Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise

Delaram Jarchi; Alex Casson

doi:10.1109/EMBC.2016.7591398

Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise

Delaram Jarchi, Alex Casson

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

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Abstract

This paper presents a new method for estimating the average heart rate from a foot/ankle worn photoplethysmography (PPG) sensor during fast bike activity. Placing the PPG sensor on the lower half of the body allows more energy to be collected from energy harvesting in order to give a power autonomous sensor node, but comes at the cost of introducing significant motion interference into the PPG trace. We present a normalised least mean square adaptive filter and short-time Fourier transform based algorithm for estimating heart rate in the presence of this motion contamination. Results from 8 subjects show the new algorithm has an average error of 9 beats-per-minute when compared to an ECG gold standard.

Original language	English
Title of host publication	IEEE Engineering in Medicine and Biology Society Conference Proceedings 2016
Publisher	IEEE
DOIs	https://doi.org/10.1109/EMBC.2016.7591398
Publication status	Published - 2016
Event	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Disney's Contemporary Resort, Orlando, Florida, United States Duration: 16 Aug 2016 → 20 Aug 2016 http://embc.embs.org/2016/

Conference

Conference	38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Abbreviated title	EMBC'16
Country/Territory	United States
City	Orlando, Florida
Period	16/08/16 → 20/08/16
Internet address	http://embc.embs.org/2016/

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10.1109/EMBC.2016.7591398

EMBC_final_versionAccepted author manuscript, 2.46 MB

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@inproceedings{1f841cc88ccc4bb6bac39235368828d4,

title = "Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise",

abstract = "This paper presents a new method for estimating the average heart rate from a foot/ankle worn photoplethysmography (PPG) sensor during fast bike activity. Placing the PPG sensor on the lower half of the body allows more energy to be collected from energy harvesting in order to give a power autonomous sensor node, but comes at the cost of introducing significant motion interference into the PPG trace. We present a normalised least mean square adaptive filter and short-time Fourier transform based algorithm for estimating heart rate in the presence of this motion contamination. Results from 8 subjects show the new algorithm has an average error of 9 beats-per-minute when compared to an ECG gold standard.",

author = "Delaram Jarchi and Alex Casson",

year = "2016",

doi = "10.1109/EMBC.2016.7591398",

language = "English",

booktitle = "IEEE Engineering in Medicine and Biology Society Conference Proceedings 2016",

publisher = "IEEE",

address = "United States",

note = "38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society , EMBC'16 ; Conference date: 16-08-2016 Through 20-08-2016",

url = "http://embc.embs.org/2016/",

}

Jarchi, D & Casson, A 2016, Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise. in IEEE Engineering in Medicine and Biology Society Conference Proceedings 2016. IEEE, 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society , Orlando, Florida, United States, 16/08/16. https://doi.org/10.1109/EMBC.2016.7591398

TY - GEN

T1 - Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise

AU - Jarchi, Delaram

AU - Casson, Alex

PY - 2016

Y1 - 2016

N2 - This paper presents a new method for estimating the average heart rate from a foot/ankle worn photoplethysmography (PPG) sensor during fast bike activity. Placing the PPG sensor on the lower half of the body allows more energy to be collected from energy harvesting in order to give a power autonomous sensor node, but comes at the cost of introducing significant motion interference into the PPG trace. We present a normalised least mean square adaptive filter and short-time Fourier transform based algorithm for estimating heart rate in the presence of this motion contamination. Results from 8 subjects show the new algorithm has an average error of 9 beats-per-minute when compared to an ECG gold standard.

AB - This paper presents a new method for estimating the average heart rate from a foot/ankle worn photoplethysmography (PPG) sensor during fast bike activity. Placing the PPG sensor on the lower half of the body allows more energy to be collected from energy harvesting in order to give a power autonomous sensor node, but comes at the cost of introducing significant motion interference into the PPG trace. We present a normalised least mean square adaptive filter and short-time Fourier transform based algorithm for estimating heart rate in the presence of this motion contamination. Results from 8 subjects show the new algorithm has an average error of 9 beats-per-minute when compared to an ECG gold standard.

UR - https://www.scopus.com/pages/publications/85009110115

U2 - 10.1109/EMBC.2016.7591398

DO - 10.1109/EMBC.2016.7591398

M3 - Conference contribution

BT - IEEE Engineering in Medicine and Biology Society Conference Proceedings 2016

PB - IEEE

T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 16 August 2016 through 20 August 2016

ER -

Estimation of heart rate from foot worn photoplethysmography sensors during fast bike exercise

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