Contributions to Proceedings:

D. Pollreisz, N. TaheriNejad:
"Reliable Respiratory Rate Extraction using PPG";
in: "2020 IEEE 11th Latin American Symposium on Circuits & Systems (LASCAS)", issued by: IEEE; IEEE, San Jose, Costa Rica, 2020, ISBN: 978-1-7281-3427-7, 1 - 4.

English abstract:
Wearable electronics enable a new look into the health of individuals in a fashion that was never possible before. However, many reliable methods for measuring Respiratory Rate (RR) require wearing gadgets that are impractical in a normal daily life setup. On the other hand, more practical methods, which are less intrusive, are often less reliable. Extracting RR using Photoplethysmogram (PPG) signals is one of the methods in the latter group. A major challenge for this method is the movement artifact, which leads to wrong estimation of RR or failure in its calculation. In this work, we propose a new algorithm, Smart Fusion of Frequency Domain Peak (SFFDP), that outperforms existing algorithm by at least 37% improvement in terms of reliability; i.e., average error, Standard Deviation (STD), and Figure of Merit (FoM). This method does not require any signal other than PPG. Therefore, it can be used in a wide range of wearable devices, such as smart watches, without any hardware additions.

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.