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

Elevated blood pressure is a key risk factor in cardiovascular diseases. However, obtaining reliable and reproducible blood pressure remains a challenge. This study, therefore, aimed to evaluate a novel cuffless wristband, based on photoplethysmography, for continuous blood pressure monitoring. Predictions by a photoplethysmography-guided algorithm were compared to arterial blood pressure measurements (in the subclavian artery), obtained during cardiac catheterisation. Eligible patients were included and screened based on AAMI/ESH/ISO Universal Standard requirements. The machine learning-based blood pressure algorithm required three cuff-based initialisation measurements in combination with approximately 100 features (signal-derived and patient demographic-based). 97 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 blood pressure was ≤100 mmHg in 48 samples (11%) and ≥160 mmHg in 106 samples (25%). Diastolic blood pressure 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 blood pressure, respectively. Similar results were observed across all genders and skin colours (Fitzpatrick I-VI). This study provides initial evidence for the accuracy of a photoplethysmography-based blood pressure algorithm in combination with a cuffless wristband across a range of blood pressure 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. Trial registration: www.clinicaltrials.gov, NCT05566886.