Description Module
The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.
Description Module path is as follows:
Study -> Protocol Section -> Description Module
Description Module
Ignite Creation Date:
2025-12-24 @ 11:04 PM
Ignite Modification Date:
2025-12-24 @ 11:04 PM
NCT ID:
NCT05202769
Brief Summary:
This study is aimed at non-invasive extraction of cardiovascular and respiratory parameters from red-green-blue (RGB) and thermal imaging cameras from patients in the intensive care unit (ICU) setting. The main focus of this study is in assessing the feasibility of implementing such a camera-based system for prolonged monitoring of patients, identifying limiting factors which may interfere with accuracy or practical aspects of the system, and postulating solutions to overcoming these.
Detailed Description:
Non-invasive monitoring of vital signs is an area that is gaining increasing popularity in clinical practise due to its advantages of increased comfort to patients and reduced risk of transmission of multidrug resistant organisms. This study aims to assess the feasibility of using RGB cameras and thermal imaging cameras for monitoring of heart rate and rhythm and respiratory rate and rhythm in the intensive care setting.
Videos of patients are taken in the ICU of a Maltese University-affiliated tertiary hospital (Mater Dei Hospital) under varying conditions, including varying light intensity, different patient positions and periods of time where clinical staff are performing regular care tasks and minor interventions such as bloodletting. Patients enrolled will be able to provide consent for the study after being given a detailed explanation of the study aims, data collected, data storage and processing and any other information they may wish to know.
The video data will be analysed via a convolutional neural network which has been previously trained to extract cardiovascular and respiratory parameters from videos taken from healthy volunteers in a non-clinical setting (a laboratory located in the University of Malta). The heart rate and respiratory rate extracted from patient videos are then compared to ground truth data obtained by current gold standard contact monitoring (data collected from Phillips Intellivue monitors used throughout the ICU) and assessed for accuracy. The practicality of setting up a camera-based system in the intensive care setting and potential means of overcoming limitations faced will also be tackled in this study from a qualitative aspect.
Study:
NCT05202769
Study Brief:
Protocol Section:
NCT05202769