Inferring subjective states through the observation of actions

Estimating another person''s subjective confidence is crucial for social interaction, but how this inference is achieved is unknown. Previous research has demonstrated that the speed at which people make decisions is correlated with their confidence in their decision. Here, we show that (i) subjects are able to infer the subjective confidence of another person simply through the observation of their actions and (ii) this inference is dependent upon the performance of each subject when executing the action. Crucially, the latter result supports a model in which motor simulation of an observed action mediates the successful understanding of other minds. We conclude that kinematic understanding allows access to the higher-order cognitive processes of others, and that this access plays a central role in social interactions.     

Segmental Kinematic Coupling of the Human Spinal Column during Locomotion

As one of the most important daily motor activities, human locomotion has been investigated intensively in recent decades. The locomotor functions and mechanics of human lower limbs have become relatively well understood. However, so far our understanding of the motions and functional contributions of the human spine during locomotion is still very poor and simultaneous in-vivo limb and spinal column motion data are scarce. The objective of this study is to investigate the delicate in-vivo kinematic coupling between different functional regions of the human spinal column during locomotion as a stepping stone to explore the locomotor function of the human spine complex. A novel infrared reflective marker cluster system was constrncted using stereophotogrammetry techniques to record the 3D in-vivo geometric shape of the spinal column and the segmental position and orientation of each functional spinal region simultaneously. Gait measurements of normal walking were conducted. The preliminary results show that the spinal column shape changes periodically in the frontal plane during locomotion. The segmental motions of different spinal functional regions appear to be strongly coupled, indicating some synergistic strategy may be employed by the human spinal column to facilitate locomotion. In contrast to traditional medical imaging-based methods, the proposed technique can be used to investigate the dynamic characteristics of the spinal column, hence providing more insight into the functional biomechanics of the human spine.     

Locomotion of Gymnarchus Niloticus： Experiment and Kinematics

In addition to forward undulatory swimming, Gymnarchus niloticus can swim via undulations of the dorsal fin while the body axis remains straight; furthermore, it swims forward and backward in a similar way, which indicates that the undulation of the dorsal fin can simultaneously provide bidirectional propulsive and maneuvering forces with the help of the tail fin. A high-resolution Charge-Coupled Device （CCD） imaging camera system is used to record kinematics of steady swimming as well as maneuvering in G. niloticus. Based on experimental data, this paper discusses the kinematics （cruising speed, wave speed, cycle frequency, amplitude, lateral displacement） of forward as well as backward swimming and maneuvering. During forward swimming, the propulsive force is generated mainly by undulations of the dorsal fin while the body axis remains straight. The kinematic parameters （wave speed, wavelength, cycle frequency, amplitude） have statistically significant correlations with cruising speed. In addition, the yaw at the head is minimal during steady swimming. From experimental data, the maximal lateral displacement of head is not more than 1% of the body length, while the maximal lateral displacement of the whole body is not more than 5% of the body length. Another important feature is that G. niloticus swims backwards using an undulatory mechanism that resembles the forward undulatory swimming mechanism. In backward swimming, the increase of lateral displacement of the head is comparatively significant; the amplitude profiles of the propulsive wave along the dorsal fin are significantly different from those in forward swimming. When G. niloticus does fast maneuvering, its body is first bent into either a C shape or an S shape, then it is rapidly unwound in a travelling wave fashion. It rarely maneuvers without the help of the tail fin and body bending.     

Computational approaches to motor control

New concepts and computational models that integrate behavioral and neurophysiological observations have addressed several of the most fundamental long-standing problems in motor control. These problems include the selection of particular trajectories among the large number of possibilities, the solution of inverse kinematics and dynamics problems, motor adaptation and the learning of sequential behaviors.     

Upper limb kinematical analysis of an elite weight lifter in the squat snatch

The kinematical parameters such as translational acceleration and angular acceleration in the upper limb of a weightlifter may change regularly during different phases of squat snatch. This study aims to make this question clear. At first, the joint coordinate system (JCS) of human upper limb based on the anatomical landmarks is defined. Then a novel method for calculating the kinematical parameters was brought forward, which was based on analyzing the relative position of the JCS to world coordinate system during an instantaneous situation and the relationship among each JCS at different times during squat snatch. Motion capture system is used to gather the data of the upper limb in an elite weightlifter during squat snatch (the mass of the barbell is 20 kg) and the method mentioned before is applied to analyze the data. Finally, the law of the change of kinematical parameters in each phase of squat snatch is found.     

A real-time computational model for estimating kinematics of ankle ligaments

Background: An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. Method: An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot–ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. Results: The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. Conclusions: This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.     

A simple,reliable method to determine the mean gait speed using heel markers on a treadmill

Gait speed is an essential parameter of gait analysis. Our study proposed a simple and accurate method to extract a mean gait speed during walking on a treadmill using only kinematic data from markers placed on the heels of the participants’ feet. This method provided an attractive, simple method that remains resistant to errors in treadmill calibration. In addition, this method required only two markers, since heel markers are essential to gait analysis, and the proposed method is robust enough to differentiate among various gait speeds (mean error <1%).     

Effect of shoulder model complexity in upper-body kinematics analysis of the golf swing

The golf swing is a complex full body movement during which the spine and shoulders are highly involved. In order to determine shoulder kinematics during this movement, multibody kinematics optimization (MKO) can be recommended to limit the effect of the soft tissue artifact and to avoid joint dislocations or bone penetration in reconstructed kinematics. Classically, in golf biomechanics research, the shoulder is represented by a 3 degrees-of-freedom model representing the glenohumeral joint. More complex and physiological models are already provided in the scientific literature. Particularly, the model used in this study was a full body model and also described motions of clavicles and scapulae. This study aimed at quantifying the effect of utilizing a more complex and physiological shoulder model when studying the golf swing. Results obtained on 20 golfers showed that a more complex and physiologically-accurate model can more efficiently track experimental markers, which resulted in differences in joint kinematics. Hence, the model with 3 degrees-of-freedom between the humerus and the thorax may be inadequate when combined with MKO and a more physiological model would be beneficial. Finally, results would also be improved through a subject-specific approach for the determination of the segment lengths.