A Non-Contact Privacy Protection Bed Angle Estimation Method Based on LiDAR

Yezhao Ju, Yuanji Li, Haiyang Zhang*, Le Xin, Changming Zhao, Ziyi Xu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Accurate bed angle monitoring is crucial in healthcare settings, particularly in Intensive Care Units (ICUs), where improper bed positioning can lead to severe complications such as ventilator-associated pneumonia. Traditional camera-based solutions, while effective, often raise significant privacy concerns. This study proposes a non-intrusive bed angle detection system based on LiDAR technology, utilizing the Intel RealSense L515 sensor. By leveraging time-of-flight principles, the system enables real-time, privacy-preserving monitoring of head-of-bed elevation angles without direct visual surveillance. Our methodology integrates advanced techniques, including coordinate system transformation, plane fitting, and a deep learning framework combining YOLO-X with an enhanced A2J algorithm. Customized loss functions further improve angle estimation accuracy. Experimental results in ICU environments demonstrate the system’s effectiveness, with an average angle detection error of less than 3 degrees.

Original languageEnglish
Article number2226
JournalSensors
Volume25
Issue number7
DOIs
Publication statusPublished - Apr 2025
Externally publishedYes

Keywords

  • A2J-Posenet
  • bed angle detection
  • LiDAR
  • point cloud

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