Artículo
Using entropies to monitoring intracranial pressure, evidence from an animal model
Pose, Fernando Ezequiel
; Videla, Carlos; Campanini Scigliano, Giovanni Denis
; Ciarrocchi, Nicolas Marcelo; Redelico, Francisco Oscar
Fecha de publicación:
09/2023
Editorial:
Elsevier
Revista:
Biomedical Signal Processing and Control
ISSN:
1746-8094
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
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.
Palabras clave:
ENTROPY
,
INTRACRANIAL COMPLIANCE
,
INTRACRANIAL PRESSURE MONITORING
Archivos asociados
Licencia
Identificadores
Colecciones
Articulos (IMTIB)
Articulos de INSTITUTO DE MEDICINA TRASLACIONAL E INGENIERIA BIOMEDICA
Articulos de INSTITUTO DE MEDICINA TRASLACIONAL E INGENIERIA BIOMEDICA
Citación
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
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