A Validation Study of Selfie Technology for Assessment of Vital Signs

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Total Enrollment

300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-11-02

Study Completion Date

2022-03-31

Brief Summary

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The aim of this study is to compare accuracy of DocMe, a video technology developed by DocMe Health Technologies, with previously validated medical devices used for measurements of heart rate, heart rate variability, respiratory rate and blood pressure in adults.

Detailed Description

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Photoplethysmography (PPG) makes uses of low-intensity infrared (IR) light. When light travels through biological tissues, it is absorbed by bones, skin pigments and both venous and arterial blood. However, as light is more strongly absorbed by blood than the surrounding tissues, the changes in blood flow can be detected by PPG sensors as changes in the intensity of light.

The signal from PPG is proportional to the quantity of blood flowing through the blood vessels and even small changes in blood volume can be detected using this method. Analysis of the waveform can provide information on a range of physiological measurements affecting the cardiovascular and respiratory systems. PPG is widely used in medicine in the form of pulse oximeters using sensors applied to peripheral digits.

Recently, it has been shown that PPG data can be obtained using images acquired from videos taken using the camera on smartphones and there is now a significant and growing body of published literature to support this.

DocMe Health Technologies has developed a system of obtaining these data using a video selfie.

At this time, the technology has been shown to be reasonably accurate when compared to home devices in healthy subjects. However, to make the technology more widely useful, the results obtained by video selfies need to be formally validated.

The aim of the study therefore is to compare measurements obtained from video selfies with measurements taken using already validated machines in the same patients.

Conditions

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Healthy Hypertension

Keywords

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Photoplethysmography Video Selfie Vital Signs Blood Pressure Oxygen Saturation Smartphone DocMe Heart Rate Respiratory Rate

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Adults (18 - 100 years old). Participants must be willing and able to give informed consent for participation in the study, and considered fit for the study by the nurse.

Exclusion Criteria

* None

Minimum Eligible Age

18 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Alex T Novak, MRCGP FRCEM

Role: PRINCIPAL_INVESTIGATOR

Oxford University Hospitals NHS Trust

Locations

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Oxford University Hospitals NHS Foundation

Oxford, Oxfordshire, United Kingdom

Site Status

Countries

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United Kingdom

References

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Barszczyk A, Lee K. Measuring Blood Pressure: from Cuff to Smartphone. Curr Hypertens Rep. 2019 Oct 10;21(11):84. doi: 10.1007/s11906-019-0990-3.

Reference Type BACKGROUND

PMID: 31599362 (View on PubMed)

Luo H, Yang D, Barszczyk A, Vempala N, Wei J, Wu SJ, Zheng PP, Fu G, Lee K, Feng ZP. Smartphone-Based Blood Pressure Measurement Using Transdermal Optical Imaging Technology. Circ Cardiovasc Imaging. 2019 Aug;12(8):e008857. doi: 10.1161/CIRCIMAGING.119.008857. Epub 2019 Aug 6.

Reference Type BACKGROUND

PMID: 31382766 (View on PubMed)

Chowdhury MH, Shuzan MNI, Chowdhury MEH, Mahbub ZB, Uddin MM, Khandakar A, Reaz MBI. Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques. Sensors (Basel). 2020 Jun 1;20(11):3127. doi: 10.3390/s20113127.

Reference Type BACKGROUND

PMID: 32492902 (View on PubMed)

Humphreys K, Ward T, Markham C. Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry. Rev Sci Instrum. 2007 Apr;78(4):044304. doi: 10.1063/1.2724789.

Reference Type BACKGROUND

PMID: 17477684 (View on PubMed)

Kong L, Zhao Y, Dong L, Jian Y, Jin X, Li B, Feng Y, Liu M, Liu X, Wu H. Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. Opt Express. 2013 Jul 29;21(15):17464-71. doi: 10.1364/OE.21.017464.

Reference Type BACKGROUND

PMID: 23938616 (View on PubMed)

Other Identifiers

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PRFX-2020-01

Identifier Type: -

Identifier Source: org_study_id

A Validation Study of Selfie Technology for Assessment of Vital Signs

Study Results

Basic Information

Brief Summary

Detailed Description

Conditions

Keywords

Study Design

Eligibility Criteria

Inclusion Criteria

Exclusion Criteria

Sponsors

Oxford University Hospitals NHS Trust

DocMe Technologies Ltd

Responsible Party

Principal Investigators

Alex T Novak, MRCGP FRCEM

Locations

Oxford University Hospitals NHS Foundation

Countries

References

Barszczyk A, Lee K. Measuring Blood Pressure: from Cuff to Smartphone. Curr Hypertens Rep. 2019 Oct 10;21(11):84. doi: 10.1007/s11906-019-0990-3.

Luo H, Yang D, Barszczyk A, Vempala N, Wei J, Wu SJ, Zheng PP, Fu G, Lee K, Feng ZP. Smartphone-Based Blood Pressure Measurement Using Transdermal Optical Imaging Technology. Circ Cardiovasc Imaging. 2019 Aug;12(8):e008857. doi: 10.1161/CIRCIMAGING.119.008857. Epub 2019 Aug 6.

Chowdhury MH, Shuzan MNI, Chowdhury MEH, Mahbub ZB, Uddin MM, Khandakar A, Reaz MBI. Estimating Blood Pressure from the Photoplethysmogram Signal and Demographic Features Using Machine Learning Techniques. Sensors (Basel). 2020 Jun 1;20(11):3127. doi: 10.3390/s20113127.

Humphreys K, Ward T, Markham C. Noncontact simultaneous dual wavelength photoplethysmography: a further step toward noncontact pulse oximetry. Rev Sci Instrum. 2007 Apr;78(4):044304. doi: 10.1063/1.2724789.

Kong L, Zhao Y, Dong L, Jian Y, Jin X, Li B, Feng Y, Liu M, Liu X, Wu H. Non-contact detection of oxygen saturation based on visible light imaging device using ambient light. Opt Express. 2013 Jul 29;21(15):17464-71. doi: 10.1364/OE.21.017464.

Other Identifiers

PRFX-2020-01