Research Article
On Evaluating Blood Pressure Through Photoplethysmography
@INPROCEEDINGS{10.1007/978-3-319-47063-4_57, author={Giovanna Sannino and Ivanoe De Falco and Giuseppe De Pietro}, title={On Evaluating Blood Pressure Through Photoplethysmography}, proceedings={Internet of Things. IoT Infrastructures. Second International Summit, IoT 360° 2015, Rome, Italy, October 27-29, 2015. Revised Selected Papers, Part I}, proceedings_a={IOT360}, year={2017}, month={1}, keywords={Blood pressure Wearable sensors Photoplethysmography Regression Genetic programming}, doi={10.1007/978-3-319-47063-4_57} }- Giovanna Sannino
Ivanoe De Falco
Giuseppe De Pietro
Year: 2017
On Evaluating Blood Pressure Through Photoplethysmography
IOT360
Springer
DOI: 10.1007/978-3-319-47063-4_57
Abstract
This paper investigates the hypothesis that a nonlinear relationship exists between photoplethysmography (PPG) and blood pressure (BP) values. Trueness of this hypothesis would imply that, instead of measuring a patient’s BP in an invasive way, this could be indirectly measured by applying a wearable PPG sensor and by using the results of a regression analysis linking PPG and BP. Genetic Programming (GP) is well suited to find the relationship between PPG and BP, because it automatically evolves the structure of the most suitable explicit mathematical model for a regression task. In this paper, for the first time, some preliminary experiments on the use of GP to explicitly relate PPG and BP values have been performed. For both systolic and diastolic BP values, explicit nonlinear mathematical models have been achieved, involving an approximation error of less than 3 mmHg in both cases.
