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Non-Invasive Vital Signs Monitoring (NIVS) Project

Non-Invasive Vital Signs Monitoring (NIVS) Project

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05202769
Acronym
NIVS
Enrollment
40
Registered
2022-01-21
Start date
2022-02-11
Completion date
2023-12-31
Last updated
2022-10-27

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hemodynamic Monitoring, Monitoring, Physiologic

Keywords

Non-invasive monitoring, RGB camera, thermal camera

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.

Interventions

OTHERVideo filming

Video clips taken using RGB and thermal imaging cameras under varying conditions of lighting, movement and procedures taking place.

Sponsors

University of Malta
CollaboratorOTHER
Sciberras, Stephen M.D.
Lead SponsorINDIV

Study design

Observational model
CASE_ONLY
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to 95 Years
Healthy volunteers
Yes

Inclusion criteria

* age above 18 years and able to provide consent

Exclusion criteria

* age under 18 years and known cardiovascular or respiratory diseases

Design outcomes

Primary

MeasureTime frame
Respiratory rate as measured by a camera system1 day
Heart Rate, as measured by a camera system1 day

Secondary

MeasureTime frame
To assess the accuracy of parameters obtained via the camera-based system as compared to the traditional contact monitoring system.1 day

Countries

Malta

Contacts

Primary ContactNicole Grech, MD
nicole.grech@gov.mt+35625457234

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026