A Continuous Non-invasive Arterial Pressure (CNAP) approach for Health 4.0 systems

Health 4.0 can provide effective ways to improve the health status of subjects by taking advantage of Cyber-Physical Systems and Internet of Things technologies for the solution of health care problems. One of these is represented by suitably estimating blood pressure values of subjects in a continuous, real-time and non-invasive way. To address it, we propose an approach only requiring a photoplethysmography sensor and a mobile/desktop device. The approach avails itself of Genetic Programming to automatically find an explicit relationship between blood pressure values and photoplethysmography ones. This relationship is tested on a set of eleven subjects and compared against other regression methods, and turns out to be better. Namely, the Root Mean Square Error values are equal to 8.49 and 6.66 for the systolic and the diastolic BP values, respectively. Those for the relative error, instead, are equal to 5.55% for the systolic and 6.59% for the diastolic values.