Gait data generation using generative adversarial network based on human dynamics
Various training techniques have been devised to capture motion data during real-time walking and provide feedback to trainees, allowing them to adjust their gait to align the measured gait parameters with target values. However, these methods may not suit all individuals owing to physical differenc...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | Japanese |
| Published: |
The Japan Society of Mechanical Engineers
2025-05-01
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| Series: | Nihon Kikai Gakkai ronbunshu |
| Subjects: | |
| Online Access: | https://www.jstage.jst.go.jp/article/transjsme/91/946/91_25-00003/_pdf/-char/en |
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