Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements
The blood pressure patterns obtained from a linearly or stepwise deflating cuff exhibit personalized traits, such as fairly uniform peak patterns and regular beat geometry; it can support the diagnosis and monitoring of hypertensive patients with reduced sensitivity to fluctuations in Blood Pressure...
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| Format: | Article |
| Language: | English |
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Wiley
2012-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2012/591252 |
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| author | Young-Suk Shin |
| author_facet | Young-Suk Shin |
| author_sort | Young-Suk Shin |
| collection | DOAJ |
| description | The blood pressure patterns obtained from a linearly or stepwise deflating cuff exhibit personalized traits, such as fairly uniform peak patterns and regular beat geometry; it can support the diagnosis and monitoring of hypertensive patients with reduced sensitivity to fluctuations in Blood Pressure (BP) over time. Monitoring of personalized trait in Oscillometric Arterial Blood Pressure Measurements (OABPM) uses the Linear Discriminant Analysis (LDA) algorithm. The representation of personalized traits with features from the oscillometric waveforms using LDA algorithm includes four phases. Data collection consists of blood pressure data using auscultatory measurements and pressure oscillations data obtained from the oscillometric method. Preprocessing involves the normalization of various sized oscillometric waveforms to a uniform size. Feature extraction involves the use of features from oscillometric amplitudes, and trait identification involves the use of the LDA algorithm. In this paper, it presents a novel OABPM-based blood pressure monitoring system that can monitor personalized blood pressure pattern. Our approach can reduce sensitivity to fluctuations in blood pressure with the features extracted from the whole area in oscillometric arterial blood pressure measurement. Therefore this technique offers reliable blood pressure patterns. This study provides a cornerstone for the diagnosis and management of hypertension in the foreseeable future. |
| format | Article |
| id | doaj-art-cda24d4295b344b1bed2734bf5580094 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2012-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-cda24d4295b344b1bed2734bf55800942025-02-03T01:07:45ZengWileyJournal of Applied Mathematics1110-757X1687-00422012-01-01201210.1155/2012/591252591252Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure MeasurementsYoung-Suk Shin0Department of Information and Communication Engineering, Chosun University, 375 Seosuk-dong, Dong-gu, Gwangju 501-759, Republic of KoreaThe blood pressure patterns obtained from a linearly or stepwise deflating cuff exhibit personalized traits, such as fairly uniform peak patterns and regular beat geometry; it can support the diagnosis and monitoring of hypertensive patients with reduced sensitivity to fluctuations in Blood Pressure (BP) over time. Monitoring of personalized trait in Oscillometric Arterial Blood Pressure Measurements (OABPM) uses the Linear Discriminant Analysis (LDA) algorithm. The representation of personalized traits with features from the oscillometric waveforms using LDA algorithm includes four phases. Data collection consists of blood pressure data using auscultatory measurements and pressure oscillations data obtained from the oscillometric method. Preprocessing involves the normalization of various sized oscillometric waveforms to a uniform size. Feature extraction involves the use of features from oscillometric amplitudes, and trait identification involves the use of the LDA algorithm. In this paper, it presents a novel OABPM-based blood pressure monitoring system that can monitor personalized blood pressure pattern. Our approach can reduce sensitivity to fluctuations in blood pressure with the features extracted from the whole area in oscillometric arterial blood pressure measurement. Therefore this technique offers reliable blood pressure patterns. This study provides a cornerstone for the diagnosis and management of hypertension in the foreseeable future.http://dx.doi.org/10.1155/2012/591252 |
| spellingShingle | Young-Suk Shin Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements Journal of Applied Mathematics |
| title | Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements |
| title_full | Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements |
| title_fullStr | Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements |
| title_full_unstemmed | Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements |
| title_short | Monitoring Personalized Trait Using Oscillometric Arterial Blood Pressure Measurements |
| title_sort | monitoring personalized trait using oscillometric arterial blood pressure measurements |
| url | http://dx.doi.org/10.1155/2012/591252 |
| work_keys_str_mv | AT youngsukshin monitoringpersonalizedtraitusingoscillometricarterialbloodpressuremeasurements |