Efficient Respiratory Rate Extraction on a Smartwatch

Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul:2020:5988-5991. doi: 10.1109/EMBC44109.2020.9175470.

Abstract

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.

MeSH terms

  • Algorithms
  • Artifacts
  • Movement
  • Photoplethysmography*
  • Respiratory Rate*