Diagnostic Performance of an Automated Blood Pressure Monitor With an Irregular Heartbeat Algorithm Designed to Detect Atrial Fibrillation.

Early detection of atrial fibrillation (AF) remains an unsolved challenge and because the greatest risk factor for AF is hypertension, blood pressure (BP) monitors with AF detectors have been developed. We evaluated the clinical performance of an irregular heartbeat (IHB) algorithm built into an A&D automated BP monitor for AF diagnosis. Each of the 239 enrolled patients underwent BP measurement 3 times using the A&D UM-212 with the IHB algorithm.

Image-based robot navigation with task achievability.

Image-based robot action planning is becoming an active area of research owing to recent advances in deep learning. To evaluate and execute robot actions, recently proposed approaches require the estimation of the optimal cost-minimizing path, such as the shortest distance or time, between two states. To estimate the cost, parametric models consisting of deep neural networks are widely used.