lyapunov exponent and correlation dimension. We observed an intermediate stage of the movement dynamics of the knee joint angle and the anterior-posterior and mediolateral centre of mass accelerations which coincided with the most energy-efficient walking speed. Furthermore, the dynamics of the joint angle trajectories and the muscle activation strategy was closely linked to the functional role and biomechanical constraints of the joints.

Fusion of spatial-temporal and kinematic features for gait recognition with deterministic learning

For obtaining optimal performance, as many informative cues as possible should be involved in the gait recognition algorithm. This paper describes a gait recognition algorithm by combining spatial-temporal and kinematic gait features. For each walking sequence, the binary silhouettes are characterized with four time-varying spatial-temporal parameters, including three lower limbs silhouette widths and one holistic silhouette area. Using deterministic learning algorithm, spatial-temporal gait features can be represented as the gait dynamics underlying the trajectories of lower limbs silhouette widths and holistic silhouette area, which can implicitly reflect the temporal changes of silhouette shape. In addition, a model-based method is proposed to extract joint-angle trajectories of lower limbs. Kinematic gait features can be represented as the gait dynamics underlying the trajectories of joint angles, which can represent the temporal changes of body structure and dynamics. Both spatial-temporal and kinematic cues can be used separately for gait recognition using smallest error principle. They are fused on the decision level using different combination rules to improve the gait recognition performance. The fusion of two different kinds of features provides a comprehensive characterization of gait dynamics, which is not sensitive to the walking conditions variation. The proposed method can still achieve superior performance when the testing walking conditions are different from the corresponding training conditions. Experimental results show that encouraging recognition accuracy can be achieved on five public gait databases: CASIA-B, CASIA-C, TUM GAID, OU-ISIR, USF HumanID.

Effect of body weight support variation on muscle activities during robot assisted gait: a dynamic simulation study

Background and Objectives: While body weight support (BWS) intonation is vital during conventional gait training of neurologically challenged subjects, it is important to evaluate its effect during robot assisted gait training. In the present research we have studied the effect of BWS intonation on muscle activities during robotic gait training using dynamic simulations. Methods: Two dimensional (2-D) musculoskeletal model of human gait was developed conjointly with another 2-D model of a robotic orthosis capable of actuating hip, knee and ankle joints simultaneously. The musculoskeletal model consists of eight major muscle groups namely; soleus (SOL), gastrocnemius (GAS), tibialis anterior (TA), hamstrings (HAM), vasti (VAS), gluteus maximus (GLU), uniarticular hip flexors (iliopsoas, IP), and Rectus Femoris (RF). BWS was provided at levels of 0, 20, 40 and 60% during the simulations. In order to obtain a feasible set of muscle activities during subsequent gait cycles, an inverse dynamics algorithm along with a quadratic minimization algorithm was implemented. Results: The dynamic parameters of the robot assisted human gait such as joint angle trajectories, ground contact force (GCF), human limb joint torques and robot induced torques at different levels of BWS were derived. The patterns of muscle activities at variable BWS were derived and analysed. For most part of the gait cycle (GC) the muscle activation patterns are quite similar for all levels of BWS as is apparent from the mean of muscle activities for the complete GC. Conclusions: Effect of BWS variation during robot assisted gait on muscle activities was studied by developing dynamic simulation. It is expected that the proposed dynamic simulation approach will provide important inferences and information about the muscle function variations consequent upon a change in BWS during robot assisted gait. This information shall be quite important while investigating the influence of BWS intonation on neuromuscular parameters of interest during robotic gait training.