On-Device, Continuous, Cuffless, and Accelerometer-Based Blood Pressure Monitoring

Cuffless blood pressure monitoring enables noninvasive, practical, and continuous cardiovascular disease management. This paper introduces an intelligent inertial blood pressure measurement device based on pulse transit time and ballistocardiography. Time-synchronized data from two accelerometers placed on the common carotid artery are fed to a lightweight on-device neural network for systolic and diastolic estimation. Platform-aware neural architecture search pre-trains the most accurate model that fits within the device from a multi-person dataset. Transfer learning personalizes the model using only 30 seconds of cuff calibration. The model achieves < ±2 mmHg systolic and diastolic error in preclinical trials on 18 patients, consumes <100 kB of memory, and provides 3 readings every second. The device is wireless, non-invasive, personalizable, and cuffless, communicating with patients using a smartphone interface. The framework enables continuous blood pressure monitoring in non-clinical settings by non-experts.