Contributions to Proceedings:
D. Pollreisz, N. TaheriNejad:
"Efficient Respiratory Rate Extraction on Smartwatch";
in: "2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)",
Using the Photoplethysmogram (PPG) sensor of a smartwatch to extract Respiratory Rate (RR) is very attractive. However, existing algorithms suffer from lack of accuracy and susceptibility to noise and movement artifacts. To tackle this issue, we propose performing Frequency Domain Peak (FDP) analysis using the Frequency Modulation (FM) feature. Moreover, our analysis of existing methods show that in contrast to the common practice Smart Fusion (SFU), despite incurring extra computational costs, is very little helpful. It is hence more preferable and efficient to avoid SFU. The proposed method shows an improvement of at least 130% in the Figure of Merit (FoM) and has more than 60% smaller mean error. Therefore, it can be reliably used in a wide range of applications.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
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Created from the Publication Database of the Vienna University of Technology.