Patrick Schoettker1, Jean Degott1, Gregory Hofmann1, Martin Proença2, Guillaume Bonnier2, Alia Lemkaddem2, Mathieu Lemay2, Raoul Schorer3, Urvan Christen4, Jean‑François Knebel4, Arlene Wuerzner5, Michel Burnier5 and Gregoire Wuerzner5
Blood pressure measurements with the OptiBP smartphone app validated against reference auscultatory measurements
Scientific Reports Vol. 10, Article number: 17827 (2020)
DOI: 10.1038/s41598-020-74955-4
1Department of Anesthesiology, Lausanne University Hospital and University of Lausanne (CH)
2CSEM, Swiss Center for Electronics and Microtechnology, Neuchâtel (CH)
3Department of Acute Medicine, Geneva University Hospital and University of Geneva, (CH)
4Biospectal SA, 1003 Lausanne (CH)
5Service of Nephrology and Hypertension, Lausanne University Hospital and University of Lausanne, (CH)
Abstract: Mobile health diagnostics have been shown to be efective and scalable for chronic disease detection and management. By maximizing the smartphones’ optics and computational power, they could allow assessment of physiological information from the morphology of pulse waves and thus estimate cufess blood pressure (BP). We trained the parameters of an existing pulse wave analysis algorithm (oBPM), previously validated in anaesthesia on pulse oximeter signals, by collecting optical signals from 51 patients fngertips via a smartphone while simultaneously acquiring BP measurements through an arterial catheter. We then compared smartphone-based measurements obtained on 50 participants in an ambulatory setting via the OptiBP app against simultaneously acquired auscultatory systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean blood pressure (MBP) measurements. Patients were normotensive (70.0% for SBP versus 61.4% for DBP), hypertensive (17.1% vs. 13.6%) or hypotensive (12.9% vs. 25.0%). The diference in BP (mean± standard deviation) between both methods were within the ISO 81,060–2:2018 standard for SBP (− 0.7 ± 7.7 mmHg), DBP (− 0.4 ± 4.5 mmHg) and MBP (− 0.6 ± 5.2 mmHg). These results demonstrate that BP can be measured with accuracy at the fnger using the OptiBP smartphone app. This may become an important tool to detect hypertension in various settings, for example in low-income countries, where the availability of smartphones is high but access to health care is low.
Fig: OptiBP application utilizes image data generated from volumetric blood fow changes via light
passing through the fngertip, refecting of of the tissue, and then passing to the phone camera’s image sensor.
Acknowledgements: We thank Dr. Frederic Michard from MiCo (michardconsulting.com) for help in manuscript preparation. With funding of Innosuisse—Swiss Innovation Agency, Project no. 32688.1 IP-ICT.
