Trends and seasonality extracting from Home Blood Pressure Monitoring readings. (2018)
- Record Type:
- Journal Article
- Title:
- Trends and seasonality extracting from Home Blood Pressure Monitoring readings. (2018)
- Main Title:
- Trends and seasonality extracting from Home Blood Pressure Monitoring readings
- Authors:
- Chuiko, G.P.
Dvornik, O.V.
Shyian, I.A.
Baganov, Ye.A. - Abstract:
- Abstract: Purpose: The aim is the first application of Singular Spectrum Analysis for computer processing of Home Blood Pressure Monitoring (HBPM). An illustration of the method advantages is the additional objective. Method: The Singular Spectrum Analysis (SSA) is a way of trend and seasonality extraction. SSA is suitable for short series with noises. It is also useful for the variability analysis. As well, it is simply programmable in a high-level programming language. Here Maple 18 was in use. Results: Trends and the slowest oscillations were obtained within a case study. The error of SSA estimations turned out to be close to the exactness of measuring. However, these errors are in good agreement with the known descriptors of the short-time variability. The periods of the slowest oscillations were different for the systolic and the diastolic pressures. Seasonality was about six months and about two months respectively. We found the amplitude of the slowest oscillations of heart rate varies in time. This fact is in contrast to the blood pressure fluctuations, for which the amplitudes are stable. Conclusions: SSA is a promising tool for HBPM data processing. It ensures smooth and readable trends as well as shows the long-term variability of series. This information can be usable for clinical decision-making and prognostics. Highlights: The Singular Spectrum Analysis (SSA) turned out an excellent way to the trend extracting of short series. The Home Blood Pressure MonitoringAbstract: Purpose: The aim is the first application of Singular Spectrum Analysis for computer processing of Home Blood Pressure Monitoring (HBPM). An illustration of the method advantages is the additional objective. Method: The Singular Spectrum Analysis (SSA) is a way of trend and seasonality extraction. SSA is suitable for short series with noises. It is also useful for the variability analysis. As well, it is simply programmable in a high-level programming language. Here Maple 18 was in use. Results: Trends and the slowest oscillations were obtained within a case study. The error of SSA estimations turned out to be close to the exactness of measuring. However, these errors are in good agreement with the known descriptors of the short-time variability. The periods of the slowest oscillations were different for the systolic and the diastolic pressures. Seasonality was about six months and about two months respectively. We found the amplitude of the slowest oscillations of heart rate varies in time. This fact is in contrast to the blood pressure fluctuations, for which the amplitudes are stable. Conclusions: SSA is a promising tool for HBPM data processing. It ensures smooth and readable trends as well as shows the long-term variability of series. This information can be usable for clinical decision-making and prognostics. Highlights: The Singular Spectrum Analysis (SSA) turned out an excellent way to the trend extracting of short series. The Home Blood Pressure Monitoring data were first and successfully analyzed by SSA. The slowest oscillations of systolic and diastolic pressures have quite different periods. … (more)
- Is Part Of:
- Informatics in medicine unlocked. Volume 10(2018)
- Journal:
- Informatics in medicine unlocked
- Issue:
- Volume 10(2018)
- Issue Display:
- Volume 10, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 10
- Issue:
- 2018
- Issue Sort Value:
- 2018-0010-2018-0000
- Page Start:
- 45
- Page End:
- 49
- Publication Date:
- 2018
- Subjects:
- Home blood pressure monitoring -- Singular spectrum analysis -- Trend -- Long-term variability -- Computer signal processing
Medical informatics -- Periodicals
610.285 - Journal URLs:
- http://www.sciencedirect.com/science/journal/23529148/ ↗
http://www.sciencedirect.com/ ↗ - DOI:
- 10.1016/j.imu.2017.12.001 ↗
- Languages:
- English
- ISSNs:
- 2352-9148
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6110.xml