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Three-dimensional motion analysis of upright bipedal walking android model
Kouji Sanaka1, Yusuke Sekiguchi2, Daisuke Kurosawa3
1Biological Mechanics Laboratory, 2-2221-3 Iwasakidai, Nisshin, Aichi 470-0135, Japan; Japan Sacroiliac Joint and Low Back Pain Center, JCHO Sendai Hospital, 2-1-1 Murasakiyama, Izumi-ku, Sendai, Miyagi 981-3281, Japan.
A trunk-driven bipedal model partially replicated human center of pressure trajectories during walking. This trunk-driven approach offers new insights for robotic gait analysis and biomechanics research.
Area of Science:
- Robotics
- Biomechanics
- Human Gait Analysis
Background:
- A bipedal android model driven by trunk motion via psoas major contractions was previously developed.
- A mechanically stabilized principle model was created to preserve gait mechanics and enable autonomous bipedal walking.
- This model addressed knee and foot-ankle joint instability for reliable center of pressure measurement.
Purpose of the Study:
- To investigate if the center of pressure (COP) trajectory generated by a trunk-driven bipedal model approximates that of humans.
- To compare the COP trajectory of the principle model with that of healthy human subjects.
Main Methods:
- Utilized a three-dimensional gait analysis system.
- Attached 35 markers to healthy subjects and 24 markers to the principle model.
- Captured and analyzed ground reaction force data, comparing the right foot's COP trajectory during the stance phase.
Main Results:
- COP trajectories were generally similar during double-limb stance and single-limb support phases.
- The principle model exhibited a backward deviation of COP during single-limb support.
- Differences were attributed to shorter stride length, slower walking speed, and prolonged single-limb support in the model.
Conclusions:
- The principle model demonstrates trunk-driven motion with passive leg swing, partially replicating human COP trajectories.
- This contrasts with conventional gait analysis assuming passive trunk motion.
- A trunk-driven approach may offer valuable insights for robotic gait analysis and biomechanics.
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