Stockwell Transform Detector for Photoplethysmography Signal Segmentation

Victoria S. Marks, Christopher L. Felton, Robert W. Techentin, Barry K. Gilbert, Victor A. Convertino, Michael J. Joyner, Timothy B. Curry, David R. Holmes, Clifton R. Haider

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Real-time embedded analysis of physiologic waveforms is critical to predict impending pathophysiology. While electrocardiogram (ECG) data is often analyzed to assess cardiovascular disease, there is recent evidence that photoplethysmography (PPG) can track blood loss and thereby alert to hypovolemia. In this work we present a Stockwell transform inspired filter bank to segment PPG waveforms. The Stockwell transform allows for computationally efficient frequency analysis. The proposed Stockwell filter bank utilizes a sparse time-frequency spectrum and is coupled to the Shannon energy envelope to extract PPG peaks. Finally, we demonstrate that the described method is tolerant to the presence of additive Gaussian noise.

Original languageEnglish (US)
Title of host publicationConference Record of the 52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
EditorsMichael B. Matthews
PublisherIEEE Computer Society
Pages1239-1243
Number of pages5
ISBN (Electronic)9781538692189
DOIs
StatePublished - Feb 19 2019
Event52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018 - Pacific Grove, United States
Duration: Oct 28 2018Oct 31 2018

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2018-October
ISSN (Print)1058-6393

Conference

Conference52nd Asilomar Conference on Signals, Systems and Computers, ACSSC 2018
CountryUnited States
CityPacific Grove
Period10/28/1810/31/18

Keywords

  • Photoplethysmography
  • Stockwell transform
  • Wearable devices

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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