Predictive Remote Photoplethysmography Algorithm for Blood Pressure Pressure Assessment and Monitoring

NCT ID: NCT06320847

Last Updated: 2024-03-20

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 300 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-01-02
• Study Completion Date: 2024-12-31

Brief Summary

Significant advancements in the field of medical technologies have resulted in the rise of contact-free methods of haemodynamic monitoring. Remote photoplethysmography (rPPG) is a videobased, contactless form of monitoring that operates through a camera-enabled device. This innovation interprets minute variations in skin colour due to blood flow which, when analysed with complex signal processing algorithms, generates vital sign readings. Currently, Nervotec's rPPG technology allows for the collection of rPPG waveforms, which enables the measurement of heart rate, heart rate variability, respiration rate and blood oxygen saturation (SpO2) level through signal processing techniques. The plethysmography signals can be used to estimate blood pressure through the creation and training of a predictive model. By examining and extracting key features of a continuous PPG waveform by training an artificial neural network, correlations between these features and BP can be studied.

Detailed Description

This is a prospective, feasibility study.Background literature has shown that plethysmography (PPG) signals can be used to estimate blood pressure through the creation and training of a predictive model. By examining and extracting key features of a continuous PPG waveform by training an artificial neural network, correlations between these features and blood pressure can be studied.

Nervotec, a digital health and AI company , has successfully used rPPG technology to allow for collection of rPPG waveforms, which enables the measurement of heart rate (HR), heart rate variability (HRV), respiration rate (RR) and blood oxygen saturation (SpO2) level through signal processing techniques. They have incorporated rPPG technology into a mobile application using smartphone cameras for scanning an individual's face. However, this is yet to be established for blood pressure. We aim to perform a prospective study to evaluate the feasibility and accuracy of obtaining blood pressure measurements through rPPG.

Hypothesis: Remote photoplethysmography can be used to determine blood pressure and this algorithm can develop into a customised smartphone based application.

Conditions

Remote Photoplethysmography , Blood Pressure

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: HEALTH_SERVICES_RESEARCH
• Blinding Strategy: NONE

Interventions

rPPG

A pulse oximeter and blood pressure cuff will be applied on the study patient by the study team member (research coordinators). At the same time, vital signs from Nervotec's rPPG technology will be recorded via the laptop and webcam. Synchronous measurement process of heart rate, respiration rate, pulse oximetry, heart rate variability and blood pressure estimates using Nervotec rPPG technology will take place for a duration of 3 minutes.

Intervention Type: DIAGNOSTIC_TEST

Eligibility Criteria

Inclusion Criteria

• Age ≥ 21 years old
• Ability to provide informed consent
• Any surgery except head and neck surgeries

Exclusion Criteria

• Age ≤ 21 years old
• Inability to provide informed consent
• Patients going for head and neck surgery

• Minimum Eligible Age: 21 Years
• Maximum Eligible Age: 100 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Nervotec Pte. Ltd.

UNKNOWN

Sponsor Role: collaborator

Singapore General Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Locations

Singapore General Hospital

Singapore, , Singapore

Site Status: RECRUITING

Countries

Singapore

Facility Contacts

Hairil Rizal Abdullah

Role: primary

hairil.rizal.abdullah@singhealth.com.sg

63265428

Other Identifiers

Predictbloodpressure

Identifier Type: -

Identifier Source: org_study_id