Work

Optical blood pressure estimation with photoplethysmography and FFT-based neural networks

Year: 2016

Type: article

Abstract: We introduce and validate a beat-to-beat optical blood pressure (BP) estimation paradigm using only photoplethysmogram (PPG) signal from finger tips. The scheme determines subject-specific contribution to PPG signal and removes most of its influence by proper normalization. Key features such as amplitudes and phases of cardiac components were extracted by a fast Fourier transform and were used to train an artificial neural network, which was then used to estimate BP from PPG. Validation was done on 69 patients from the MIMIC II database plus 23 volunteers. All estimations showed a good correlation with the reference values. This method is fast and robust, and can potentially be used to perform pulse wave analysis in addition to BP estimation.

Source: Biomedical Optics Express

DOI: 10.1364/boe.7.003007

Authors: Xiaoman Xing, Mingshan Sun

Institutions: Chinese Academy of Sciences, Suzhou Institute of Biomedical Engineering and Technology

Language: English

Topic: Non-Invasive Vital Sign Monitoring

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,913