Imperial College London
Alternate

ProfessorEstherRodriguez Villegas

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor in Low Power Electronics
 
 
 
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Contact

 

+44 (0)20 7594 6193e.rodriguez

 
 
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Location

 

914Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Sharma:2019:10.1109/TBME.2018.2836187,
author = {Sharma, P and Imtiaz, SA and Rodriguez, Villegas E},
doi = {10.1109/TBME.2018.2836187},
journal = {IEEE Transactions on Biomedical Engineering},
pages = {246--256},
title = {An algorithm for heart rate extraction from acoustic recordings at the neck},
url = {http://dx.doi.org/10.1109/TBME.2018.2836187},
volume = {66},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Heart rate is an important physiological parameter to assess the cardiac condition of an individual and is traditionally determined by attaching multiple electrodes on the chest of a subject to record the electrical activity of the heart. The installation and handling complexities of such systems does not prove feasible for a user to undergo a long-term monitoring in the home settings. A small-sized, battery-operated wearable monitoring device is placed on the suprasternal notch at neck to record acoustic signals containing information about breathing and cardiac sounds. The heart sounds obtained are heavily corrupted by the respiratory cycles and other external artifacts. This paper presents a novel algorithm for reliably extracting the heart rate from such acoustic recordings, keeping in mind the constraints posed by the wearable technology. The methodology constructs the Hilbert energy envelope of the signal by calculating its instantaneous characteristics to segment and classify a cardiac cycle into S1 and S2 sounds using their timing characteristics. The algorithm is tested on a dataset consisting of 13 subjects with an approximate data length of 75 hours and achieves an accuracy of 94.34%, an RMS error of 3.96 bpm and a correlation coefficient of 0.93 with reference to a commercial device in use.
AU  - Sharma,P
AU  - Imtiaz,SA
AU  - Rodriguez,Villegas E
DO  - 10.1109/TBME.2018.2836187
EP  - 256
PY  - 2019///
SN  - 0018-9294
SP  - 246
TI  - An algorithm for heart rate extraction from acoustic recordings at the neck
T2  - IEEE Transactions on Biomedical Engineering
UR  - http://dx.doi.org/10.1109/TBME.2018.2836187
UR  - https://ieeexplore.ieee.org/document/8360948
UR  - http://hdl.handle.net/10044/1/59862
VL  - 66
ER  -
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