Shaping of Reach-to-Grasp Kinematics by Intentions: A Meta-Analysis

Age-related changes in motor planning for prior intentions: a mouse tracking reach-to-click task

When we complete sequential movements with different intentions, we plan our movements and adjust ahead. Such a phenomenon is called anticipatory planning for prior intentions and is known to decline with age. In daily life activities, we often need to consider and plan for multiple demands in one movement sequence. However, previous studies only considered one dimension of prior intentions, either different types of onward actions or different precisions of fit or placement. Therefore, in this study, we investigated anticipatory planning for both extrinsic (movement direction) and intrinsic (fit precision) target-related properties in a computer-based movement task and analyzed the computer cursor movement kinematics of both young and older adults. We found that older people consider and adjust for different properties step-by-step, with movement direction being considered as a prior intention during reach movement and fit precision as a motor constraint during drop movement. The age-related changes in the completion of onward actions are constrained by one's general cognitive ability, sensorimotor performance and effective motor planning for prior intentions. Age-related decline in motor planning can manifest as counterproductive movement profiles, resulting in suboptimal performance of intended actions.

Motion Analysis of the Mug Transportation Task Through Upper Limb Kinematics

The task of transporting objects is a fundamental part of daily living activities. Previous kinematic studies focusing on tasks such as pointing, reach-to-grasp, and drinking have not fully captured the motor behaviors involved in object transportation, including placing a cup on a table or storing items in specific places. Hence, this study aimed to analyze the motor behavior associated with transporting a mug using upper limb kinematic variables. Fifteen healthy adults were instructed to transport an open-handle mug across a table. The kinematic metrics evaluated included object end-error for accuracy, frontal and lateral end-range for precision, movement time, peak velocity, time to peak velocity for control strategy, object path ratio for efficiency, and interjoint coordination. The stability of motor behavior was assessed through a test-retest analysis. The mug transporting task achieved accuracy with a radius <10 mm around the target, a peak velocity of ∼0.4 m/s, a control strategy where acceleration time constituted about 30% of the movement time, and a slightly curved trajectory. The test-retest analysis confirmed stable motor behavior across all kinematic metrics (ICCs > 0.75). Thus, the mug transporting task exhibited unique and stable kinematic characteristics, distinguishing it from non-transport activities and effectively mirroring transporting activities of daily living.

Recognition of Grasping Patterns Using Deep Learning for Human-Robot Collaboration

Recent advances in the field of collaborative robotics aim to endow industrial robots with prediction and anticipation abilities. In many shared tasks, the robot's ability to accurately perceive and recognize the objects being manipulated by the human operator is crucial to make predictions about the operator's intentions. In this context, this paper proposes a novel learning-based framework to enable an assistive robot to recognize the object grasped by the human operator based on the pattern of the hand and finger joints. The framework combines the strengths of the commonly available software MediaPipe in detecting hand landmarks in an RGB image with a deep multi-class classifier that predicts the manipulated object from the extracted keypoints. This study focuses on the comparison between two deep architectures, a convolutional neural network and a transformer, in terms of prediction accuracy, precision, recall and F1-score. We test the performance of the recognition system on a new dataset collected with different users and in different sessions. The results demonstrate the effectiveness of the proposed methods, while providing valuable insights into the factors that limit the generalization ability of the models.

Depth and direction effects in the prediction of static and shifted reaching goals from kinematics

The kinematic parameters of reach-to-grasp movements are modulated by action intentions. However, when an unexpected change in visual target goal during reaching execution occurs, it is still unknown whether the action intention changes with target goal modification and which is the temporal structure of the target goal prediction. We recorded the kinematics of the pointing finger and wrist during the execution of reaching movements in 23 naïve volunteers where the targets could be located at different directions and depths with respect to the body. During the movement execution, the targets could remain static for the entire duration of movement or shifted, with different timings, to another position. We performed temporal decoding of the final goals and of the intermediate trajectory from the past kinematics exploiting a recurrent neural network. We observed a progressive increase of the classification performance from the onset to the end of movement in both horizontal and sagittal dimensions, as well as in decoding shifted targets. The classification accuracy in decoding horizontal targets was higher than the classification accuracy of sagittal targets. These results are useful for establishing how human and artificial agents could take advantage from the observed kinematics to optimize their cooperation in three-dimensional space.

The combined effects of motor and social goals on the kinematics of object-directed motor action

Voluntary actions towards manipulable objects are usually performed with a particular motor goal (i.e., a task-specific object-target-effector interaction) and in a particular social context (i.e., who would benefit from these actions), but the mutual influence of these two constraints has not yet been properly studied. For this purpose, we asked participants to grasp an object and place it on either a small or large target in relation to Fitts’ law (motor goal). This first action prepared them for a second grasp-to-place action which was performed under temporal constraints, either by the participants themselves or by a confederate (social goal). Kinematic analysis of the first preparatory grasp-to-place action showed that, while deceleration time was impacted by the motor goal, peak velocity was influenced by the social goal. Movement duration and trajectory height were modulated by both goals, the effect of the social goal being attenuated by the effect of the motor goal. Overall, these results suggest that both motor and social constraints influence the characteristics of object-oriented actions, with effects that combine in a hierarchical way.

The Visual Perception of Material Properties Affects Motor Planning in Prehension: An Analysis of Temporal and Spatial Components of Lifting Cups

The current study examined the role of visually perceived material properties in motor planning, where we analyzed the temporal and spatial components of motor movements during a seated reaching task. We recorded hand movements of 14 participants in three dimensions while they lifted and transported paper cups that differed in weight and glossiness. Kinematic- and spatial analysis revealed speed-accuracy trade-offs to depend on visual material properties of the objects, in which participants reached slower and grabbed closer to the center of mass for stimuli that required to be handled with greater precision. We found grasp-preparation during the first encounters with the cups was not only governed by the anticipated weight of the cups, but also by their visual material properties, namely glossiness. After a series of object lifting, the execution of reaching, the grip position, and the transportation of the cups from one location to another were preeminently guided by the object weight. We also found the planning phase in reaching to be guided by the expectation of hardness and surface gloss. The findings promote the role of general knowledge of material properties in reach-to-grasp movements, in which visual material properties are incorporated in the spatio-temporal components.

Observer-Agent Kinematic Similarity Facilitates Action Intention Decoding

It is well known that the kinematics of an action is modulated by the underlying motor intention. In turn, kinematics serves as a cue also during action observation, providing hints about the intention of the observed action. However, an open question is whether decoding others’ intentions on the basis of their kinematics depends solely on how much the kinematics varies across different actions, or rather it is also influenced by its similarity with the observer motor repertoire. The execution of reach-to-grasp and place actions, differing for target size and context, was recorded in terms of upper-limb kinematics in 21 volunteers and in an actor. Volunteers had later to observe the sole reach-to-grasp phase of the actor’s actions, and predict the underlying intention. The potential benefit of the kinematic actor-participant similarity for recognition accuracy was evaluated. In execution, both target size and context modulated specific kinematic parameters. More importantly, although participants performed above chance in intention recognition, the similarity of motor patterns positively correlated with recognition accuracy. Overall, these data indicate that kinematic similarity exerts a facilitative role in intention recognition, providing further support to the view of action intention recognition as a visuo-motor process grounded in motor resonance.