Big Data Edge on Consumer Devices for Precision Medicine

dc.contributor.authorStauffer, Jake
dc.contributor.authorZhang, Qingxue
dc.contributor.departmentBiomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
dc.date.accessioned2024-06-27T12:20:22Z
dc.date.available2024-06-27T12:20:22Z
dc.date.issued2022
dc.description.abstractConsumer 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.versionAuthor's manuscript
dc.identifier.citationStauffer 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.urihttps://hdl.handle.net/1805/41951
dc.language.isoen_US
dc.publisherIEEE
dc.relation.isversionof10.1109/ICCE53296.2022.9730484
dc.relation.journal2022 IEEE International Conference on Consumer Electronics (ICCE)
dc.rightsPublisher Policy
dc.sourceAuthor
dc.subjectBig Data
dc.subjectBig Data Edge
dc.subjectBiomechanics
dc.subjectData visualization
dc.subjectElectric potential
dc.subjectMedical services
dc.subjectMobile Edge
dc.subjectPrecision medicine
dc.subjectSmart Health
dc.subjectWearable computers
dc.titleBig Data Edge on Consumer Devices for Precision Medicine
dc.typeConference proceedings
Files
Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Stauffer2022BigData-NSF-AAM.pdf
Size:
441.48 KB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.04 KB
Format:
Item-specific license agreed upon to submission
Description: