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    <responseDate>2026-10-13T00:58:17Z</responseDate>
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    <identifier>10.57760/sciencedb.29663</identifier>
    <datestamp>2026-01-12T10:25:17Z</datestamp>
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  <dc:date>2026-01-12</dc:date>
  <dc:title>Multi-scenario video, rPPG, and blood volume pulse multimodal dataset(ZJXU-MOTION)</dc:title>
  <dc:identifier>doi:10.57760/sciencedb.29663</dc:identifier>
  <dc:language>en</dc:language>
  <dc:description>ZJXU-MOTION designed variables such as motion and lighting, creating an uncompressed high-bitrate dataset that provides rich resources for video compression encoding research and training deep learning methods for rPPG, especially in motion scenarios. This dataset includes RGB video, infrared video, BVP signals, and ECG signals.</dc:description>
  <dc:subject>Remote Photoplethysmography; rPPG; Video compression algorithms; Blood Volume Pulse; BVP; Heart Rate; HR; PSNR; Sports Scene; Heart Rate Monitoring</dc:subject>
  <dc:creator>Ye Xiaolang</dc:creator>
  <dc:creator>Zhan Xinlong</dc:creator>
  <dc:creator>Zeng Luhang</dc:creator>
  <dc:creator>Zhou Yuhao</dc:creator>
  <dc:creator>Wei Yuanwang</dc:creator>
  <dc:creator>Sun Hong</dc:creator>
  <dc:creator>Zhang Xianchao</dc:creator>
  <dc:rights>RESTRICTED</dc:rights>
  <dc:type>dataset</dc:type>
  <dc:relation>http://www.doi.org/10.1016/j.bspc.2024.107445</dc:relation>
  <dc:publisher>Science Data Bank</dc:publisher>
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