FindTrial
Sign In

Deep Learning-Based ATC Intelligent ECG Recognition Algorithm for Accurate Decision-Making in Mechanical Chest Compression CPR: A Multicenter Prospective Study

Deep Learning-Based ATC Intelligent ECG Recognition Algorithm for Accurate Decision-Making in Mechanical Chest Compression CPR: A Multicenter Prospective Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120038
Enrollment
Unknown
Registered
2026-03-09
Start date
2026-03-10
Completion date
Unknown
Last updated
2026-03-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Cardiac arrest

Interventions

Defibrillation group:N/A

Sponsors

The First Affiliated Hospital of Henan University of Science and Technology
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Age = 18 years old; 2. Patients who need cardiopulmonary resuscitation due to their condition; 3. Meeting ethical requirements and having signed the informed consent form.

Exclusion criteria

Exclusion criteria: 1. Refusal of CPR; 2. Pregnant women; 3. Severe chest wall trauma, burns, skin defects, etc., which prevent the connection of electrode pads; 4. Severe chest trauma that makes conventional chest compressions impossible; 5. Patients in the terminal stage of cancer; 6. All other situations where the researcher deems the patient unsuitable for participation in the clinical study.

Design outcomes

Primary

MeasureTime frame
Autonomous circulation recovery rate(ROSC);—

Countries

China

Contacts

Public ContactYingying Hu

The First Affiliated Hospital of Henan University of Science and Technology

huying415@126.com+86 151 3792 6909

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Mar 20, 2026