Identification of blood pressure reflecting personalized traits using bilateral photoplethysmography.
Blood pressure
linear discriminant analysis
maximum low amplitudes
personalized trait
photoplethysmography
Journal
Technology and health care : official journal of the European Society for Engineering and Medicine
ISSN: 1878-7401
Titre abrégé: Technol Health Care
Pays: Netherlands
ID NLM: 9314590
Informations de publication
Date de publication:
2020
2020
Historique:
pubmed:
5
5
2020
medline:
7
4
2021
entrez:
5
5
2020
Statut:
ppublish
Résumé
Blood pressure (BP) is currently diagnosed by cuff-based devices, which are inconvenient and provide discontinuous measurements. Photoplethysmography (PPG)-based cuffless techniques have recently been used to accurately estimate both systolic BP (SBP) and diastolic BP (DBP). However, it is difficult to use these SBP and DBP estimations to reflect the personalized traits in the peripheral vascular condition; thus, their accuracy is limited. The purpose of this study is to describe a technique that can be distinguished simply among three BP categories (normotensive, prehypertensive, and hypertensive) and reflect individual traits using PPG only. We measured BP over 120 s using the fingers of 105 subjects. The PPG waveforms varied in size and amplitude over time. Therefore, normalization for uniform features for individual traits was done after the extracted waveforms were divided into multiple windows. The feature is determined by the lowest amplitude in the waveform within each divided window. The features have been applied to distinguish three BP categories using the first-eigenvector (1-EV) and second-eigenvector (2-EV) in linear discriminant analysis. The best decision boundary for each BP category was estimated using 1-EV (-0.02 to +0.02) and 2-EV (>+0.02) in the hypertensive category, 1-EV (< 0) and 2-EV (⩽+0.02) in the prehypertensive category, and 1-EV (⩾-0.02) and 2-EV (⩽+0.02) in the normotensive category. The overlap range with 1-EV (-0.02 to 0) and 2-EV (⩽+0.02) in particular accurately reflected individual traits. Discrimination among the three BP categories reflecting individual traits was successfully achieved using PPG. This method could improve limitations of cuff-based techniques.
Sections du résumé
BACKGROUND
BACKGROUND
Blood pressure (BP) is currently diagnosed by cuff-based devices, which are inconvenient and provide discontinuous measurements. Photoplethysmography (PPG)-based cuffless techniques have recently been used to accurately estimate both systolic BP (SBP) and diastolic BP (DBP). However, it is difficult to use these SBP and DBP estimations to reflect the personalized traits in the peripheral vascular condition; thus, their accuracy is limited.
OBJECTIVE
OBJECTIVE
The purpose of this study is to describe a technique that can be distinguished simply among three BP categories (normotensive, prehypertensive, and hypertensive) and reflect individual traits using PPG only.
METHODS
METHODS
We measured BP over 120 s using the fingers of 105 subjects. The PPG waveforms varied in size and amplitude over time. Therefore, normalization for uniform features for individual traits was done after the extracted waveforms were divided into multiple windows. The feature is determined by the lowest amplitude in the waveform within each divided window. The features have been applied to distinguish three BP categories using the first-eigenvector (1-EV) and second-eigenvector (2-EV) in linear discriminant analysis.
RESULTS
RESULTS
The best decision boundary for each BP category was estimated using 1-EV (-0.02 to +0.02) and 2-EV (>+0.02) in the hypertensive category, 1-EV (< 0) and 2-EV (⩽+0.02) in the prehypertensive category, and 1-EV (⩾-0.02) and 2-EV (⩽+0.02) in the normotensive category. The overlap range with 1-EV (-0.02 to 0) and 2-EV (⩽+0.02) in particular accurately reflected individual traits.
CONCLUSION
CONCLUSIONS
Discrimination among the three BP categories reflecting individual traits was successfully achieved using PPG. This method could improve limitations of cuff-based techniques.
Identifiants
pubmed: 32364154
pii: THC209022
doi: 10.3233/THC-209022
pmc: PMC7369108
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
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