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dc.contributor.author
Pose, Fernando Ezequiel  
dc.contributor.author
Videla, Carlos  
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Campanini Scigliano, Giovanni Denis  
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Ciarrocchi, Nicolas Marcelo  
dc.contributor.author
Redelico, Francisco Oscar  
dc.date.available
2024-02-20T14:39:58Z  
dc.date.issued
2023-09  
dc.identifier.citation
Pose, Fernando Ezequiel; Videla, Carlos; Campanini Scigliano, Giovanni Denis; Ciarrocchi, Nicolas Marcelo; Redelico, Francisco Oscar; Using entropies to monitoring intracranial pressure, evidence from an animal model; Elsevier; Biomedical Signal Processing and Control; 86; 9-2023; 1-12  
dc.identifier.issn
1746-8094  
dc.identifier.uri
http://hdl.handle.net/11336/227606  
dc.description.abstract
Intracranial hypertension (ICH) is associated with worse neurological outcomes and increased mortality. Therefore, its correct monitoring is very important in neurological intensive care and the operating room. There have been successful attempts to use entropic quantifiers to monitor intracranial pressure (ICP);however, they have not been compared against each other to analyze their properties. In this study, we conducted an animal experiment on intracranial hypertension and analyzed the data to determine the efficacy of the most commonly used entropies in literature, namely, Approximate Entropy, Sample Entropy, Permutation Entropy, and Wavelet Entropy. Our analysis revealed that Wavelet Entropy exhibited the best early warning properties, detecting a median insult value of 10.34 ml, 147 s before the ICP reached 20 mmHg, when the ICP median value was 8.37 mmHg. Although all the entropies showed a decomplexing effect on the ICP signal, Wavelet Entropy was the most sensitive, possibly due to the frequency-dependent nature of brain compliance.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
ENTROPY  
dc.subject
INTRACRANIAL COMPLIANCE  
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INTRACRANIAL PRESSURE MONITORING  
dc.subject.classification
Neurociencias  
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Medicina Básica  
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CIENCIAS MÉDICAS Y DE LA SALUD  
dc.title
Using entropies to monitoring intracranial pressure, evidence from an animal model  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-02-20T12:34:34Z  
dc.journal.volume
86  
dc.journal.pagination
1-12  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Pose, Fernando Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentina  
dc.description.fil
Fil: Videla, Carlos. Hospital Italiano; Argentina  
dc.description.fil
Fil: Campanini Scigliano, Giovanni Denis. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentina  
dc.description.fil
Fil: Ciarrocchi, Nicolas Marcelo. Hospital Italiano; Argentina  
dc.description.fil
Fil: Redelico, Francisco Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Medicina Traslacional e Ingeniería Biomédica - Hospital Italiano. Instituto de Medicina Traslacional e Ingeniería Biomédica.- Instituto Universitario Hospital Italiano de Buenos Aires. Instituto de Medicina Traslacional e Ingeniería Biomédica; Argentina  
dc.journal.title
Biomedical Signal Processing and Control  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.bspc.2023.105320