Cargando…
Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study
BACKGROUND: Outside of a clinical setting, oscillometric devices make remote monitoring of blood pressure and virtual care more convenient and feasible. HeartBeat Technologies Ltd developed a novel approach to measuring blood pressure remotely after an initial blood pressure reading by a nurse using...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105754/ https://www.ncbi.nlm.nih.gov/pubmed/33890856 http://dx.doi.org/10.2196/19187 |
_version_ | 1783689663127486464 |
---|---|
author | Holyoke, Paul Yogaratnam, Karthika Kalles, Elizabeth |
author_facet | Holyoke, Paul Yogaratnam, Karthika Kalles, Elizabeth |
author_sort | Holyoke, Paul |
collection | PubMed |
description | BACKGROUND: Outside of a clinical setting, oscillometric devices make remote monitoring of blood pressure and virtual care more convenient and feasible. HeartBeat Technologies Ltd developed a novel approach to measuring blood pressure remotely after an initial blood pressure reading by a nurse using the conventional measurement method. Using a finger pulse oximeter, a photoplethysmogram wave is transmitted by Bluetooth to a smartphone or tablet. A smartphone app (MediBeat) transmits the photoplethysmogram to a server for analysis by a proprietary algorithm—the person’s current blood pressure is sent back to the smartphone and to the individual’s health care provider. OBJECTIVE: This study sought to determine whether the HeartBeat algorithm calculates blood pressure as accurately as required by the European Society of Hypertension International Protocol revision 2010 (ESH-IP2) for validation of blood pressure measuring devices. METHODS: ESH-IP2 requirements, modified to conform to a more recent international consensus statement, were followed. The ESH-IP2 establishes strict guidelines for the conduct and reporting of any validation of any device to measure blood pressure, including using the standard manual blood pressure instrument as a comparator and specific required accuracy levels for low, medium, and high ranges of blood pressure readings. The consensus statement requires a greater number of study participants for each of the blood pressure ranges. The validation of the accuracy of the algorithm was conducted with a Contec CMS50EW pulse oximeter and a Samsung Galaxy XCover 4 smartphone. RESULTS: The differences between the HeartBeat-calculated and the manually measured blood pressures of 62 study participants did not meet the ESH-IP2 standards for accuracy for either systolic or diastolic blood pressure measurements. There was no discernible pattern in the inaccuracies of the HeartBeat-calculated measurements. CONCLUSIONS: The October 4, 2019 version of the HeartBeat algorithm, implemented in combination with the MediBeat app, a pulse oximeter, and an Android smartphone, was not sufficiently accurate for use in a general adult population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04082819; http://clinicaltrials.gov/ct2/show/NCT04082819 |
format | Online Article Text |
id | pubmed-8105754 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-81057542021-05-12 Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study Holyoke, Paul Yogaratnam, Karthika Kalles, Elizabeth J Med Internet Res Original Paper BACKGROUND: Outside of a clinical setting, oscillometric devices make remote monitoring of blood pressure and virtual care more convenient and feasible. HeartBeat Technologies Ltd developed a novel approach to measuring blood pressure remotely after an initial blood pressure reading by a nurse using the conventional measurement method. Using a finger pulse oximeter, a photoplethysmogram wave is transmitted by Bluetooth to a smartphone or tablet. A smartphone app (MediBeat) transmits the photoplethysmogram to a server for analysis by a proprietary algorithm—the person’s current blood pressure is sent back to the smartphone and to the individual’s health care provider. OBJECTIVE: This study sought to determine whether the HeartBeat algorithm calculates blood pressure as accurately as required by the European Society of Hypertension International Protocol revision 2010 (ESH-IP2) for validation of blood pressure measuring devices. METHODS: ESH-IP2 requirements, modified to conform to a more recent international consensus statement, were followed. The ESH-IP2 establishes strict guidelines for the conduct and reporting of any validation of any device to measure blood pressure, including using the standard manual blood pressure instrument as a comparator and specific required accuracy levels for low, medium, and high ranges of blood pressure readings. The consensus statement requires a greater number of study participants for each of the blood pressure ranges. The validation of the accuracy of the algorithm was conducted with a Contec CMS50EW pulse oximeter and a Samsung Galaxy XCover 4 smartphone. RESULTS: The differences between the HeartBeat-calculated and the manually measured blood pressures of 62 study participants did not meet the ESH-IP2 standards for accuracy for either systolic or diastolic blood pressure measurements. There was no discernible pattern in the inaccuracies of the HeartBeat-calculated measurements. CONCLUSIONS: The October 4, 2019 version of the HeartBeat algorithm, implemented in combination with the MediBeat app, a pulse oximeter, and an Android smartphone, was not sufficiently accurate for use in a general adult population. TRIAL REGISTRATION: ClinicalTrials.gov NCT04082819; http://clinicaltrials.gov/ct2/show/NCT04082819 JMIR Publications 2021-04-23 /pmc/articles/PMC8105754/ /pubmed/33890856 http://dx.doi.org/10.2196/19187 Text en ©Paul Holyoke, Karthika Yogaratnam, Elizabeth Kalles. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 23.04.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Holyoke, Paul Yogaratnam, Karthika Kalles, Elizabeth Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title | Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title_full | Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title_fullStr | Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title_full_unstemmed | Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title_short | Web-Based Smartphone Algorithm for Calculating Blood Pressure From Photoplethysmography Remotely in a General Adult Population: Validation Study |
title_sort | web-based smartphone algorithm for calculating blood pressure from photoplethysmography remotely in a general adult population: validation study |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8105754/ https://www.ncbi.nlm.nih.gov/pubmed/33890856 http://dx.doi.org/10.2196/19187 |
work_keys_str_mv | AT holyokepaul webbasedsmartphonealgorithmforcalculatingbloodpressurefromphotoplethysmographyremotelyinageneraladultpopulationvalidationstudy AT yogaratnamkarthika webbasedsmartphonealgorithmforcalculatingbloodpressurefromphotoplethysmographyremotelyinageneraladultpopulationvalidationstudy AT kalleselizabeth webbasedsmartphonealgorithmforcalculatingbloodpressurefromphotoplethysmographyremotelyinageneraladultpopulationvalidationstudy |