Abstract
Due to the current focus of research on ankle rehabilitation robots on structural design, there is still limited research on ankle human–machine interaction technology. In order to enable rehabilitation robots to conduct personalized rehabilitation training based on patients’ ankle movement intentions, we propose a new ankle motion recognition method based on plantar pressure. First, we designed a plantar pressure collection system based on array sensors. Then, we collected nine types of ankle joint motion pressure data from five volunteers and conducted algorithm selection, data processing, and algorithm optimization. Finally, we proposed a small sample optimization algorithm based on support vector machine, with an average recognition rate of 93.16%. The recognition method proposed in this paper can be combined with ankle rehabilitation robots to achieve active rehabilitation functions, laying the foundation for the clinical application of active rehabilitation technology.
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