Evidence map›Paper›PMID 40218738›Full record

ArticleSensors (Basel, Switzerland)2025

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

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

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Yezhao JuSchool of Optoelectronics, Beijing Institute of Technology, Beijing 100086, China.
Yuanji LiNanjing Research Institute of Electronics Technology, Nanjing 210039, China.
Haiyang ZhangSchool of Optoelectronics, Beijing Institute of Technology, Beijing 100086, China.ORCID 0000-0002-2382-0509
Le XinNanjing Research Institute of Electronics Technology, Nanjing 210039, China.
Changming ZhaoSchool of Optoelectronics, Beijing Institute of Technology, Beijing 100086, China.
Ziyi XuSchool of Optoelectronics, Beijing Institute of Technology, Beijing 100086, China.

Funding

Huawei Technologies (China) No Grant Number
6 · The paper itself

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.

Indexed as

A2J-Posenetbed angle detectionLiDARpoint cloud

Identifiers

PMID40218738
PMCPMC11991437

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.