This study aims to investigate the use of heart sound recordings, or phonocardiograms, recorded with smartphones' built-in microphones and accessory microphones to estimate heart rate (HR) and heart rate variability (HRV). HR refers to the number of heart beats per minute, while HRV refers to the variation in the intervals between heart beats. Participants will have their heart sounds (phonocardiograms) recorded before and after exercise, and electrocardiogram (ECG) and photoplethysmogram (PPG) data recorded before, during, and after exercise to induce a wide range of HR. Researchers will match the phonocardiograms, ECG, and PPG data to create a database for use in future training and testing of algorithms (including artificial intelligence (AI)).
Study Type
OBSERVATIONAL
Enrollment
50
Collection of computer algorithms called ausculto® that is designed to perform heart sound analysis to estimate heart rate and heart rate variability
Participants will be requested to exercise to raise their HR over the resting range while heart-related physiological signals are collected.
HR estimation
The algorithm will estimate participants' HR from phonocardiograms at multiple timepoints. The concordance correlation coefficient, mean bias, and limits of agreement will be calculated for HR with ECG-derived HR as the gold standard.
Time frame: Day 0
HRV estimation
The algorithm will estimate participants' HRV from phonocardiograms at multiple timepoints. The absolute difference (error) in HRV estimation will be calculated with ECG-derived HRV as the gold standard.
Time frame: Day 0
Participants' comfort level for devices used in this study
A survey will be given to participants after heart data collection to evaluate their preferences and comfort level when using the different devices to measure HR and HRV.
Time frame: Day 0
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