Seo, Youjung Kwon, Saehim Sunarya, Unang Park, Sungmin Park, Kwangsuk Jung, Dawoon Cho, Youngho Park, Cheolsoo 2024-01-19T09:33:16Z 2024-01-19T09:33:16Z 2023-04-20 2023-05 2093-9868 https://pubs.kist.re.kr/handle/201004/113768 The rapid evolution of wearable technology in healthcare sectors has created the opportunity for people to measure their blood pressure (BP) using a smartwatch at any time during their daily activities. Several commercially-available wearable devices have recently been equipped with a BP monitoring feature. However, concerns about recalibration remain. Pulse transit time (PTT)-based estimation is required for initial calibration, followed by periodic recalibration. Recalibration using arm-cuff BP monitors is not practical during everyday activities. In this study, we investigated recalibration using PTT-based BP monitoring aided by a deep neural network (DNN) and validated the performance achieved with more practical wrist-cuff BP monitors. The PTT-based prediction produced a mean absolute error (MAE) of 4.746 +/- 1.529 mmHg for systolic blood pressure (SBP) and 3.448 +/- 0.608 mmHg for diastolic blood pressure (DBP) when tested with an arm-cuff monitor employing recalibration. Recalibration clearly improved the performance of both DNN and conventional linear regression approaches. We established that the periodic recalibration performed by a wrist-worn BP monitor could be as accurate as that obtained with an arm-worn monitor, confirming the suitability of wrist-worn devices for everyday use. This is the first study to establish the potential of wrist-cuff BP monitors as a means to calibrate BP monitoring devices that can reliably substitute for arm-cuff BP monitors. With the use of wrist-cuff BP monitoring devices, continuous BP estimation, as well as frequent calibrations to ensure accurate BP monitoring, are now feasible. English 대한의용생체공학회 Blood pressure estimation and its recalibration assessment using wrist cuff blood pressure monitor Article 10.1007/s13534-023-00271-1 1 Biomedical Engineering Letters (BMEL), v.13, pp.221 - 233 Biomedical Engineering Letters (BMEL) 13 221 233 N scie scopus kci 000957517700001 2-s2.0-85150744419 Engineering, Biomedical Engineering Article; Early Access PULSE TRANSIT-TIME INTERNATIONAL PROTOCOL VALIDATION HEALTH MODEL LESS HOME Photoplethysmogram MAE DNN Signal processing Blood pressure Recalibration Attention mechanism Electrocardiogram