Evidence map›Paper›PMID 41635451›Full record

ArticleHealth science reports2026

Computer Vision-Guided Automated External Defibrillator System Improves Cardiopulmonary Resuscitation Accuracy: A Randomized Crossover Trial.

Li Liu, Hua Huang, Pengcheng Zhao, Yan Chen, Sixing Liu, Qun Wu, Wei Jing, Mingjie Yin, Yongyuan Li, Jiahuan Lu and 3 more

Abstract read
In one paragraph

Article in Health science reports, 2026. 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
–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

2 citing papers in PubMed.

  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

13 authors.

Li LiuJiangsu Yuyue Medical Equipment and Supply Co. Ltd. Zhenjiang Jiangsu China.
Hua HuangJiangsu Yuyue Medical Equipment and Supply Co. Ltd. Zhenjiang Jiangsu China.
Pengcheng ZhaoWomen & Children Intensive Care Unit The First Affiliated Hospital of Nanjing Medical University Nanjing China.
Yan ChenDepartment of Emergency and Critical Care Medicine, Gusu School of Nanjing Medical University, Suzhou Clinical Medical Center of Critical Care Medicine, Suzhou Clinical Medical Center of Burn and Trauma The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital) Suzhou China.
Sixing LiuJiangsu Yuyue Medical Equipment and Supply Co. Ltd. Zhenjiang Jiangsu China.
Qun WuJiangsu Yuyue Medical Equipment and Supply Co. Ltd. Zhenjiang Jiangsu China.
Wei JingJiangsu Yuyue Medical Equipment and Supply Co. Ltd. Zhenjiang Jiangsu China.
Mingjie YinSchool of Computer Science Nanjing University of Posts and Telecommunications Nanjing China.
Yongyuan LiSchool of Computer Science Nanjing University of Posts and Telecommunications Nanjing China.
Jiahuan LuSchool of Computer Science Nanjing University of Posts and Telecommunications Nanjing China.
Xicheng ZhangNational Clinical Research Center for Child Health Hangzhou China.
He XuSchool of Computer Science Nanjing University of Posts and Telecommunications Nanjing China.ORCID https://orcid.org/0000-0003-2809-2237
Yimu JiSchool of Computer Science Nanjing University of Posts and Telecommunications Nanjing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Out-of-hospital cardiac arrests (OHCAs) remain a critical challenge in emergency care, as CPR effectiveness heavily relies on precise chest compressions. We propose a novel CPR guidance system using computer vision to track rescuer motion in real time. This study aims to evaluate the system's efficacy in improving CPR performance, particularly its adaptability to both adult and pediatric populations. Methods: We evaluated a novel CPR navigation system integrated into an Automated External Defibrillator (AED), termed HeartSave M650, which utilizes computer vision to guide CPR quality. A prospective, randomized, crossover trial was conducted comparing HeartSave M650 against the traditional HeartSave M600. In total, 81 volunteers (41 CPR-trained; 40 untrained) stratified into adult ( Results: The primary outcome demonstrated that the M650 significantly improved optimal-depth compressions in adults (60.38% vs. 29.54%, Conclusion: HeartSave M650 improves compression depth accuracy, more than doubling correct performance compared to conventional AEDs. Its ability to reduce over-depth compressions further supports its clinical value in standardizing CPR quality.

Indexed as

cardiopulmonary resuscitationchest compression quality metricscomputer vision applicationCPR navigation systemmodel quantization

Identifiers

PMID41635451
PMCPMC12862101

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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.