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Exoskeleton cloud-brain platform and its application in safety assessment
Robotic Intelligence and Automation ( IF 2.1 ) Pub Date : 2021-06-03 , DOI: 10.1108/aa-11-2020-0184
Fashu Xu , Rui Huang , Hong Cheng , Min Fan , Jing Qiu

Purpose

This paper aims at the problem of attaching the data of doctors, patients and the real-time sensor data of the exoskeleton to the cloud in intelligent rehabilitation applications. This study designed the exoskeleton cloud-brain platform and validated its safety assessment.

Design/methodology/approach

According to the dimension of data and the transmission speed, this paper implements a three-layer cloud-brain platform of exoskeleton based on Alibaba Cloud's Lambda-like architecture. At the same time, given the human–machine safety status detection problem of the exoskeleton, this paper built a personalized machine-learning safety detection module for users with the multi-dimensional sensor data cloned by the cloud-brain platform. This module includes an abnormality detection model, prediction model and state classification model of the human–machine state.

Findings

These functions of the exoskeleton cloud-brain and the algorithms based on it were validated by the experiments, they meet the needs of use.

Originality/value

This thesis innovatively proposes a cloud-brain platform for exoskeletons, beginning the digitalization and intelligence of the exoskeletal rehabilitation process and laying the foundation for future intelligent assistance systems.



中文翻译:

外骨骼云脑平台及其在安全评估中的应用

目的

本文针对智能康复应用中医生、患者数据和外骨骼实时传感器数据上云的问题。本研究设计了外骨骼云脑平台并验证了其安全性评估。

设计/方法/方法

本文根据数据的维度和传输速度,基于阿里云的类Lambda架构,实现了外骨骼三层云脑平台。同时,针对外骨骼的人机安全状态检测问题,利用云脑平台克隆的多维传感器数据,为用户构建了个性化的机器学习安全检测模块。该模块包括人机状态的异常检测模型、预测模型和状态分类模型。

发现

外骨骼云脑的这些功能和基于它的算法经过实验验证,满足使用需要。

原创性/价值

本论文创新性地提出了外骨骼云脑平台,开启了外骨骼康复过程的数字化、智能化,为未来的智能辅助系统奠定了基础。

更新日期:2021-06-02
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