14 April 2017 The assessment of sympathetic activity using iPPG based inter-limb coherence measurements
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Proceedings Volume 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III; 1033718 (2017) https://doi.org/10.1117/12.2267895
Event: Saratov Fall Meeting 2016: Fourth International Symposium on Optics and Biophotonics, 2016, Saratov, Russian Federation
Abstract
Photoplethysmography is an optical technique that can be used to detect blood volume changes and to measure important physiological parameters. This is low cost and non-invasive technique. However, one has to apply sensor directly to the skin. In this regard, the development on remote mothods receives the growing attention, such as imaging photoplethysmography (iPPG). Note, most of public-available iPPG systems are based on smartphone-embedded cameras, and thus have a sample frequency about 30-60 frames per second, which is enough for heart rate measurements, but may be too low for some more advanced usages of this technique. In our work, we describe the attempt to use smartphone-based iPPG technique aimed to measure the tiny mismatch in RR interval data series recorded from left and right arms. We use the transmission mode iPPG, in which the light transmitted through the medium of finger is detected by a web-camera opposite the LED source. The computational scheme by processing and analysis of the received signal was implemented using MATLAB language (MathWork Inc. in the United States). We believe that further development of our approach may lead to fast and low cost method to access the state of the sympathetic nervous system.
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Maria O. Tsoy, Maria O. Tsoy, Kristina V. Rogatina, Kristina V. Rogatina, Elena S. Stiukhina, Elena S. Stiukhina, Dmitry E. Postnov, Dmitry E. Postnov, } "The assessment of sympathetic activity using iPPG based inter-limb coherence measurements", Proc. SPIE 10337, Saratov Fall Meeting 2016: Laser Physics and Photonics XVII; and Computational Biophysics and Analysis of Biomedical Data III, 1033718 (14 April 2017); doi: 10.1117/12.2267895; https://doi.org/10.1117/12.2267895
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