Startle Increases the Incidence of Anticipatory Muscle Activations but Does Not Change the Task-Specific Muscle Onset for Patients After Subacute Stroke

Objectives: To demonstrate the task-specificities of anticipatory muscle activations (AMAs) among different forward-reaching tasks and to explore the StartleReact Effect (SE) on AMAs in occurrence proportions, AMA onset latency or amplitude within these tasks in both healthy and stroke population.Methods: Ten healthy and ten stroke subjects were recruited. Participants were asked to complete the three forward-reaching tasks (reaching, reaching to grasp a ball or cup) on the left and right hand, respectively, with two different starting signals (warning-Go, 80 dB and warning-startle, 114 dB). The surface electromyography of anterior deltoid (AD), flexor carpi radialis (FCR), and extensor carpi radialis (ECR) on the moving side was recorded together with signals from bilateral sternocleidomastoid muscles (SCM), lower trapezius (LT), latissimus dorsi (LD), and tibialis anterior (TA). Proportions of valid trials, the incidence of SE, AMA incidence of each muscle, and their onset latency and amplitude were involved in analyses. The differences of these variables across different move sides (healthy, non-paretic, and paretic), normal or startle conditions, and the three tasks were explored. The ECR AMA onset was selected to further explore the SE on the incidence of AMAs.Results: Comparisons between move sides revealed a widespread AMA dysfunction in subacute stroke survivors, which was manifested as lower AMA onset incidence, changed onset latency, and smaller amplitude of AMAs in bilateral muscles. However, a significant effect of different tasks was only observed in AMA onset latency of muscle ECR (F = 3.56, p = 0.03, η2p = 0.011), but the significance disappeared in the subsequent analysis of the stroke subjects only (p > 0.05). Moreover, the following post-hoc comparison indicated significant early AMA onsets of ECR in task cup when comparing with reach (p < 0.01). For different stimuli conditions, a significance was only revealed on shortened premotor reaction time under startle for all participants (F = 60.68, p < 0.001, ηp2 = 0.056). Furthermore, stroke survivors had a significantly lower incidence of SE than healthy subjects under startle (p < 0.01). But all performed a higher incidence of ECR AMA onset (p < 0.05) than with normal signal. In addition, the incidence of ECR AMAs of both non-paretic and paretic sides could be increased significantly via startle (p ≤ 0.02).Conclusions: Healthy people have task-specific AMAs of muscle ECR when they perform forward-reaching tasks with different hand manipulations. However, this task-specific adjustment is lost in subacute stroke survivors. SE can improve the incidence of AMAs for all subjects in the forward-reaching tasks involving precision manipulations, but not change AMA onset latency and amplitude.

Effects of Task Constraints on Kinematic Characteristics of Body Segments in Children with Cerebral Palsy and Children with Typical Development during Hand-Reaching

Background: Children with cerebral palsy (CP) have difficulty in managing postural control during functional reaching tasks, although children with different postural control ability are able to come up with different motor solutions to cope with different task demands. This study examined the effect of task constraint on postural control performance in children with cerebral palsy and typical development (TD) in terms of different postural control abilities. Methods: A cross-sectional research design was used. Twelve children with spastic diplegic cerebral palsy (mean age: 107.8 months) and 16 typically developing children (mean age: 110.9 months) participated in this study. Individually, all subjects were seated in a height-adjusted chair and were requested to reach for target(s) located at three different directions (medial, anterior, and lateral). A six-camera Qualisys Motion Capture System was used to capture motion data. Kinematic data in terms of body alignment and angular changes were analyzed. Results: Children with cerebral palsy demonstrated different postural control strategies to complete different reaching tasks compared to typically developing children by preparing postural alignment in advance, coordinating different body orientation movements during reaching after showing difficulty in managing reach medially. Conclusions: Children with cerebral palsy perceive their insufficient ability and prepare their alignment in advance to adapt to the task demanded and decrease the postural challenges of the task. Even though children with cerebral palsy self-generate different motor solutions to reach without falling, these alternative strategies might not be the most efficient adaptation.

The Study of 3D Reaching Tasks on Visual Servoing Using Quaternion

The image-based monocular visual servoing is difficult to realize the grasping task on three-dimension. This study presented a method of quaternion on 3D reaching tasks of visual servoing. This method used a camera and a laser scanner to acquire the information of the images and the depth. Then the parameters of Jacobian matrix could be determined by the method of the quaternion. A particular constraint mechanism was also proposed to optimize the reaching trajectory of the robot. The simulation results demonstrated our proposed method could implement the 3D reaching tasks successfully and had a significant performance improvement compared to conventional methods.

Smoothness metrics for reaching performance after stroke. Part 1: which one to choose?

Background Smoothness is commonly used for measuring movement quality of the upper paretic limb during reaching tasks after stroke. Many different smoothness metrics have been used in stroke research, but a ‘valid’ metric has not been identified. A systematic review and subsequent rigorous analysis of smoothness metrics used in stroke research, in terms of their mathematical definitions and response to simulated perturbations, is needed to conclude whether they are valid for measuring smoothness. Our objective was to provide a recommendation for metrics that reflect smoothness after stroke based on: (1) a systematic review of smoothness metrics for reaching used in stroke research, (2) the mathematical description of the metrics, and (3) the response of metrics to simulated changes associated with smoothness deficits in the reaching profile. Methods The systematic review was performed by screening electronic databases using combined keyword groups Stroke, Reaching and Smoothness. Subsequently, each metric identified was assessed with mathematical criteria regarding smoothness: (a) being dimensionless, (b) being reproducible, (c) being based on rate of change of position, and (d) not being a linear transform of other smoothness metrics. The resulting metrics were tested for their response to simulated changes in reaching using models of velocity profiles with varying reaching distances and durations, harmonic disturbances, noise, and sub-movements. Two reaching tasks were simulated; reach-to-point and reach-to-grasp. The metrics that responded as expected in all simulation analyses were considered to be valid. Results The systematic review identified 32 different smoothness metrics, 17 of which were excluded based on mathematical criteria, and 13 more as they did not respond as expected in all simulation analyses. Eventually, we found that, for reach-to-point and reach-to-grasp movements, only Spectral Arc Length (SPARC) was found to be a valid metric. Conclusions Based on this systematic review and simulation analyses, we recommend the use of SPARC as a valid smoothness metric in both reach-to-point and reach-to-grasp tasks of the upper limb after stroke. However, further research is needed to understand the time course of smoothness measured with SPARC for the upper limb early post stroke, preferably in longitudinal studies.

Motor learning in reaching tasks leads to homogenization of task space error distribution

A human arm, up to the wrist, is often modelled as a redundant 7 degree-of-freedom serial robot. Despite its inherent nonlinearity, we can perform point-to-point reaching tasks reasonably fast and with reasonable accuracy in the presence of external disturbances and noise. In this work, we take a closer look at the task space error during point-to-point reaching tasks and learning during an external force-field perturbation. From experiments and quantitative data, we confirm a directional dependence of the peak task space error with certain directions showing larger errors than others at the start of a force-field perturbation, and the larger errors are reduced with repeated trials implying learning. The analysis of the experimental data further shows that a) the distribution of the peak error is made more uniform across directions with trials and the error magnitude and distribution approaches the value when no perturbation is applied, b) the redundancy present in the human arm is used more in the direction of the larger error, and c) homogenization of the error distribution is not seen when the reaching task is performed with the non-dominant hand. The results support the hypothesis that not only magnitude of task space error, but the directional dependence is reduced during motor learning and the workspace is homogenized possibly to increase the control efficiency and accuracy in point-to-point reaching tasks. The results also imply that redundancy in the arm is used to homogenize the workspace, and additionally since the bio-mechanically similar dominant and non-dominant arms show different behaviours, the homogenizing is actively done in the central nervous system.

On the Impact of Gravity Compensation on Reinforcement Learning in Goal-Reaching Tasks for Robotic Manipulators

Advances in machine learning technologies in recent years have facilitated developments in autonomous robotic systems. Designing these autonomous systems typically requires manually specified models of the robotic system and world when using classical control-based strategies, or time consuming and computationally expensive data-driven training when using learning-based strategies. Combination of classical control and learning-based strategies may mitigate both requirements. However, the performance of the combined control system is not obvious given that there are two separate controllers. This paper focuses on one such combination, which uses gravity-compensation together with reinforcement learning (RL). We present a study of the effects of gravity compensation on the performance of two reinforcement learning algorithms when solving reaching tasks using a simulated seven-degree-of-freedom robotic arm. The results of our study demonstrate that gravity compensation coupled with RL can reduce the training required in reaching tasks involving elevated target locations, but not all target locations.

Comprehensive Review on Reaching and Grasping of Objects in Robotics

SUMMARY Interaction between a robot and its environment requires perception about the environment, which helps the robot in making a clear decision about the object type and its location. After that, the end effector will be brought to the object’s location for grasping. There are many research studies on the reaching and grasping of objects using different techniques and mechanisms for increasing accuracy and robustness during grasping and reaching tasks. Thus, this paper presents an extensive review of research directions and topics of different approaches such as sensing, learning and gripping, which have been implemented within the current five years.