![]() ![]() There are no further patents, products in development or marketed products to declare. One of the co-authors (Peter Rolfe) currently serves as Director of Science and Technology of Oxford BioHorizons Ltd., a consultancy company, and as a grant review committee member of the European Commission. iPhysioMeter app, distributed for free at iTunes App Store (Apple, Inc.), used in this study, was developed by two of the authors of the present paper (Kenta Matsumura and Takehiro Yamakoshi). ![]() No additional external funding was received for this study.Ĭompeting interests: We have the following interests. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: The study was partially supported by the Ministry of Education, Culture, Sports, Science and Technology, Japan via Grant-in-Aid for Young Scientists (A) No. Received: JAccepted: JanuPublished: March 11, 2014Ĭopyright: © 2014 Matsumura et al. We conclude that the use of green light PPG could be of particular benefit in ambulatory monitoring where motion artifacts are a significant issue.Ĭitation: Matsumura K, Rolfe P, Lee J, Yamakoshi T (2014) iPhone 4s Photoplethysmography: Which Light Color Yields the Most Accurate Heart Rate and Normalized Pulse Volume Using the iPhysioMeter Application in the Presence of Motion Artifact? PLoS ONE 9(3):Įditor: Derek Abbott, University of Adelaide, Australia These findings suggest that green is the most suitable color for measuring HR and NPV from the reflection mode photoplethysmogram under motion artifact conditions. Moreover, the signal-to-noise ratio obtained with green and blue light PPG was higher than that of red light PPG. The analyses revealed that the accuracy of HR was acceptably high with all three wavelengths (all rs > 0.996, fixed biases: −0.12 to 0.10 beats per minute, proportional biases: r = −0.29 to 0.03), but that of NPV was the best with green light ( r = 0.791, fixed biases: −0.01 arbitrary units, proportional bias: r = 0.11). We then assessed the accuracy of the HR and NPV measurements under the influence of motion artifacts. To test this hypothesis, we made measurements in 12 healthy volunteers of HR and NPV derived from reflection mode plethysmograms recorded simultaneously at three different spectral regions (red, green and blue) at the same physical location with a smartphone. ![]() Further, it is known that the wavelength of light used for PPG influences the photon penetration depth and we therefore hypothesized that influences of motion artifact could be wavelength-dependant. Despite its widespread use, the method of PPG is susceptible to motion artifacts as physical displacements influence photon propagation phenomena and, thereby, the effective optical path length. This has been achieved with reflection mode photoplethysmography (PPG), by using a smartphone’s embedded flash as a light source and the camera as a light sensor. Recent progress in information and communication technologies has made it possible to measure heart rate (HR) and normalized pulse volume (NPV), which are important physiological indices, using only a smartphone. ![]()
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