BP-Net: Cuff-less, Calibration-free, and Non-invasive Blood Pressure Estimation via a Generic Deep Convolutional Architecture. (arXiv:2112.15271v1 [cs.LG])

Objective: The paper focuses on development of robust and accurate processing
solutions for continuous and cuff-less blood pressure (BP) monitoring. In this
regard, a robust deep learning-based framework is proposed for computation of
low latency, continuous, and calibration-free upper and lower bounds on the
systolic and diastolic BP. Method: Referred to as the BP-Net, the proposed
framework is a novel convolutional architecture that provides longer effective
memory while achieving superior performance due to incorporation of casual
dialated convolutions and residual …

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