Measuring Behavior using Motion Capture

Motion capture systems, using optical, magnetic or mechanical sensors are now widely used to record\ud human motion. Motion capture provides us with precise measurements of human motion at a very high\ud recording frequency and accuracy, resulting in a massive amount of movement data on several joints of the\ud body or markers of the face. But how do we make sure that we record the right things? And how can we\ud correctly interpret the recorded data?\ud In this multi-disciplinary symposium, speakers from the field of biomechanics, computer animation, human\ud computer interaction and behavior science come together to discus their methods to both record motion and\ud to extract useful properties from the data. In these fields, the construction of human movement models from\ud motion capture data is the focal point, although the application of such models differs per field. Such\ud models can be used to generate and evaluate highly adaptable and believable animation on virtual\ud characters in computer animation, to explore the details of gesture interaction in Human Computer\ud Interaction applications, to identify patterns related to affective states or to find biomechanical properties of\ud human movement

Center of mass velocity-based predictions in balance recovery following pelvis perturbations during human walking

In many simple walking models foot placement dictates the center of pressure location and ground reaction force components, whereas humans can modulate these aspects after foot contact. Because of the differences, it is unclear to what extend predictions made by models are valid for human walking. Yet, both model simulations and human experimental data have previously indicated that the center of mass (COM) velocity plays an important role in regulating stable walking.\ud \ud Here, perturbed human walking was studied for the relation of the horizontal COM velocity at heel strike and toe-off with the foot placement location relative to the COM, the forthcoming center of pressure location relative to the COM, and the ground reaction forces. Ten healthy subjects received various magnitude mediolateral and anteroposterior pelvis perturbations at toe-off, during 0.63 and 1.25 m s−1 treadmill walking.\ud \ud At heel strike after the perturbation, recovery from mediolateral perturbations involved mediolateral foot placement adjustments proportional to the mediolateral COM velocity. In contrast, for anteroposterior perturbations no significant anteroposterior foot placement adjustment occurred at this heel strike. However, in both directions the COM velocity at heel strike related linearly to the center of pressure location at the subsequent toe-off. This relation was affected by the walking speed and was, for the slow speed, in line with a COM velocity based control strategy previously applied by others in a linear inverted pendulum model. Finally, changes in gait phase durations suggest that the timing of actions could play an important role during the perturbation recovery

The PREHydrA:A Passive Return, High Force Density, Electro-Hydrostatic Actuator Concept for Wearable Robotics

This letter presents the Passive Return Electro-Hydrostatic Actuator (PREHydrA), an actuator for use in wearable robotics. It eliminates conventional hydraulic systems’ fluid supply and valves, potentially making it lighter, more efficient, and simpler. It also avoids the configuration-dependent friction of Bowden cable transmissions. A physical port-based network model was created of the PREHydrA that predicts force tracking with a maximum error of about 4 N. Closed loop output force control was used in experiments to obtain a mean absolute tracking error below 4 N for force references from 300 N amplitude at 0.5 Hz to 20 N amplitude at 10 Hz. These forces, frequencies, and corresponding velocities (up to 0.47 m/s) demonstrate that the PREHydrA's performance is sufficient for many wearable applications

Changes in circle area after gravity compensation training in chronic stroke patients

After a stroke, many people experience difficulties to selectively activate muscles. As a result many patients move the affected arm in stereotypical patterns. Shoulder abduction is often accompanied by elbow flexion, reducing the ability to extend the elbow. This involuntary coupling reduces the patient's active range of motion. Gravity compensation reduces the activation level of shoulder abductors which limits the amount of coupled elbow flexion. As a result, stroke patients can instantaneously increase their active range of motion [1]. The objective of the present study is to examine whether training in a gravity compensated environment can also lead to an increased range of motion in an unsupported environment. Parts of this work have been presented at EMBC2009, Minneapolis, USA