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Multimodality Video Acquisition System for the Assessment of Vital Distress in Children.
Boivin, Vincent; Shahriari, Mana; Faure, Gaspar; Mellul, Simon; Tiassou, Edem Donatien; Jouvet, Philippe; Noumeir, Rita.
Afiliação
  • Boivin V; CHU Sainte-Justine Research Centre, Montréal, QC H3T 1C5, Canada.
  • Shahriari M; Department of Electrical Engineering, Ecole de Technologie Supérieure (ETS), Montréal, QC H3C 1K3, Canada.
  • Faure G; CHU Sainte-Justine Research Centre, Montréal, QC H3T 1C5, Canada.
  • Mellul S; Department of Pediatrics, Université de Montréal (UdeM), Montréal, QC H3T 1C5, Canada.
  • Tiassou ED; CHU Sainte-Justine Research Centre, Montréal, QC H3T 1C5, Canada.
  • Jouvet P; CHU Sainte-Justine Research Centre, Montréal, QC H3T 1C5, Canada.
  • Noumeir R; CHU Sainte-Justine Research Centre, Montréal, QC H3T 1C5, Canada.
Sensors (Basel) ; 23(11)2023 Jun 02.
Article em En | MEDLINE | ID: mdl-37300019
ABSTRACT
In children, vital distress events, particularly respiratory, go unrecognized. To develop a standard model for automated assessment of vital distress in children, we aimed to construct a prospective high-quality video database for critically ill children in a pediatric intensive care unit (PICU) setting. The videos were acquired automatically through a secure web application with an application programming interface (API). The purpose of this article is to describe the data acquisition process from each PICU room to the research electronic database. Using an Azure Kinect DK and a Flir Lepton 3.5 LWIR attached to a Jetson Xavier NX board and the network architecture of our PICU, we have implemented an ongoing high-fidelity prospectively collected video database for research, monitoring, and diagnostic purposes. This infrastructure offers the opportunity to develop algorithms (including computational models) to quantify vital distress in order to evaluate vital distress events. More than 290 RGB, thermographic, and point cloud videos of each 30 s have been recorded in the database. Each recording is linked to the patient's numerical phenotype, i.e., the electronic medical health record and high-resolution medical database of our research center. The ultimate goal is to develop and validate algorithms to detect vital distress in real time, both for inpatient care and outpatient management.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Unidades de Terapia Intensiva Pediátrica / Hospitalização Tipo de estudo: Observational_studies / Prognostic_studies Limite: Child / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Unidades de Terapia Intensiva Pediátrica / Hospitalização Tipo de estudo: Observational_studies / Prognostic_studies Limite: Child / Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá