Development and Internal Validation of an AI-Enabled Cuff-less, Non-invasive Continuous Blood Pressure Monitor Across All Classes of Hypertension
Francisco López-Jiménez, Abhishek Deshmukh, John D. Bisognano, John Boehmer, Mouli Ramasamy, Prashanth S. Kumar, Suraj Kapa, Venk Varadan, Vijay K. Varadan, Marat Fudim
Abstract
BACKGROUND: Non-invasive, continuous blood pressure monitoring technologies require additional validation beyond standard cuff-based methods. This study evaluates a non-invasive, multiparametric wearable cuffless blood pressure (BP) diagnostic monitor across all hypertension classes with diverse subjects. METHODS: A prospective, multicenter study assessed Nanowear's SimpleSense-BP performance, including induced and natural BP changes, significant BP variations (Systolic BP (SBP) ≥ ± 15 mm Hg and Diastolic BP (DBP) ≥ ± 10 mm Hg), and reference input value validity over 4 weeks. RESULTS: 303 subjects (18-83 yrs; 50.16% Female) participated in algorithmic development and validation (Normal - 35%, Prehypertensive - 24%, Stage 1 - 24%, Stage 2 - 17%). 54 subjects were tested for induced change performance, 149 exhibited significant changes, and 91 validated reference value duration. CONCLUSIONS: The study clinically validated a continuous, AI-based BP diagnostic monitor using non-invasive wearable data. Further testing on diverse populations and external validation are recommended. The protocol was inspired by ISO 81060-2 and IEEE 1708:2019 standards.