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dc.contributor.authorZhu, Junyi
dc.contributor.authorSnowden, Jackson
dc.contributor.authorVerdejo, Joshua
dc.contributor.authorChen, Emily
dc.contributor.authorZhang, Paul
dc.contributor.authorGhaednia, Hamid
dc.contributor.authorSchwab, Joseph
dc.contributor.authorMueller, Stefanie
dc.date.accessioned2022-11-03T15:38:03Z
dc.date.available2022-11-03T15:38:03Z
dc.date.issued2021-10-10
dc.identifier.isbn978-1-4503-8635-7
dc.identifier.urihttps://hdl.handle.net/1721.1/146105
dc.publisherACM|UIST'21: User Interface Software and Technology CD-Romen_US
dc.relation.isversionofhttps://doi.org/10.1145/3472749.3474758en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceACM|UIST'21: User Interface Software and Technology CD-Romen_US
dc.titleEIT-kit: An Electrical Impedance Tomography Toolkit for Health and Motion Sensingen_US
dc.typeArticleen_US
dc.identifier.citationZhu, Junyi, Snowden, Jackson, Verdejo, Joshua, Chen, Emily, Zhang, Paul et al. 2021. "EIT-kit: An Electrical Impedance Tomography Toolkit for Health and Motion Sensing."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-11-02T22:08:00Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2022-11-02T22:08:00Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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