title: Algorithm for heart rate extraction in a novel wearable acoustic sensor.
abstract: Phonocardiography is a widely used method of listening to the heart sounds and indicating the presence of cardiac abnormalities. Each heart cycle consists of two major sounds - S1 and S2 - that can be used to determine the heart rate. The conventional method of acoustic signal acquisition involves placing the sound sensor at the chest where this sound is most audible. Presented is a novel algorithm for the detection of S1 and S2 heart sounds and the use of them to extract the heart rate from signals acquired by a small sensor placed at the neck. This algorithm achieves an accuracy of 90.73 and 90.69%, with respect to heart rate value provided by two commercial devices, evaluated on more than 38 h of data acquired from ten different subjects during sleep in a pilot clinical study. This is the largest dataset for acoustic heart sound classification and heart rate extraction in the literature to date. The algorithm in this study used signals from a sensor designed to monitor breathing. This shows that the same sensor and signal can be used to monitor both breathing and heart rate, making it highly useful for long-term wearable vital signs monitoring.
authors.affiliation: Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , UK.
authors.forename: Guangwei
authors.initials: G
authors.lastname: Chen
authors.affiliation: Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , UK.
authors.forename: Syed Anas
authors.initials: SA
authors.lastname: Imtiaz
authors.affiliation: Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , UK.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Aguilar-Pelaez
authors.affiliation: Department of Electrical and Electronic Engineering , Imperial College London , London SW7 2AZ , UK.
authors.forename: Esther
authors.initials: E
authors.lastname: Rodriguez-Villegas
keywords: S1 heart sound detection; S2 heart sound detection; acoustic heart sound classification; acoustic signal acquisition; acoustic signal processing; acoustic transducers; biomedical transducers; body sensor networks; breathing monitoring; cardiac abnormalities; commercial devices; data acquisition; dataset; feature extraction; heart cycle; heart rate extraction; heart rate extraction algorithm; heart sound listening; long-term wearable vital signs monitoring; medical signal processing; novel wearable acoustic sensor; patient monitoring; phonocardiography; pneumodynamics; signal acquisition; signal classification