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Signal quality measures for unsupervised blood pressure measurement

Accurate systolic and diastolic pressure estimation, using automated blood pressure measurement, is difficult to achieve when the transduced signals are contaminated with noise or interference, such as movement artifact. This study presents an algorithm for automated signal quality assessment in blo...

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Main Authors: Abdul Sukora, Jumadi, Redmond, S J, Chan, G S H, Lovell, N H
Format: Article
Language:English
Published: IOP Publishing 2012
Subjects:
TK7800-8360 Electronics
Online Access:http://eprints.uthm.edu.my/4119/1/AJ%202019%20%28241%29.pdf
http://eprints.uthm.edu.my/4119/
https://dx.doi.org/ 10.1088/0967-3334/33/3/465
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spelling my.uthm.eprints.41192021-11-25T04:07:51Z http://eprints.uthm.edu.my/4119/ Signal quality measures for unsupervised blood pressure measurement Abdul Sukora, Jumadi Redmond, S J Chan, G S H Lovell, N H TK7800-8360 Electronics Accurate systolic and diastolic pressure estimation, using automated blood pressure measurement, is difficult to achieve when the transduced signals are contaminated with noise or interference, such as movement artifact. This study presents an algorithm for automated signal quality assessment in blood pressure measurement by determining the feasibility of accurately detecting systolic and diastolic pressures when corrupted with various levels of movement artifact. The performance of the proposed algorithm is compared to a manually annotated reference scoring (RS). Based on visual representations and audible playback of Korotkoff sounds, the creation of the RS involved two experts identifying sections of the recorded sounds and annotating sections of noise contamination. The experts determined the systolic and diastolic pressure in 100 recorded Korotkoff sound recordings, using a simultaneous electrocardiograph as a reference signal. The recorded Korotkoff sounds were acquired from 25 healthy subjects (16 men and 9 women) with a total of four measurements per subject. Two of these measurements contained purposely induced noise artifact caused by subject movement. Morphological changes in the cuff pressure signal and the width of the Korotkoff pulse were extracted features which were believed to be correlated with the noise presence in the recorded Korotkoff sounds. Verification of reliable Korotkoff pulses was also performed using extracted features from the oscillometric waveform as recorded from the inflatable cuff. The time between an identified noise section and a verified Korotkoff pulse was the key feature used to determine the validity of possible systolic and diastolic pressures in noise contaminated Korotkoff sounds. The performance of the algorithm was assessed based on the ability to: verify if a signal was contaminated with any noise; the accuracy, sensitivity and specificity of this noise classification, and the systolic and diastolic pressure differences between the result obtained from the algorithm and the RS. 90% of the actual noise contaminated signals were correctly identified, and a sample-wise accuracy, sensitivity and specificity of 97.0%, 80.61% and 98.16%, respectively, were obtained from 100 pooled signals. The mean systolic and diastolic differences were 0.37 ± 3.31 and 3.10 ± 5.46 mmHg, respectively, when the artifact detection algorithm was utilized, with the algorithm correctly determined if the signal was clean enough to attempt an estimation of systolic or diastolic pressures in 93% of blood pressure measurements. IOP Publishing 2012 Article PeerReviewed text en http://eprints.uthm.edu.my/4119/1/AJ%202019%20%28241%29.pdf Abdul Sukora, Jumadi and Redmond, S J and Chan, G S H and Lovell, N H (2012) Signal quality measures for unsupervised blood pressure measurement. Physiological Measurement, 33 (3). pp. 465-486. ISSN 0967-3334 https://dx.doi.org/ 10.1088/0967-3334/33/3/465
institution Universiti Tun Hussein Onn Malaysia
building UTHM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tun Hussein Onn Malaysia
content_source UTHM Institutional Repository
url_provider http://eprints.uthm.edu.my/
language English
topic TK7800-8360 Electronics
spellingShingle TK7800-8360 Electronics
Abdul Sukora, Jumadi
Redmond, S J
Chan, G S H
Lovell, N H
Signal quality measures for unsupervised blood pressure measurement
description Accurate systolic and diastolic pressure estimation, using automated blood pressure measurement, is difficult to achieve when the transduced signals are contaminated with noise or interference, such as movement artifact. This study presents an algorithm for automated signal quality assessment in blood pressure measurement by determining the feasibility of accurately detecting systolic and diastolic pressures when corrupted with various levels of movement artifact. The performance of the proposed algorithm is compared to a manually annotated reference scoring (RS). Based on visual representations and audible playback of Korotkoff sounds, the creation of the RS involved two experts identifying sections of the recorded sounds and annotating sections of noise contamination. The experts determined the systolic and diastolic pressure in 100 recorded Korotkoff sound recordings, using a simultaneous electrocardiograph as a reference signal. The recorded Korotkoff sounds were acquired from 25 healthy subjects (16 men and 9 women) with a total of four measurements per subject. Two of these measurements contained purposely induced noise artifact caused by subject movement. Morphological changes in the cuff pressure signal and the width of the Korotkoff pulse were extracted features which were believed to be correlated with the noise presence in the recorded Korotkoff sounds. Verification of reliable Korotkoff pulses was also performed using extracted features from the oscillometric waveform as recorded from the inflatable cuff. The time between an identified noise section and a verified Korotkoff pulse was the key feature used to determine the validity of possible systolic and diastolic pressures in noise contaminated Korotkoff sounds. The performance of the algorithm was assessed based on the ability to: verify if a signal was contaminated with any noise; the accuracy, sensitivity and specificity of this noise classification, and the systolic and diastolic pressure differences between the result obtained from the algorithm and the RS. 90% of the actual noise contaminated signals were correctly identified, and a sample-wise accuracy, sensitivity and specificity of 97.0%, 80.61% and 98.16%, respectively, were obtained from 100 pooled signals. The mean systolic and diastolic differences were 0.37 ± 3.31 and 3.10 ± 5.46 mmHg, respectively, when the artifact detection algorithm was utilized, with the algorithm correctly determined if the signal was clean enough to attempt an estimation of systolic or diastolic pressures in 93% of blood pressure measurements.
format Article
author Abdul Sukora, Jumadi
Redmond, S J
Chan, G S H
Lovell, N H
author_facet Abdul Sukora, Jumadi
Redmond, S J
Chan, G S H
Lovell, N H
author_sort Abdul Sukora, Jumadi
title Signal quality measures for unsupervised blood pressure measurement
title_short Signal quality measures for unsupervised blood pressure measurement
title_full Signal quality measures for unsupervised blood pressure measurement
title_fullStr Signal quality measures for unsupervised blood pressure measurement
title_full_unstemmed Signal quality measures for unsupervised blood pressure measurement
title_sort signal quality measures for unsupervised blood pressure measurement
publisher IOP Publishing
publishDate 2012
url http://eprints.uthm.edu.my/4119/1/AJ%202019%20%28241%29.pdf
http://eprints.uthm.edu.my/4119/
https://dx.doi.org/ 10.1088/0967-3334/33/3/465
_version_ 1738581210041417728
score 13.211869

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