Using AI to detect early heart failure worsening from voice, cough and breathing sounds
Utilising AI Analysis of Sounds To prEdict heaRt failurE decOmpensation
This will test whether a smartphone app that uses AI to analyse voice, cough and breathing sounds can spot early signs of worsening in adults with chronic NYHA class 3–4 heart failure.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 250 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Cambridge University Hospitals NHS Foundation Trust Academic / other |
| Locations | 1 site (Cambridge, Cambridgeshire) |
| Trial ID | NCT06555757 on ClinicalTrials.gov |
What this trial studies
Researchers will collect smartphone recordings of participants' voice, coughs and breathing alongside routine clinical data such as height, weight, BMI, medical history, physical exam findings, resting vital signs and blood samples. An AI algorithm will analyse the sound recordings to identify patterns associated with pulmonary congestion and impending acute decompensated heart failure. Participants will attend Cambridge University Hospitals for baseline assessments and may provide additional recordings remotely via a mobile app or a loaned smartphone. The approach aims to find subtle, non-invasive signals that precede clinical worsening and could be monitored outside the hospital.
Who should consider this trial
Good fit: Adults (age ≥18) with chronic stable heart failure classified as NYHA class 3 or 4 who can give informed consent and use a smartphone (or accept a loaned device) are ideal candidates.
Not a fit: Patients with active pneumonia, significant chronic pulmonary disease (eg, severe asthma, COPD, interstitial lung disease), current pulmonary embolus, those requiring continuous high‑flow oxygen, or those unable to provide consent or use a smartphone are unlikely to benefit from this approach.
Why it matters
Potential benefit: If successful, this could give patients and clinicians an early, non-invasive warning of fluid buildup in the lungs and help prevent emergency hospital admissions.
How similar studies have performed: Early pilot studies and AI-based voice/lung-sound research show promise, but this application in heart failure requires larger-scale validation and is not yet proven.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Male or Female, aged 18 years or above. * Diagnosed with chronic stable heart failure NYHA Class 3 or 4 (either during most recent cardiology/heart failure clinic visit, or ADHF during recent/current hospitalization). * Participant is willing and able to give informed consent for participation in the study. * Participant has a smartphone device and can download a purposely designed mobile application on their phone (with guidance from the study investigators) or is willing to have sound recordings via a smartphone device loaned for the purpose of the study. Exclusion Criteria: * Unable to provide consent * Patients requiring continuous oxygen therapy at flow rates that cannot be provided through nasal cannula * Patients with currently known pneumonia * Patients with known significant pulmonary disease including asthma, COPD, pulmonary fibrosis/interstitial lung disease, pulmonary hemorrhage. * Patients with current Pulmonary embolus * Patients with other intercurrent acute symptomatic illness (e.g., viral/bacterial infection) at time of recording * Patients requiring continuous oxygen therapy at flow rates that cannot be provided through nasal cannula * Patients with tracheostomy or who have undergone a surgical procedure to the head/neck/larynx which would affect the normal functioning of the vocal cords. * Aphasic * Patients excluded at PI discretion
Where this trial is running
Cambridge, Cambridgeshire
- Cambridge University Hospitals NHS Foundation Trust — Cambridge, Cambridgeshire, United Kingdom (Recruiting)
Study contacts
- Principal investigator: Joseph Cheriyan — Cambridge University Hospitals NHS Foundation Trust
- Study coordinator: Erdem Demir
- Email: erdem.demir1@nhs.net
- Phone: +44 1223 256621
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.