Whole-body Motion Research Articles

Dance expertise modulates visual sensitivity to complex biological movements

Motor resonance processes that occur when observing an individual perform an action may be modulated by acquired visuomotor expertise. We used the event-related potential (EEG/ERP) technique to investigate the ability to automatically recognize a subtle difference between very similar novel contemporary dance movements. Twelve professional dancers and twelve non-dancers were shown 212 pairs of videos of complex whole-body movements that lasted 3s. The second of each pair was the repetition of the previous movement or a slight variation of it (deviance). The participants were engaged in a secondary attentional task. Modulation of a larger centro-parietal N400 effect and a reduction of the Late Positivity amplitude (repetition suppression effect) were identified in response to deviant stimuli only in the dancers. Source reconstruction (swLORETA) showed activations in biological motion, body and face processing related areas, and fronto-parietal and limbic systems. The current findings provide evidence that acquired dance expertise modifies the ability to visually code whole-body complex movements.

Perception of the dynamic visual vertical during sinusoidal linear motion.

The vestibular system provides information for spatial orientation. However, this information is ambiguous: because the otoliths sense the gravitoinertial force, they cannot distinguish gravitational and inertial components. As a consequence, prolonged linear acceleration of the head can be interpreted as tilt, referred to as the somatogravic effect. Previous modeling work suggests that the brain disambiguates the otolith signal according to the rules of Bayesian inference, combining noisy canal cues with the a priori assumption that prolonged linear accelerations are unlikely. Within this modeling framework the noise of the vestibular signals affects the dynamic characteristics of the tilt percept during linear whole-body motion. To test this prediction, we devised a novel paradigm to psychometrically characterize the dynamic visual vertical-as a proxy for the tilt percept-during passive sinusoidal linear motion along the interaural axis (0.33 Hz motion frequency, 1.75 m/s2 peak acceleration, 80 cm displacement). While subjects (n=10) kept fixation on a central body-fixed light, a line was briefly flashed (5 ms) at different phases of the motion, the orientation of which had to be judged relative to gravity. Consistent with the model's prediction, subjects showed a phase-dependent modulation of the dynamic visual vertical, with a subject-specific phase shift with respect to the imposed acceleration signal. The magnitude of this modulation was smaller than predicted, suggesting a contribution of nonvestibular signals to the dynamic visual vertical. Despite their dampening effect, our findings may point to a link between the noise components in the vestibular system and the characteristics of dynamic visual vertical.NEW & NOTEWORTHY A fundamental question in neuroscience is how the brain processes vestibular signals to infer the orientation of the body and objects in space. We show that, under sinusoidal linear motion, systematic error patterns appear in the disambiguation of linear acceleration and spatial orientation. We discuss the dynamics of these illusory percepts in terms of a dynamic Bayesian model that combines uncertainty in the vestibular signals with priors based on the natural statistics of head motion.

Tracking the Cheetah Tail Using Animal-Borne Cameras, GPS, and an IMU

The cheetah (Acinonyx Jubatus) is the fastest terrestrial animal and is also highly maneuverable. An investigation into the whole-body motion dynamics of this specialized predator will illuminate various factors that influence and affect performance in legged animals as well as provide insight for the design of future bio-inspired robots. Presently, animal sensor collars can capture the gross animal behavior successfully but do not provide information about the animal's complete motion. Here, in an effort towards whole-body motion estimation, we demonstrate the use of animal mounted cameras, as well as the sensor suite of a smartphone that are attached to captive cheetahs during maneuvers. The various sensors are fused by an Extended Kalman Smoother (EKS) to provide high-bandwidth state estimates of the position, velocity, and acceleration of the cheetah spine and tail.

A topological approach for human movement classification and anticipation

The motion capture systems are increasingly used for biomedical purposes. In order to recognize and classify the movements, however whole-body movements using passive markers, generate a huge amount of data. Can topological data analysis methods improve the recognition of movements? Can we use the results of this analysis combined with particular types of neural networks to anticipate the continuation of a movement?

Multi-contact locomotion using a contact graph with feasibility predictors

Multi-contact locomotion that uses both the hands and feet in a complex environment remains a challenging problem in computer animation. To address this problem, we present a contact graph, which is a motion graph augmented by learned feasibility predictors, namely contact spaces and an occupancy estimator, for a motion clip in each graph node. By estimating the feasibilities of candidate contact points that can be reached by modifying a motion clip, the predictors allow us to find contact points that are likely to be valid and natural before attempting to generate the actual motion for the contact points. The contact graph thus enables the efficient generation of multi-contact motion in two steps: planning contact points to the goal and then generating the whole-body motion. We demonstrate the effectiveness of our method by creating several climbing motions in complex and cluttered environments by using only a small number of motion samples.

Handedness effects of imagined fine motor movements

ABSTRACTPrevious studies of movement imagery have found inter-individual differences in the ability to imagine whole-body movements. The majority of these studies have used subjective scales to measure imagery ability, which may be confounded by other factors related to effort. Madan and Singhal [2013. Introducing TAMI: An objective test of ability in movement imagery. Journal of Motor Behavior, 45(2), 153–166. doi:10.1080/00222895.2013.763764] developed the Test of Ability in Movement Imagery (TAMI) to address these confounds by using a multiple-choice format with objectively correct responses. Here we developed a novel movement imagery questionnaire targeted at assessing movement imagery of fine-motor hand movements. This questionnaire included two subscales: Functionally-involved Movement (i.e., tool-related) and Isolated Movement (i.e., hand-only). Hand-dominance effects were observed, such that right-handed participants were significantly better at responding to right-hand questions compared to left-hand questions for both imagery types. A stronger handedness effect was observed for Functionally-involved Movement imagery, and it did not correlate with the Edinburgh Handedness Inventory. We propose that the Functionally-involved Movement imagery subscale provides an objective hand imagery test that induces egocentric spatial processing and a greater involvement of memory processes, potentially providing a better skill-based measure of handedness.

Multi-Contact Locomotion Using a Contact Graph with Feasibility Predictors

Multi-contact locomotion that uses both the hands and feet in a complex environment remains a challenging problem in computer animation. To address this problem, we present a contact graph, which is a motion graph augmented by learned feasibility predictors, namely contact spaces and an occupancy estimator, for a motion clip in each graph node. By estimating the feasibilities of candidate contact points that can be reached by modifying a motion clip, the predictors allow us to find contact points that are likely to be valid and natural before attempting to generate the actual motion for the contact points. The contact graph thus enables the efficient generation of multi-contact motion in two steps: planning contact points to the goal and then generating the whole-body motion. We demonstrate the effectiveness of our method by creating several climbing motions in complex and cluttered environments by using only a small number of motion samples.

Trajectory Optimization Through Contacts and Automatic Gait Discovery for Quadrupeds

In this letter, we present a trajectory optimization framework for whole-body motion planning through contacts. We demonstrate how the proposed approach can be applied to automatically discover different gaits and dynamic motions on a quadruped robot. In contrast to most previous methods, we do not prespecify contact-switches, -timings, -points or gait patterns, but they are a direct outcome of the optimization. Furthermore, we optimize over the entire dynamics of the robot, which enables the optimizer to fully leverage the capabilities of the robot. To illustrate the spectrum of achievable motions, we show eight different tasks, which would require very different control structures when solved with state-of-the-art methods. Using our trajectory optimization approach, we are solving each task with a simple, high level cost function and without any changes in the control structure. Furthermore, we fully integrate our approach with the robot's control and estimation framework such that we are able to run the optimization online. Through several hardware experiments, we show that the optimized trajectories and control inputs can be directly applied to physical systems.

Wireless Kinect-NAO Framework Based on Takagi-Sugeno Fuzzy Inference System

Abstract In the context of learning new skills by imitation for children with special educational needs, we propose Wireless Kinect-NAO Framework (WKNF) for robot teleoperation in real time based on Takagi-Sugeno (T-S) Fuzzy Inference System. The new solutions here are related to complex whole-body motion retargeting, standing body stabilization, view invariance and smoothness of robot motions. The raw depth Kinect data are fuzzified and processed by median filter. The joint angles estimation for motion mapping of Human to NAO movements is based on fuzzy logic and featured angles rather than direct angles are calculated by Inverse Kinematics due to differences in the human and robot kinematics. During the joint angles calculation nonlinearities are observed as a result of ambiguity of Kinect 3D joint coordinates in different offsets. NAO kinematic limitations and nonlinearities in workspace are decomposed and linearly approximated by T-S fuzzy rules of zero and first order that have local support in 2D projections. To prevent the robot to fall down, the center of mass is considered in order NAO to stay within a support and safe polygon. The feasibility of the proposed framework has been proven by real experiments.

Long-term test-retest reliability of event-related potential (ERP) recordings during treadmill walking using the mobile brain/body imaging (MoBI) approach

Advancements in acquisition technology and signal-processing techniques have spurred numerous recent investigations on the electro-cortical signals generated during whole-body motion. This approach, termed Mobile Brain/Body Imaging (MoBI), has the potential to elucidate the neural correlates of perceptual and cognitive processes during real-life activities, such as locomotion. However, as of yet, no one has assessed the long-term stability of event-related potentials (ERPs) recorded under these conditions. Therefore, the objective of the current study was to evaluate the test-retest reliability of cognitive ERPs recorded while walking. High-density EEG was acquired from 12 young adults on two occasions, separated by an average of 2.3years, as they performed a Go/No-Go response inhibition paradigm. During each testing session, participants performed the task while walking on a treadmill and seated. Using the intraclass correlation coefficient (ICC) as a measure of agreement, we focused on two well-established neurophysiological correlates of cognitive control, the N2 and P3 ERPs. Following ICA-based artifact rejection, the earlier N2 yielded good to excellent levels of reliability for both amplitude and latency, while measurements for the later P3 component were generally less robust but still indicative of adequate to good levels of stability. Interestingly, the N2 was more consistent between walking sessions, compared to sitting, for both hits and correct rejection trials. In contrast, the P3 waveform tended to have a higher degree of consistency during sitting conditions. Overall, these results suggest that the electro-cortical signals obtained during active walking are representative of stable indices of neurophysiological function.

Does the anthropometric model influence whole-body center of mass calculations in gait?

Examining whole-body center of mass (COM) motion is one of method being used to quantify dynamic balance and energy during gait. One common method for estimating the COM position is to apply an anthropometric model to a marker set and calculate the weighted sum from known segmental COM positions. Several anthropometric models are available to perform such a calculation. However, to date there has been no study of how the anthropometric model affects whole-body COM calculations during gait. This information is pertinent to researchers because the choice of anthropometric model may influence gait research findings and currently the trend is to consistently use a single model. In this study we analyzed a single stride of gait data from 103 young adult participants. We compared the whole-body COM motion calculated from 4 different anthropometric models (Plagenhoef et al., 1983; Winter, 1990; de Leva, 1996; Pavol et al., 2002). We found that anterior-posterior motion calculations are relatively unaffected by the anthropometric model. However, medial-lateral and vertical motions are significantly affected by the use of different anthropometric models. Our findings suggest that the researcher carefully choose an anthropometric model to fit their study populations when interested in medial-lateral or vertical motions of the COM. Our data can provide researchers a priori information on the model determination depending on the particular variable and how conservative they may want to be with COM comparisons between groups.

Why pace? The influence of social, housing, management, life history, and demographic characteristics on locomotor stereotypy in zoo elephants

Stereotypic behaviors (SB) are common in zoo-housed elephants, and these behaviors can be performed at high rates. Elephants perform different SB forms (e.g., weaving, pacing), but no published studies have evaluated the factors contributing to the development or performance of these different forms. Instead, as with most SB studies across species, elephant studies have relied on analyses that aggregate all SB forms, which limits the development and testing of form-specific hypotheses or abatement practices. Our objectives were to characterize the SB forms of North American zoo elephants and use multivariable epidemiological models to test form-specific hypotheses. We videotaped 77 elephants (African: N=5 males, 31 females; Asian N=8 males, 33 females) at 39 zoos who performed SBs and used a novel classification scheme and 5-min instantaneous samples to characterize their SB forms. Locomotor and whole-body SBs were the most common, but most elephants who performed locomotor SBs also performed whole-body SBs. Thus, we characterized each elephant according to whether it included locomotion in its SB repertoire [Locomotor Presence (LP)] or only whole-body movements. We used binomial regression models fitted with generalized estimating equations to test hypotheses about which of 26 social, housing, management, life history, and demographic variables were most associated with LP. The odds of LP increased by 26% for every 10% increase in time housed separately (odds ratio=1.026, p=0.04), 96.2% for every additional social group with which an elephant had contact (odds ratio=1.962, p=0.01), and 46% for every 10% increase in time housed indoors (odds ratio=1.046, p=0.01). Age was non-significantly confounded with all three variables. We hypothesize that the social variables in our models increase LP risk because they are associated with uncontrollable social group changes, anticipation of potentially rewarding social experiences, or the frustration of social behaviors. The housing variable included in our model likely increases LP risk because indoor spaces are less complex, resulting in the channeling of walking or social avoidance behaviors into more simplistic movements. Overall, our results suggest that elephant managers may best be able to prevent locomotor SB by enhancing their elephants’ social environment and the spatial complexity of their enclosures. Future research should focus on determining whether addressing the risk factors for LP results in less frequent performance and identifying other temporally proximate eliciting factors.

Active balance of humanoid movement based on dynamic task-prior system

To maintain human-like active balance in a humanoid robot, this article proposes a dynamic priority-based multitask algorithm to avoid self-collision during highly complex robotic whole-body motions and rebalance after external disturbance using momentum compensation strategies. On the one hand, the conflict between self-collision and self-balance constraints in task-space merging with end-effector tracking tasks are considered in the multitask algorithm to improve the robot’s balance. On the other hand, for self-balance during the robot’s movement, momentum compensation is considered as one task and utilized to reject unknown disturbances. Two strategies are put forward to restrain the sudden change in momentum. One is to calculate the correction in the joint space with the resolved momentum control (RMC) method; the other is to add an end-effector tracking motion in the task space. Simulations and experiments on a full-body humanoid robot validate the effectiveness of the proposed method. Experiments on both a simulation and a full-body humanoid are designed to validate the task-prior algorithm. With the proposed method, the humanoid robot succeeds in avoiding self-collision during movement and is able to rectify itself to the preplanned steady stance while encountering undefined external forces.

Effects Of High-intensity Functional Circuit Training On Motor Function And Exercise Motivation

PURPOSE: Only a small share of the world population meets current physical activity guidelines, which recommend regular engagement in endurance, strength, and neuromotor exercise. As lack of time has been reported to constitute a major cause of inactivity, multidimensional methods with short training duration might be a promising alternative to classical, volume-oriented approaches. This randomized-controlled trial aimed to examine the effects of a high-intensity functional circuit (HIFCT) training program on motor function and motivation to exercise in healthy, untrained adults. METHODS: 25 inactive participants (26±5 yrs, 9♂) were randomly allocated to two groups. The intervention group (HIFCT, n=15) 3×/wk performed functional exercises incorporating complex whole-body movements (e.g. Squats, Step-Ups, Burpees) in a circuit format. The 15 min workouts were composed of repetitive 20s all-out bouts with 10s breaks. In the comparison group (moderate aerobic exercise, MAE) the participants walked 3×/wk for 50 min at moderate intensity (progressively increased from 50 to 60% of the individual heart rate reserve). Motor outcomes, measured prior to and after the six-week intervention, were cycling capacity (maximum work load), dynamic maximum strength (leg and shoulder press), postural control (force plate), and jump capacity (reactive strength index, counter-movement jump, single leg hop for distance). Motivation to exercise was assessed using the self-concordance index. Systematic group differences were detected with the Mann-Whitney-U-test (α=.05). RESULTS: In comparison to MAE, HIFCT increased maximum leg strength (difference of relative median pre-post changes between groups: 6%), shoulder strength (8.4%), and cycling workload (6.5%; p<.05). No differences were found for postural control and jump capacity (p>.05). Although not statistically significant, there was a tendency for increased self-concordance following HIFCT (p<.1) CONCLUSION: Despite considerably shorter training duration, HIFCT enhances motor function in healthy untrained adults more effectively than MAE. It might moreover be better suited to motivate inactive people to engage in regular activity. Further research should thus investigate long-term adherence to the program and its effectivity in other settings.

The Impact of Oral Promethazine on Human Whole-Body Motion Perceptual Thresholds.

Despite the widespread treatment of motion sickness symptoms using drugs and the involvement of the vestibular system in motion sickness, little is known about the effects of anti-motion sickness drugs on vestibular perception. In particular, the impact of oral promethazine, widely used for treating motion sickness, on vestibular perceptual thresholds has not previously been quantified. We examined whether promethazine (25mg) alters vestibular perceptual thresholds in a counterbalanced, double-blind, within-subject study. Thresholds were determined using a direction recognition task (left vs. right) for whole-body yaw rotation, y-translation (interaural), and roll tilt passive, self-motions. Roll tilt thresholds were 31% higher after ingestion of promethazine (P=0.005). There were no statistically significant changes in yaw rotation and y-translation thresholds. This worsening of precision could have functional implications, e.g., during driving, bicycling, and piloting tasks. Differing results from some past studies of promethazine on the vestibulo-ocular reflex emphasize the need to study motion perception in addition to motor responses.

Multi-Contact Locomotion Using a Contact Graph with Feasibility Predictors

Multi-contact locomotion that uses both the hands and feet in a complex environment remains a challenging problem in computer animation. To address this problem, we present a contact graph, which is a motion graph augmented by learned feasibility predictors, namely contact spaces and an occupancy estimator, for a motion clip in each graph node. By estimating the feasibilities of candidate contact points that can be reached by modifying a motion clip, the predictors allow us to find contact points that are likely to be valid and natural before attempting to generate the actual motion for the contact points. The contact graph thus enables the efficient generation of multi-contact motion in two steps: planning contact points to the goal and then generating the whole-body motion. We demonstrate the effectiveness of our method by creating several climbing motions in complex and cluttered environments by using only a small number of motion samples.

Dynamic balance preservation and prevention of sliding for humanoid robots in the presence of multiple spatial contacts

The main indicator of dynamic balance is the $\mathit{ZMP}$ . Its original notion assumes that both feet of the robot are in contact with the flat horizontal surface (all contacts are in the same plane) and that the friction is high enough so that sliding does not occur. With increasing capabilities of humanoid robots and the higher complexity of the motion that needs to be performed, these assumptions might not hold. Having in mind that the system is dynamically balanced if there is no rotation about the edges of the feet and if the feet do not slide, we propose a novel approach for testing the dynamic balance of bipedal robots, by using linear contact wrench conditions compiled in a single matrix (Dynamic Balance Matrix). The proposed approach has wide applicability since it can be used to check the stability of different kinds of contacts (including point, line, and surface) with arbitrary perimeter shapes. Motion feasibility conditions are derived on the basis of the conditions which the wrench of each contact has to satisfy. The approach was tested by simulation in two scenarios: biped climbing up and walking sideways on the inclined flat surface which is too steep for a regular walk without additional support. The whole-body motion was synthesized and performed using a generalized task prioritization framework.

Does movement influence representations of time and space?

Embodied cognition posits that abstract conceptual knowledge such as mental representations of time and space are at least partially grounded in sensorimotor experiences. If true, then the execution of whole-body movements should result in modulations of temporal and spatial reference frames. To scrutinize this hypothesis, in two experiments participants either walked forward, backward or stood on a treadmill and responded either to an ambiguous temporal question (Experiment 1) or an ambiguous spatial question (Experiment 2) at the end of the walking manipulation. Results confirmed the ambiguousness of the questions in the control condition. Nevertheless, despite large power, walking forward or backward did not influence the answers or response times to the temporal (Experiment 1) or spatial (Experiment 2) question. A follow-up Experiment 3 indicated that this is also true for walking actively (or passively) in free space (as opposed to a treadmill). We explore possible reasons for the null-finding as concerns the modulation of temporal and spatial reference frames by movements and we critically discuss the methodological and theoretical implications.

Design and Experimental Evaluation of a Fast Torque-Controlled Hydraulic Humanoid Robot

This paper reports the design and control of a fast torque-controlled hydraulic humanoid robot, TaeMu. The robot has 15 active joints that are all driven by hydraulic servocylinders with an external hydraulic power supply. The 1377-mm tall robot has a three-axis active torso used for static and dynamic balancing. It weighs 72.3 kg including a dummy weight stand for the arms. Its lightweight design with carbon-fiber-reinforced plastic allows the legs to have a similar mass distribution to that of human legs. We present the details of the hardware design including the hydraulic actuator selection, mechanism, and control systems, as well as the passivity-based controller design for joint torque control and whole-body motion control. We present experimentally obtained results, such as speed testing, basic torque control testing, full-body compliant balancing with attitude regulation/tracking, and balanced full-squat motions. The experimentally obtained results and estimated joint specification imply the high potential of the robot to perform human-like motions if the researchers can invent proper control algorithms.

Accuracy and repeatability of single-pose calibration of inertial measurement units for whole-body motion analysis

Portable inertial measurement units (IMUs) are suitable for motion analysis outside the laboratory. However, IMUs depend on the calibration of each body segment to measure human movement. Different calibration approaches have been developed for simplicity of use or similarity to laboratory motion analysis, but they have not been extensively examined. The main objective of the study was to determine the accuracy and repeatability of two common single-pose calibrations (N-pose and T-pose) under different conditions of placement (self-placement and passive placement), as well as their similarity to laboratory analysis based on anatomical landmarks. A further aim of the study was to develop two additional single-pose calibrations (chair-pose and stool-pose) and determine their accuracy and repeatability. Postures and movements of 12 healthy participants were recorded simultaneously with a full-body IMU suit and an optoelectronic system as the criterion measure. Three repetitions of the T-pose and the N-pose were executed by self-placement and passive placement, and three repetitions of the chair-pose and stool-pose were also performed. Repeatability for each single-pose calibration showed an average intraclass correlation coefficient for all axes and joints between 0.90 and 0.94 and a standard error of measurement between 1.5° and 2.1°. The T-pose with passive placement is recommended to reduce longitudinal axis offset error and to increase similarity to laboratory motion analysis. Finally, the chair-pose obtained the least longitudinal axis offset error amongst the tested poses, which shows potential for IMU calibration.