DevelopmentandApplication of a Single Feature Recognition Model for Heart Failure Based onArtificial Intelligence Optimization Algorithms

The goal of this observational study is to develop and validate a single-feature artificial intelligence algorithm based on data from a wearable ECG patch in patients with heart failure (HF). The main question it aims to answer is:

Does the algorithm, using synchronized ECG and accelerometer signals from the patch, achieve accurate detection of heart sounds (S1, S2, and in some patients S3, S4) compared to the Eko CORE500 digital stethoscope in patients with acute exacerbation of HF?

Participants with confirmed HF (NYHA class II-IV) will undergo two 2-minute sessions of simultaneous ECG patch and digital stethoscope recordings, followed by standard 12-lead ECG. Data will be used for algorithm training and validation, with the primary endpoint being the sensitivity and specificity of heart sound detection against the reference device.

Study Overview

• Status: Not yet recruiting
• Conditions: Heart Failure - NYHA II - IV; Cardiac Sound

• Study Type: Observational
• Enrollment (Estimated): 50

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: N/A

• Sampling Method: Non-Probability Sample

Study Population

Selection criteria: Age ≥ 18 years; Body mass index < 35 kg/m2; Diagnosed with heart failure: According to the "2024 Chinese Guidelines for Diagnosis and Treatment of Heart Failure", "2021 ESC Guidelines for Diagnosis and Treatment of Acute and Chronic Heart Failure", and "2022 AHA/ACC/HFSA Guidelines for Management of Heart Failure", and the NYHA classification is II to IV, and the patients have severe comorbidities or unstable condition, which may interfere with data collection during the study period.

Description

Inclusion Criteria:

• Age ≥ 18 years old;
• Body mass index < 35 kg/m2;
• Diagnosed with heart failure: according to "Chinese Guidelines for Diagnosis and Treatment of Heart Failure 2024", "2021 ESC Guidelines for Diagnosis and Treatment of Acute and Chronic Heart Failure", and "2022 AHA/ACC/HFSA Guidelines for Management of Heart Failure";
• NYHA classification II - IV;
• Able to fully understand the purpose and process of the trial and voluntarily sign the informed consent form.

Exclusion Criteria:

• There are physical disabilities that prevent safe and thorough testing;
• There are open wounds on the chest skin or the skin is allergic to the patches;
• There is a large amount of pericardial effusion, pericardial tamponade, pleural friction rub, pneumothorax, and a large amount of pleural effusion, which may affect data collection;
• The patient has severe comorbidities or unstable condition, which may interfere with data collection during the study period;
• Other situations where the investigator believes the subject is not suitable to participate in this trial, such as those that may increase the risk of the trial, affect the subject's compliance with the protocol, or affect the subject's ability to complete the trial due to physical or psychological diseases or conditions.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Heart sounds include S1 and S2	In some patients, S3 and S4 are also present.	10-15 minutes

Collaborators and Investigators

• Sponsor: Second Affiliated Hospital, School of Medicine, Zhejiang University

Study record dates

Study Major Dates

• Study Start (Estimated): June 1, 2026
• Primary Completion (Estimated): February 28, 2027
• Study Completion (Estimated): May 31, 2027

Study Registration Dates

• First Submitted: June 15, 2026
• First Submitted That Met QC Criteria: June 23, 2026
• First Posted (Actual): June 25, 2026

Study Record Updates

• Last Update Posted (Actual): June 25, 2026
• Last Update Submitted That Met QC Criteria: June 23, 2026
• Last Verified: June 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: 20260571