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Análisis de la fotopletismografía para determinación de variaciones en el tono vascular y la presión arterial : Estudio basado en redes neuronales [Photoplethysmography waveform analysis for classification of vascular tone andarterial blood pressure: Study based on neural networks]

Echeverria, N. I. (author)
Univ Nacl Mar del Plata, Fac Ingn, Lab Bioingn, ICYTE CONICET, Mar Del Plata, Buenos Aires, Argentina.
Scandurra, A. G. (author)
Univ Nacl Mar del Plata, Fac Ingn, Lab Bioingn, ICYTE CONICET, Mar Del Plata, Buenos Aires, Argentina.
Acosta, C. M. (author)
Hosp Privado Comun, Dept Anestesiol, Mar Del Plata, Buenos Aires, Argentina.
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Meschino, G. J. (author)
Suarez-Sipmann, Fernando (author)
Uppsala universitet,Klinisk fysiologi,Hedenstiernalaboratoriet,Ctr Invest Biomed Red Enfermedades Resp CIBERES, Madrid, Spain.;Hosp Univ Princesa, Dept Cuidados Crit, Madrid, Spain.
Tusman, G. (author)
Hosp Privado Comun, Dept Anestesiol, Mar Del Plata, Buenos Aires, Argentina.
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Univ Nacl Mar del Plata, Fac Ingn, Lab Bioingn, ICYTE CONICET, Mar Del Plata, Buenos Aires, Argentina Hosp Privado Comun, Dept Anestesiol, Mar Del Plata, Buenos Aires, Argentina. (creator_code:org_t)
Elsevier BV, 2023
2023
English.
In: REVISTA ESPANOLA DE ANESTESIOLOGIA Y REANIMACION. - : Elsevier BV. - 0034-9356 .- 2340-3284. ; 70:4, s. 209-217
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Background: To test whether a Shallow Neural Network (S-NN) can detect and classify vasculartone dependent changes in arterial blood pressure (ABP) by advanced photopletysmographic(PPG) waveform analysis.Methods: PPG and invasive ABP signals were recorded in 26 patients undergoing scheduled general surgery. We studied the occurrence of episodes of hypertension (systolic arterial pressure(SAP) > 140 mmHg), normotension and hypotension (SAP < 90 mmHg). Vascular tone accordingto PPG was classified in two ways: 1) By visual inspection of changes in PPG waveform amplitude and dichrotic notch position; where Classes I-II represent vasoconstriction (notch placed> 50% of PPG amplitude in small amplitude waves), Class III normal vascular tone (notch placedbetween 20-50% of PPG amplitude in normal waves) and Classes IV-V-VI vasodilation (notch <20% of PPG amplitude in large waves). 2) By an automated analysis, using S-NN trained andvalidated system that combines seven PPG derived parameters.Results: The visual assessment was precise in detecting hypotension (sensitivity 91%, specificity86% and accuracy 88%) and hypertension (sensitivity 93%, specificity 88% and accuracy 90%). Normotension presented as a visual Class III (III-III) (median and 1st-3rdquartiles), hypotensionas a Class V (IV-VI) and hypertension as a Class II (I-III); all p < 0.0001. The automated S-NNperformed well in classifying ABP conditions. The percentage of data with correct classificationby S-ANN was 83% for normotension, 94% for hypotension, and 90% for hypertension.Conclusions: Changes in ABP were correctly classified automatically by S-NN analysis of the PPGwaveform contour.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Kardiologi (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Cardiac and Cardiovascular Systems (hsv//eng)

Keyword

Arterial blood pressure
Photoplethysmography
Vascular tone
Arterial compliance
Neural networks

Publication and Content Type

ref (subject category)
art (subject category)

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