CARAMEL
Research type
Research Study
Full title
Cardiorespiratory Markers Inferred from Photoplethysmography Using Machine Learning - CARAMEL
IRAS ID
325931
Contact name
Elina Naydenova
Contact email
Sponsor organisation
Feebris Ltd
Duration of Study in the UK
0 years, 11 months, 26 days
Research summary
This research study protocol aims to explore the use of algorithms for extracting reliable information from pulse oximeter devices and digital stethoscopes. The study focuses on deriving breathing rate (BR), pulse rate (PR) and detecting heart rhythm abnormalities, including indicators of atrial fibrillation (AF), from pulse oximetry signals. The study will take place in community settings such as the sponsor offices. It is non-interventional and involves negligible participant risk. Data will be collected from up to 200 participants (data collection: ~20 minutes per person). Participants will be above 18 years of age, and acutely well at the time of the study. Participants will undergo breathing rate/sound and pulse rate measurements using pulse oximeters, a digital stethoscope and capnography (a measurement of exhaled carbon-dioxide, and therefore breathing frequency). For heart rhythm abnormalities, participants will wear pulse oximeters and ECG leads. The study aims to investigate scalable and cost-effective methods for deriving important information about a patient’s clinical status from pulse oximeter devices and a digital stethoscope.
REC name
South Central - Oxford C Research Ethics Committee
REC reference
23/SC/0146
Date of REC Opinion
3 Aug 2023
REC opinion
Further Information Favourable Opinion