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.

Application of the Artificial Neural Network for Blood Pressure Evaluation with Smartphones

Lamonaca F;A. Furfaro;
2013

Abstract

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.
9781479914265
Measurement
blood pressure evaluation
smartphone
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/314489
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