Application of the Artificial Neural Network for blood pressure evaluation with smartphones
|Title||Application of the Artificial Neural Network for blood pressure evaluation with smartphones|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Lamonaca, F, Barbe, K, Kurylyak, Y, Grimaldi, D, Van Moer, W, Furfaro, A, Spagnuolo, V|
|Conference Name||7th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013|
|Keywords||ABP Spacelabs 90207, ambulatory blood pressure monitor, artificial neural network, Artificial neural networks, Biomedical monitoring, Blood pressure, blood pressure evaluation, blood pressure measurement, Cameras, diastolic BP, feature extraction, fit forward neural network, frame sequence fingertip, integrated camera, medical signal processing, mobile computing, Monitoring, neural nets, photoplethysmogram, photoplethysmography, PPG signal extraction, smart phones, smartphone, smartphones, systolic BP, Training, volumetric blood variation|
The smartphone is proposed to evaluate the Blood Pressure (BP) anywhere and anytime. The tasks performed by smartphone are (i) extraction of the PhotoPlethysmoGram (PPG) signal from a frame sequence acquired by the integrated camera, and (ii) processing it by Artificial Neural Network for the evaluation of the BP. The PPG signal is evaluated by analyzing the volumetric blood variation of the fingertip on the frame sequence. Successively, parameters characterizing the pulses of the PPG signal are sent to the Fit Forward Neural Network for the simultaneously evaluation of the systolic and the diastolic BP. The validation of the results is performed by comparing them with the ones obtained by the Ambulatory Blood Pressure monitor ABP Spacelabs 90207. Preliminary experimental results show useful information to address the future research devoted to reduce the maximum error.