Currently, the replacement of traditional rehabilitation therapists with lower limb rehabilitation exoskeleton robots has become a trend. However, rehabilitation hospitals lack a comprehensive lower limb rehabilitation exoskeleton robot medical monitoring system to enable data analysis and management of the patient’s rehabilitation process. Therefore, this paper focuses on the rehabilitation lower limb exoskeleton robots and designs a cloud-edge-end collaborative monitoring system, and establishes an experimental platform to conduct related experiments. The aim is to achieve monitoring of the rehabilitation hospital environment and the lower limb rehabilitation exoskeleton robots, and to manage the data of patients’ rehabilitation process through the platform website. Experimental results indicate that the monitoring system designed in this paper meets application requirements and can present the data generated during the patient’s rehabilitation process in a web format to users or therapists.

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Design of Cloud-Edge-End Collaborative Monitoring System for Lower Limb Rehabilitation Exoskeleton

  • Ting Zhang,
  • Mengfan Zhang,
  • Xiaoqing Yuan

摘要

Currently, the replacement of traditional rehabilitation therapists with lower limb rehabilitation exoskeleton robots has become a trend. However, rehabilitation hospitals lack a comprehensive lower limb rehabilitation exoskeleton robot medical monitoring system to enable data analysis and management of the patient’s rehabilitation process. Therefore, this paper focuses on the rehabilitation lower limb exoskeleton robots and designs a cloud-edge-end collaborative monitoring system, and establishes an experimental platform to conduct related experiments. The aim is to achieve monitoring of the rehabilitation hospital environment and the lower limb rehabilitation exoskeleton robots, and to manage the data of patients’ rehabilitation process through the platform website. Experimental results indicate that the monitoring system designed in this paper meets application requirements and can present the data generated during the patient’s rehabilitation process in a web format to users or therapists.