Abstract
Identifying the current gait phase is a key in the control of ankle-foot orthoses, which assist ankle motion during walking. We address the problem to estimate whether the foot is in a swing or stance phase only from the ankle angle. A recurrent neural network with long-short-term-memory architecture is developed and evaluated with experimental data.
Original language | English |
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Pages (from-to) | 291-296 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 53 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2020 |
Event | 3rd IFAC Workshop on Cyber-Physical and Human Systems, CPHS 2020 - Beijing, China Duration: Dec 3 2020 → Dec 5 2020 |
Keywords
- Ankle-foot orthosis
- gait analysis
- long short-term memory
- neural networks
ASJC Scopus subject areas
- Control and Systems Engineering