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    <responseDate>2026-10-14T11:30:50Z</responseDate>
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    <identifier>10.57760/sciencedb.38486</identifier>
    <datestamp>2026-06-11T10:42:30Z</datestamp>
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  <dc:date>2026-06-11</dc:date>
  <dc:title>BRACETS_AUDIO_EIT</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.38486</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>The BRACETS_AUDIO_EIT dataset used in this study was obtained by preprocessing the respiratory sound data and EIT data from the publicly available BRACETS dataset. This dataset contains synchronously acquired respiratory sound signals and thoracic electrical impedance tomography signals, which can reflect both the acoustic status of the airways and the regional ventilation distribution of the lungs. Therefore, it is suitable for RS and EIT bimodal fusion research. The original BRACETS dataset is publicly available on the Mendeley Data platform under the title BRACETS: Bimodal Repository of Auscultation Coupled with Electrical Impedance Thoracic Signals, with the DOI: 10.17632/f43c7snks5.1.</dc:description>
  <dc:subject>Respiratory sound; Electrical impedance tomography; Differential diagnosis; Respiratory diseases; Machine learning; Data fusion</dc:subject>
  <dc:creator>WU Yang</dc:creator>
  <dc:creator>GU Yuying</dc:creator>
  <dc:rights>PUBLIC</dc:rights>
  <dc:rights>https://creativecommons.org/licenses/by/4.0/</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:publisher>Science Data Bank</dc:publisher>
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