- Design and Development of

- Omegabot: Inchworm inspired

- Large deformable morphing

- Wearable robotic hand
- Hands on surgical robot:
   Shared control system
- Situation Understanding for
   Smart Devices

- Wireless Camera Sensor
   Networks Technology

- Mobile Sensor Networks:
   Algorithms and Applications
- Whole-Body Control Framework
    for Humanoid Robot

- Walking Pattern Generation for
   Humanoid Robot

- Robot Hand Control
- Quadruped Robot Control with
   Whole-Body Control Framework

- Human Gait Analysis using
   3D Motion Capture
- Coordination of multiple robots
- Flocking and consensus
- Vision-based guidance and

- Online collision avoidance for
   mobile robots

- Wireless sensor network
- Aerial Manipulation
- Haptics/VR
- Autonomous Mobility
- Telerobotics
- Mechanics/Control
- Industrial Control
- Mobile Manipulation
- Simultaneous Visual and
   Inertia Calibration

- Mechanics of Closed Chains
- Motion Optimization via
   Nonlinear Dimension

- Probabilistic Optimal Planning
   Algorithm for Minimum
   upstream Motions

- Automated Plug-In Recharging
   System for Hybrid Electric
Human Gait Analysis using 3D Motion Capture
This study addresses postural changes during human gait caused by different heel heights, and describes the causal relationship of the changes due to high heels. The experiment was designed in which two different shoe heel heights were used for walking (1 cm, 9.8 cm), and twelve women participated in the test. The trajectory of 35 points on the body was tracked during the gait. From this trajectory information, joint angle and stride pattern were calculated. These three features were analyzed to determine postural changes that occurred from the effects of high heels. The body parts showing notable differences with high-heeled walking are described in the results. The causal relationship between high heels and postural changes in gait is established to clarify the results. Two major factors explain the reason for the changes during a high-heeled gait, which are muscle discomfort and dynamic instability. This study may help to adapt the effects of high heels to several applications such as gait detection, human recognition, and human gait motion imitation for humanoid robots and character animation.

ResultThe stride ratio(SR), which is stride length divided by stride time, decreased because of the reduced stride length and this result is consistent with the findings by Merrifield and Sato et al. The support time ratio(STR), which is double support time divided by single support time, was 1.5 times greater with high heels than flat shoes.

The ankle dorsi/plantar-flexion had completely different averages and the reduced range of motion. The knee flexion had a greater maximum point at the stance phase, but a smaller maximum point at the swing phase with high heels. Hip flexion shows the slightly extended range of motion with high heels. Spine tilt in sagittal plane and rotation about vertical axis became greater during high-heeled gait. The results on the knee flexion and spine angle are consistent with the study by Opila et al.

The trajectories of the body parts were observed in the X-axis (anterior-posterior), Y-axis (lateral), and Z-axis (vertical). The ankle trajectory in the Z-axis shows the narrower motion with high heels. On the other hand, the knee trajectory had the opposite results to the ankle. The pelvis trajectory in Z-axis showed the greater fluctuation at high-heeled gait, and this effect was continuously observed in the upper body trajectories. The ankle trajectory in X-axis indicated the slightly reduced movement with high heels. A unique feature appeared at the knee along the X-axis, which had a different temporal peak point. Along the Y-axis, no specific changes were found.

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