Exoskeleton cloud-brain platform and its application in safety assessment

IF 1.9 4区 计算机科学 Q3 AUTOMATION & CONTROL SYSTEMS Assembly Automation Pub Date : 2021-06-03 DOI:10.1108/AA-11-2020-0184
Fashu Xu, Rui Huang, Hong Cheng, Mingyuan Fan, Jing Qiu
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Abstract

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.
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外骨骼云脑平台及其在安全评估中的应用
目的本文旨在解决智能康复应用中医生、患者的数据以及外骨骼的实时传感器数据与云的连接问题。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/方法论/方法根据数据的维度和传输速度,本文实现了一个基于阿里云类似Lambda架构的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,本文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及其算法经过实验验证,符合使用需求。独创性/价值本文创新性地提出了一个外骨骼云脑平台,开启了外骨骼康复过程的数字化和智能化,为未来的智能辅助系统奠定了基础。
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来源期刊
Assembly Automation
Assembly Automation 工程技术-工程:制造
CiteScore
4.30
自引率
14.30%
发文量
51
审稿时长
3.3 months
期刊介绍: Assembly Automation publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of assembly technology and automation, and reflecting the most interesting and strategically important research and development activities from around the world. Because of this, readers can stay at the very forefront of industry developments. All research articles undergo rigorous double-blind peer review, and the journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations.
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