Blood Pressure Drop Prediction by using HRV Measurements in Orthostatic Hypotension.

Orthostatic Hypotension is defined as a reduction of systolic and diastolic blood pressure within 3 minutes of standing, and may cause dizziness and loss of balance. Orthostatic Hypotension has been considered an important risk factor for falls since 1960. This paper presents a model to predict the...

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Publicado en:Journal of Medical Systems Vol. 39; no. 11; pp. 1 - 8
Autores principales: Sannino, Giovanna, Melillo, Paolo, Stranges, Saverio, Pietro, Giuseppe, Pecchia, Leandro
Formato: equations & formulas research tables/charts Journal Article
Publicado: Springer Nature Nov2015
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Nov2015
      vid: 39
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      pub: Springer Nature
      place: New York, New York
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        10.1007/s10916-015-0292-5
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        atl: Blood Pressure Drop Prediction by using HRV Measurements in Orthostatic Hypotension.
      aug:
        au:
          Sannino, Giovanna
          Melillo, Paolo
          Stranges, Saverio
          Pietro, Giuseppe
          Pecchia, Leandro
        affil: Institute of High Performance Computing and Networking (ICAR - CNR), via pietro castellino 111-80131 Naples Italy
      sug:
        subj:
          Heart Rate Variability
          Hypotension, Orthostatic
          Systolic Pressure
          Human
          Electrocardiography
          Accidental Falls Risk Factors
          Research Protocols
          Experimental Studies
          Data Analysis Software
          Models, Statistical
      ab: Orthostatic Hypotension is defined as a reduction of systolic and diastolic blood pressure within 3 minutes of standing, and may cause dizziness and loss of balance. Orthostatic Hypotension has been considered an important risk factor for falls since 1960. This paper presents a model to predict the systolic blood pressure drop due to orthostatic hypotension, relying on heart rate variability measurements extracted from 5 minute ECGs recorded before standing. This model was developed and validated with the leave-one-out cross-validation technique involving 10 healthy subjects, and finally tested with an additional 5 healthy subjects, whose data were not used during the training and cross-validation process. The results show that the model predicts correctly the systolic blood pressure drop in 80 % of all experiments, with an error rate below the measurement error of a sphygmomanometer digital device.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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