Big Data Edge on Consumer Devices for Precision Medicine
dc.contributor.author | Stauffer, Jake | |
dc.contributor.author | Zhang, Qingxue | |
dc.contributor.department | Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering | |
dc.date.accessioned | 2024-06-27T12:20:22Z | |
dc.date.available | 2024-06-27T12:20:22Z | |
dc.date.issued | 2022 | |
dc.description.abstract | Consumer electronics like smartphones and wearable computers are furthering precision medicine significantly, through capturing/leveraging big data on the edge towards real-time, interactive healthcare applications. Here we propose a big data edge platform that can, not only capture/manage different biomedical dynamics, but also enable real-time visualization of big data. The big data can also be uploaded to cloud for long-term management. The system has been evaluated on the real-world biomechanical data-based application, and demonstrated its effectiveness on big data management and interactive visualization. This study is expected to greatly advance big data-driven precision medicine applications. | |
dc.eprint.version | Author's manuscript | |
dc.identifier.citation | Stauffer J, Zhang Q. Big Data Edge on Consumer Devices for Precision Medicine. In: 2022 IEEE International Conference on Consumer Electronics (ICCE). ; 2022:1-3. doi:10.1109/ICCE53296.2022.9730484 | |
dc.identifier.uri | https://hdl.handle.net/1805/41951 | |
dc.language.iso | en_US | |
dc.publisher | IEEE | |
dc.relation.isversionof | 10.1109/ICCE53296.2022.9730484 | |
dc.relation.journal | 2022 IEEE International Conference on Consumer Electronics (ICCE) | |
dc.rights | Publisher Policy | |
dc.source | Author | |
dc.subject | Big Data | |
dc.subject | Big Data Edge | |
dc.subject | Biomechanics | |
dc.subject | Data visualization | |
dc.subject | Electric potential | |
dc.subject | Medical services | |
dc.subject | Mobile Edge | |
dc.subject | Precision medicine | |
dc.subject | Smart Health | |
dc.subject | Wearable computers | |
dc.title | Big Data Edge on Consumer Devices for Precision Medicine | |
dc.type | Conference proceedings |