How do we understand the intentions of other people? There has been a longstanding controversy over whether it is possible to understand others’ intentions by simply observing their movements. Here, we show that indeed movement kinematics can form the basis for intention detection. By combining kinematics and psychophysical methods with classification and regression tree (CART) modeling, we found that observers utilized a subset of discriminant kinematic features over the total kinematic pattern in order to detect intention from observation of simple motor acts. Intention discriminability covaried with movement kinematics on a trial-by-trial basis, and was directly related to the expression of discriminative features in the observed movements. These findings demonstrate a definable and measurable relationship between the specific features of observed movements and the ability to discriminate intention, providing quantitative evidence of the significance of movement kinematics for anticipating others’ intentional actions.

It has been shown that when subjects can predict object properties [e.g., weight or center of mass (CM)], fingertip forces are appropriately scaled before the object is lifted, i.e., before somatosensory feedback can be processed. However, it is not known whether subjects, in addition to these anticipatory force mechanisms, exploit the ability to choose where digits can be placed to facilitate object manipulation. We addressed this question by asking subjects to reach and grasp an object whose CM was changed to the left, center, or right of the object in either a predictable or unpredictable manner. The only task requirement was to minimize object roll during lift. We hypothesized that subjects would modulate contact points but only when object CM location could be predicted. As expected, object roll was significantly smaller in the predictable condition. This experimental condition was also associated with statistically distinct spatial distributions of contact points as a function of object CM location but primarily when large torques had to be counteracted, i.e., for right and left CM locations. In contrast, when subjects could not anticipate CM location, a "default" distribution of contact points was used, this being statistically indistinguishable from that adopted for the center CM location in the predictable condition. We conclude that choice of contact points is integrated with anticipatory force control mechanisms to facilitate object manipulation. These results demonstrate that planning of digit placement is an important component of grasp control.

Objects can be grasped in several ways due to their physical properties, the context surrounding the object, and the goal of the grasping agent. The aim of the present study was to investigate whether the prior-to-contact grasping kinematics of the same object vary as a result of different goals of the person grasping it. Subjects were requested to reach toward and grasp a bottle filled with water, and then complete one of the following tasks: (1) Grasp it without performing any subsequent action; (2) Lift and throw it; (3) Pour the water into a container; (4) Place it accurately on a target area; (5) Pass it to another person. We measured the angular excursions at both metacarpal-phalangeal (mcp) and proximal interphalangeal (pip) joints of all digits, and abduction angles of adjacent digit pairs by means of resistive sensors embedded in a glove. The results showed that the presence and the nature of the task to be performed following grasping affect the positioning of the fingers during the reaching phase. We contend that a one-to-one association between a sensory stimulus and a motor response does not capture all the aspects involved in grasping. The theoretical approach within which we frame our discussion considers internal models of anticipatory control which may provide a suitable explanation of our results.

. The aim of the present study was to determine whether hand shaping was affected by planning of an action subsequent to object contact. Ten subjects (5 females and 5 males, ages 19 -33) were requested to reach toward and grasp a convex object between the thumb and the four fingers of the right hand and to perform one of the following actions: 1) lift up the object; 2) insert the object into a niche of a similar shape and size as the object, or 3) insert the object into a rectangular niche much larger than the object. Flexion/extension at the metacarpal-phalangeal and proximal interphalangeal joints of all digits were measured using resistive sensors embedded in a glove. Although all experimental conditions required grasping the same object, we found different covariation patterns among finger joint angles across conditions. Gradual preshaping of the hand occurred only when planning object lift or when the end-goal required object placement into the tight niche. In contrast, for the larger niche, gradual preshaping was not evident for the ring and the little finger. Further, reaching movements were faster for movements ending with the larger niche than for the other movement conditions. The present results suggest that hand shaping takes into account end-goal in addition to object geometry. We discuss these findings in the context of forward internal models that allow the prediction of the sensorimotor consequences of motor commands in advance to their execution.

Research on reach-to-grasp movements generally concentrates on kinematics values that are expression of maxima, in particular the maximum aperture of the hand and the peak of wrist velocity. These parameters provide a snapshot description of movement kinematics at a specific time point during reach, i.e., the maximum within a set of value, but do not allow to investigate how hand kinematics gradually conform to target properties. The present study was designed to extend the characterization of object size effects to the temporal domain. Thus, we computed the wrist velocity and the grip aperture throughout reach-to-grasp movements aimed at large versus small objects. To provide a deeper understanding of how joint movements varied over time, we also considered the time course of finger motion relative to hand motion. Results revealed that movement parameters evolved in parallel but at different rates in relation to object size. Furthermore, a classification analysis performed using a Support Vector Machine (SVM) approach showed that kinematic features taken as a group predicted the correct target size well before contact with the object. Interestingly, some kinematics features exhibited a higher ability to discriminate the target size than others did. These findings reinforce our knowledge about the relationship between kinematics and object properties and shed new light on the quantity and quality of information available in the kinematics of a reach-to-grasp movement over time. This might have important implications for our understanding of the action-perception coupling mechanism.