Evaluation of a novel cuffless photoplethysmography-based wristband for measuring blood pressure according to the regulatory standards.

Abstract

Elevated blood pressure (BP) is a key risk factor in cardiovascular diseases. However, obtaining reliable and reproducible BP remains a challenge. This study, therefore, aimed to evaluate a novel cuffless wristband, based on photoplethysmography (PPG), for continuous BP monitoring. Predictions by a PPG-guided algorithm were compared to arterial BP measurements (in the sub-clavian artery), obtained during cardiac catheterization. Eligible patients were included and screened based on AAMI/European Society of Hypertension (ESH)/ISO Universal Standard requirements. The machine learning-based BP algorithm required three cuff-based initialization measurements in combination with ∼100 features (signal-derived and patient demographic-based). Ninety-seven patients and 420 samples were included. Mean age, weight, and height were 67.1 years (SD 11.1), 83.4 kg (SD 16.1), and 174 cm (SD 10), respectively. Systolic BP was ≤100 mmHg in 48 samples (11%) and ≥160 mmHg in 106 samples (25%). Diastolic BP was ≤70 mmHg in 222 samples (53%) and ≥85 mmHg in 99 samples (24%). The algorithm showed mean errors of ±3.7 mmHg (SD 4.4 mmHg) and ±2.5 mmHg (SD 3.7 mmHg) for systolic and diastolic BP, respectively. Similar results were observed across all genders and skin colours (Fitzpatrick I-VI). This study provides initial evidence for the accuracy of a PPG-based BP algorithm in combination with a cuffless wristband across a range of BP distributions. This research complies with the AAMI/ESH/ISO Universal Standard, however, further research is required to evaluate the algorithms performance in light of the remaining European Society of Hypertension recommendations. www.clinicaltrials.gov, NCT05566886.