An IoT-based framework of Webvr visualization for medical big data in connected health
Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmit...
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sg-ntu-dr.10356-1459212023-03-04T17:12:32Z An IoT-based framework of Webvr visualization for medical big data in connected health Xu, Gaowei Lan, Yisha Zhou, Wen Huang, Chenxi Li, Weibin Zhang, Wei Zhang, Guokai Ng, Eddie Yin Kwee Cheng, Yongqiang Peng, Yonghong Che, Wenliang School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Internet of Thing Telemedicine Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment. Published version 2021-01-14T06:01:52Z 2021-01-14T06:01:52Z 2019 Journal Article Xu, G., Lan, Y., Zhou, W., Huang, C., Li, W., Zhang, W., . . . Che, W. (2019). An IoT-based framework of Webvr visualization for medical big data in connected health. IEEE Access, 7, 173866-173874. doi:10.1109/ACCESS.2019.2957149 2169-3536 0000-0003-3752-7749 0000-0002-5508-1819 0000-0002-8840-5437 0000-0003-4675-4767 0000-0002-1266-1864 0000-0002-2100-0259 0000-0002-9370-3594 0000-0002-5430-2405 0000-0002-0952-8325 0000-0002-5701-1080 0000-0001-7282-7638 https://hdl.handle.net/10356/145921 10.1109/ACCESS.2019.2957149 2-s2.0-85078339005 7 173866 173874 en IEEE Access © 2019 IEEE. This journal is 100% open access, which means that all content is freely available without charge to users or their institutions. All articles accepted after 12 June 2019 are published under a CC BY 4.0 license, and the author retains copyright. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, as long as proper attribution is given. application/pdf |
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Engineering::Mechanical engineering Internet of Thing Telemedicine Xu, Gaowei Lan, Yisha Zhou, Wen Huang, Chenxi Li, Weibin Zhang, Wei Zhang, Guokai Ng, Eddie Yin Kwee Cheng, Yongqiang Peng, Yonghong Che, Wenliang An IoT-based framework of Webvr visualization for medical big data in connected health |
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Recently, telemedicine has been widely applied in remote diagnosis, treatment and counseling, where the Internet of Things (IoT) technology plays an important role. In the process of telemedicine, data are collected from remote medical equipment, such as CT machine and MRI machine, and then transmitted and reconstructed locally in three-dimensions. Due to the large amount of data to be transmitted in the reconstructed model and the small storage capacity, data need to be compressed progressively before transmission. On this basis, we proposed a lightweight progressive transmission algorithm based on large data visualization in telemedicine to improve transmission efficiency and achieve lossless transmission of original data. Moreover, a novel four-layer system architecture based on IoT has been introduced, including the sensing layer, analysis layer, network layer and application layer. In this way, the three-dimensional reconstructed data at the local end is compressed and transmitted to the remote end, and then visualized at the remote end to show reconstructed 3D models. Thus, it is conducive to doctors in remote real-time diagnosis and treatment, and then realize the data processing and transmission between doctors, patients and medical equipment. |
author2 |
School of Mechanical and Aerospace Engineering |
author_facet |
School of Mechanical and Aerospace Engineering Xu, Gaowei Lan, Yisha Zhou, Wen Huang, Chenxi Li, Weibin Zhang, Wei Zhang, Guokai Ng, Eddie Yin Kwee Cheng, Yongqiang Peng, Yonghong Che, Wenliang |
format |
Article |
author |
Xu, Gaowei Lan, Yisha Zhou, Wen Huang, Chenxi Li, Weibin Zhang, Wei Zhang, Guokai Ng, Eddie Yin Kwee Cheng, Yongqiang Peng, Yonghong Che, Wenliang |
author_sort |
Xu, Gaowei |
title |
An IoT-based framework of Webvr visualization for medical big data in connected health |
title_short |
An IoT-based framework of Webvr visualization for medical big data in connected health |
title_full |
An IoT-based framework of Webvr visualization for medical big data in connected health |
title_fullStr |
An IoT-based framework of Webvr visualization for medical big data in connected health |
title_full_unstemmed |
An IoT-based framework of Webvr visualization for medical big data in connected health |
title_sort |
iot-based framework of webvr visualization for medical big data in connected health |
publishDate |
2021 |
url |
https://hdl.handle.net/10356/145921 |
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1759856224106446848 |