Blood Pressure Monitoring using a Smartphone Camera: Performance of the OBPM Technology

Josep Sola1, Martin Proença, Patrick Schoettker2, Alia Lemkaddem3, Fabian Braun4, Christophe Verjus3, Mattia Bertschi, Eliott Jones, Thierry Kunz

  • 1CSEM - Centre Suisse d'Electronique et Microtechnique
  • 2CHUV – Centre Hospitalier Universitaire Vaudois
  • 3CSEM
  • 4CSEM SA

Details

18:15 - 20:15 | Mon 5 Mar | Caribbean ABC | MoPO.45

Session: Poster Session # 1 and BSN Innovative Health Technology Demonstrations

Abstract

While hypertension globally affects two out of five adults worldwide, there exists no easily-scalable technology to measure blood pressure out of the clinics. The idea of using smartphone sensors to estimate blood pressure was already tackled in the past, but failed because of low accuracy. Based on data from a previous study (NCT02651558), we recently developed a library of algorithms that predicts blood pressure from optical signals: the Optical Blood Pressure Monitoring (OBPM) technology. In the current work, we studied the performances of this technology when applied to video sequences acquired by a commercial smartphone camera. We implemented a measurement campaign on 35 healthy volunteers that performed physical exercises. The volunteers were requested to apply their right forefinger on top of the camera of a commercial smartphone while video sequences were acquired. The video sequences were then processed by the OBPM algorithms, and the predicted blood pressure values were compared to reference oscillometric blood pressure readings. After a calibration procedure, the predicted diastolic blood pressure values showed to comply with the ISO81060-2 performance requirements with a mean error of 0.32 mmHg, and a standard deviation of the error of 7.02 mmHg. This study provides first experimental evidence to support that a commercial smartphone can be transformed into