@inproceedings{4cd15ef2b7e5435bbe1df9adb478b6f9,
title = "Respiratory phase detection from optical phonocardiography characteristics",
abstract = "This paper presents a respiratory phase prediction technique from an optical phonocardiograph (PCG) signal. The PCG acquisition was conducted using a speckle-based sensor which includes illumination of the inspected subjects by a laser beam and analyzing the temporal changes in the spatial distribution of the back scattered secondary speckle patterns. From the analysis of the 2D speckle patterns a 1D nano vibrations signal was extracted. Then, we performed an analysis of this 1D signal while relying on the PCG extracted features used in Na{\"i}ve Bayes model. The performance accuracy for the respiratory phase prediction conducted over four subjects was 83\%. The high accuracy made possible thanks to 9 spatial illumination spots used in our optical sensor and using a decision algorithm involving spots' combination (while each one of the 9 spots illuminating the chest of the inspected subjects was analyzed separately).",
keywords = "PPG, Photonic sensing, Respiratory phase, Speckle patterns",
author = "Yitzhak, \{Hadas Lupa\} and Oliver, \{Ricardo Rubio\} and Monreal, \{Javier Garcia\} and Zeev Zalevsky",
note = "Publisher Copyright: {\textcopyright} 2021 SPIE; Diagnostic and Therapeutic Applications of Light in Cardiology 2021 ; Conference date: 06-03-2021 Through 11-03-2021",
year = "2021",
doi = "10.1117/12.2577146",
language = "الإنجليزيّة",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Laura Marcu and \{van Soest\}, Gijs",
booktitle = "Diagnostic and Therapeutic Applications of Light in Cardiology 2021",
address = "الولايات المتّحدة",
}