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• W4383890120 abstract "Recent studies corroborate Wi-Fi Channel State Information (CSI) usability to monitor patients remotely and obtain health information non-invasively and with low-cost. In addition to monitoring vital signs, this technology can also be applied to presence detection, subject recognition, position and movement identification, among other uses. Despite its wide range of potential applications, there is a lack of CSI datasets that cover multiple activities and include participants’ phenotype information to help develop, test, and compare new solutions. This study highlights the importance of building a robust public Wi-Fi CSI dataset. Therefore, we present <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>eHealth CSI</i> , a CSI dataset that includes a variety of Wi-Fi CSI data from more than 100 people in various activities in a controlled room. We also include CSI data collected in the same room without the presence of participants. This dataset was made publicly available online to other researchers under request. In this work, we introduce CSI technology and describe the data collection setup. In addition to CSI data, our dataset includes participants’ phenotype information and heartbeat rate monitoring data using a smartwatch." @default.
• W4383890120 created "2023-07-12" @default.
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• W4383890120 date "2023-01-01" @default.
• W4383890120 modified "2023-09-24" @default.
• W4383890120 title "eHealth CSI: A Wi-Fi CSI Dataset of Human Activities" @default.
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• W4383890120 doi "https://doi.org/10.1109/access.2023.3294429" @default.
• W4383890120 hasPublicationYear "2023" @default.
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