Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography

There are many existing wearable devices which are just meant to measure the Systolic Blood Pressure (SBP), and worn on the wrist. However, the current trend of wearable devices is towards the head mounted wearable devices. Pulse wave transit time (PWTT) is used as a non-invasive and cuffless method...

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Main Authors: Hassan, Rohayanti, Jamaludin, Mohd. Najeb, Silvadorai, Kahuthaman, Anwar, Toni
Format: Article
Published: International Journal of Software Engineering and Technology 2018
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Online Access:http://eprints.utm.my/id/eprint/82342/
http://ijset.mjiit.utm.my
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spelling my.utm.823422019-11-26T06:54:05Z http://eprints.utm.my/id/eprint/82342/ Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography Hassan, Rohayanti Jamaludin, Mohd. Najeb Silvadorai, Kahuthaman Anwar, Toni QA75 Electronic computers. Computer science There are many existing wearable devices which are just meant to measure the Systolic Blood Pressure (SBP), and worn on the wrist. However, the current trend of wearable devices is towards the head mounted wearable devices. Pulse wave transit time (PWTT) is used as a non-invasive and cuffless method for blood pressure estimation. In this study, ECG signals from the head will be first extracted by using a stimulus based algorithm utilizing ensemble averaging technique to compute for the 〖PWTT〗_head with reference to the Photoplethysmogram (PPG) signals from the earlobe. The chest ECG signals (lead II) and Photoplethysmogram (PPG) signals fingertip will be simultaneously recorded with the head recordings and earlobe PPG to be used as reference signal to measure the 〖PWTT〗_chest from the chest and to verify the performance of the 〖PWTT〗_head measured from the head. The results obtained are analyzed by using regression plots and difference error. The expected outcome is by using 〖PWTT〗_head , SBP can be estimated accurately within the ANSI.AAMI SP10:2002 standards for noninvasive blood pressure accuracy (±5 [mmHg] mean error, 8[mmHg] standard deviations). International Journal of Software Engineering and Technology 2018 Article PeerReviewed Hassan, Rohayanti and Jamaludin, Mohd. Najeb and Silvadorai, Kahuthaman and Anwar, Toni (2018) Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography. International Journal of Software Engineering and Technology, 4 (2). pp. 50-56. ISSN 2289-2842 http://ijset.mjiit.utm.my
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Hassan, Rohayanti
Jamaludin, Mohd. Najeb
Silvadorai, Kahuthaman
Anwar, Toni
Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
description There are many existing wearable devices which are just meant to measure the Systolic Blood Pressure (SBP), and worn on the wrist. However, the current trend of wearable devices is towards the head mounted wearable devices. Pulse wave transit time (PWTT) is used as a non-invasive and cuffless method for blood pressure estimation. In this study, ECG signals from the head will be first extracted by using a stimulus based algorithm utilizing ensemble averaging technique to compute for the 〖PWTT〗_head with reference to the Photoplethysmogram (PPG) signals from the earlobe. The chest ECG signals (lead II) and Photoplethysmogram (PPG) signals fingertip will be simultaneously recorded with the head recordings and earlobe PPG to be used as reference signal to measure the 〖PWTT〗_chest from the chest and to verify the performance of the 〖PWTT〗_head measured from the head. The results obtained are analyzed by using regression plots and difference error. The expected outcome is by using 〖PWTT〗_head , SBP can be estimated accurately within the ANSI.AAMI SP10:2002 standards for noninvasive blood pressure accuracy (±5 [mmHg] mean error, 8[mmHg] standard deviations).
format Article
author Hassan, Rohayanti
Jamaludin, Mohd. Najeb
Silvadorai, Kahuthaman
Anwar, Toni
author_facet Hassan, Rohayanti
Jamaludin, Mohd. Najeb
Silvadorai, Kahuthaman
Anwar, Toni
author_sort Hassan, Rohayanti
title Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
title_short Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
title_full Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
title_fullStr Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
title_full_unstemmed Algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
title_sort algorithm to estimate systolic blood pressure by extracting electrocardiogram signal from the head using earlobe photoplethysmography
publisher International Journal of Software Engineering and Technology
publishDate 2018
url http://eprints.utm.my/id/eprint/82342/
http://ijset.mjiit.utm.my
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score 13.18916