Evidence map›Paper›PMID 38610365›Full record

ArticleSensors (Basel, Switzerland)2024

Detection and Evaluation for High-Quality Cardiopulmonary Resuscitation Based on a Three-Dimensional Motion Capture System: A Feasibility Study.

Xingyi Tang, Yan Wang, Haoming Ma, Aoqi Wang, You Zhou, Sijia Li, Runyuan Pei, Hongzhen Cui, Yunfeng Peng, Meihua Piao

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
4.1field-weighted citation impact, top 7% of its field
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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
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

10 authors at 2 institutions in 1 country.

Xingyi TangSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.ORCID 0009-0007-6992-4710
Yan WangSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.ORCID 0000-0001-7396-7739
Haoming MaSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.
Aoqi WangSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.
You ZhouSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.ORCID 0000-0002-1352-0211
Sijia LiSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.
Runyuan PeiSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.ORCID 0009-0007-8190-2477
Hongzhen CuiSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China.ORCID 0000-0001-8890-2161
Yunfeng PengSchool of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China.
Meihua PiaoSchool of Nursing, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100144, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNUniversity of Science and Technology Beijing · CN

Funding

Peking Union Medical College 2023 Medical Education Scholar Program 2023zlgc0711The Non-Profit Central Research Institute Fund of Chinese Academy of Medical Sciences 2023-RC320-01
6 · The paper itself

Abstract

High-quality cardiopulmonary resuscitation (CPR) and training are important for successful revival during out-of-hospital cardiac arrest (OHCA). However, existing training faces challenges in quantifying each aspect. This study aimed to explore the possibility of using a three-dimensional motion capture system to accurately and effectively assess CPR operations, particularly about the non-quantified arm postures, and analyze the relationship among them to guide students to improve their performance. We used a motion capture system (Mars series, Nokov, China) to collect compression data about five cycles, recording dynamic data of each marker point in three-dimensional space following time and calculating depth and arm angles. Most unstably deviated to some extent from the standard, especially for the untrained students. Five data sets for each parameter per individual all revealed statistically significant differences (

Indexed as

Cardiopulmonary ResuscitationData CompressionChinaFeasibility StudiesHumansMotion Capturearm posturecardiopulmonary resuscitationhigh-qualitymotion capturethree-dimensionaltraining

Identifiers

PMID38610365
PMCPMC11014185
OpenAlexW4393218577

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.