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| Name | Class |
|---|---|
| Oxford University Hospitals NHS Trust | OTHER |
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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.
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.
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| Measure | Description | Time Frame |
|---|---|---|
| Heart Rate | Heart Rate (beats/minute) assessed 3 times at 10 minute intervals on one occasion | Baseline |
| Respiratory Rate | Respiratory Rate in breaths/min assessed visually or oximeter if it has the capability assessed 3 times at 10 minute intervals on one occasion | Baseline |
| Heart Rate Variability | Heart Rate (beats/minute) assessed 3 times at 10 minute intervals on one occasion | Baseline |
| Blood Pressure | Systolic and Diastolic Blood Pressure assessed 3 times at 10 minute intervals on one occasion | Baseline |
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Inclusion Criteria:
Exclusion Criteria:
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Study Population:
We will seek to adhere to ISO (81060-2:2018)guidelines and AHA BP consensus standards.
at least 5% population reference range systolic BP <100mmHg at least 5% population reference range systolic BP >160mmHg at least 20% population reference range systolic BP >140mmHg at least 5% population reference range diastolic BP <60mmHg at least 5% population reference range diastolic BP >100mmHg at least 20% population reference range diastolic BP >80mmHg
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| Name | Affiliation | Role |
|---|---|---|
| Alex T Novak, MRCGP FRCEM | Oxford University Hospitals NHS Trust | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Oxford University Hospitals NHS Foundation | Oxford | Oxfordshire | OX3 9DU | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31599362 | Background | 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. | |
| 31382766 | Background | 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. |
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| ID | Term |
|---|---|
| D006973 | Hypertension |
| ID | Term |
|---|---|
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
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| 32492902 | Background | 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. |
| 17477684 | Background | 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. |
| 23938616 | Background | 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. |