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      Source–Detector Spectral Pairing-Related Inaccuracies in Pulse Oximetry: Evaluation of the Wavelength Shift

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          Abstract

          Pulse oximetry enables oxygen saturation estimation ( S p O 2 ) non-invasively in real time with few components and modest processing power. With the advent of affordable development kits dedicated to the monitoring of biosignals, capabilities once reserved to hospitals and high-end research laboratories are becoming accessible for rapid prototyping. While one may think that medical-grade equipment differs greatly in quality, surprisingly, we found that the performance requirements are not widely different from available consumer-grade components, especially regarding the photodetection module in pulse oximetry. This study investigates how the use of candidate light sources and photodetectors for the development of a custom S p O 2 monitoring system can lead to inaccuracies when using the standard computational model for oxygen saturation without calibration. Following the optical characterization of selected light sources, we compare the extracted parameters to the key features in their respective datasheet. We then quantify the wavelength shift caused by spectral pairing of light sources in association with photodetectors. Finally, using the widely used approximation, we report the resulting absolute error in S p O 2 estimation and show that it can lead up to 8% of the critical 90–100% saturation window.

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          Advances in Photopletysmography Signal Analysis for Biomedical Applications

          Heart Rate Variability (HRV) is an important tool for the analysis of a patient’s physiological conditions, as well a method aiding the diagnosis of cardiopathies. Photoplethysmography (PPG) is an optical technique applied in the monitoring of the HRV and its adoption has been growing significantly, compared to the most commonly used method in medicine, Electrocardiography (ECG). In this survey, definitions of these technique are presented, the different types of sensors used are explained, and the methods for the study and analysis of the PPG signal (linear and nonlinear methods) are described. Moreover, the progress, and the clinical and practical applicability of the PPG technique in the diagnosis of cardiovascular diseases are evaluated. In addition, the latest technologies utilized in the development of new tools for medical diagnosis are presented, such as Internet of Things, Internet of Health Things, genetic algorithms, artificial intelligence and biosensors which result in personalized advances in e-health and health care. After the study of these technologies, it can be noted that PPG associated with them is an important tool for the diagnosis of some diseases, due to its simplicity, its cost–benefit ratio, the easiness of signals acquisition, and especially because it is a non-invasive technique.
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            The Analysis of PPG Morphology: Investigating the Effects of Aging on Arterial Compliance

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              Neurovascular coupling and epilepsy: hemodynamic markers for localizing and predicting seizure onset.

              Hemodynamic surrogates of epileptic activity are being used to map epileptic foci with PET, SPECT, and fMRI. However, there are few studies of neurovascular coupling in epilepsy. Recent data indicate that cerebral blood flow, although focally increased at the onset of a seizure, may be temporarily inadequate to meet the metabolic demands of both interictal and ictal epileptic events. Transient focal tissue hypoxia and hyperperfusion may be excellent markers for the epileptic focus and may even precede the onset of the ictal event.
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                Author and article information

                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                10 June 2020
                June 2020
                : 20
                : 11
                : 3302
                Affiliations
                [1 ]Department of Computer and Electrical Engineering, Université Laval, 1065 Avenue de la Médecine, Quebec, QC G1V 0A6, Canada; benoit.gosselin@ 123456gel.ulaval.ca
                [2 ]CERVO Research Center, Quebec, QC G1J 2G3, Canada
                [3 ]Sorbonne Université, CNRS, LIP6, F-75005 Paris, France
                Author notes
                [†]

                These authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0003-1354-961X
                https://orcid.org/0000-0003-1473-3451
                https://orcid.org/0000-0002-6444-2671
                Article
                sensors-20-03302
                10.3390/s20113302
                7309008
                32532116
                c6d99f81-0aa1-401e-80af-f263dd378bec
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 05 May 2020
                : 05 June 2020
                Categories
                Article

                Biomedical engineering
                pulse oximetry,wearable sensors,spectrum distribution,wavelength shift,sensor shift,calibration,beer–lambert law,led

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