Multimodality Video Acquisition System for the Assessment of Vital Distress in Children.
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.
Palavras-chave
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