Fashu Xu, Rui Huang, Hong Cheng, Mingyuan Fan, Jing Qiu
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引用次数: 0
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.
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.