On the Design of a Physiological Signal Feature Extraction and Segmentation Digital Subsystem

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

Abstract

Real-time and compact algorithms are desired for wearable physiologic monitoring devices. We present a QRS waveform detection algorithm, inspired by the Stockwell time-frequency transform and targeted to embedded architectures. The proposed QRS detector uses a complex filter for feature extraction and efficient estimations to achieve minimal computations and limited digital hardware resources. The QRS detector algorithm is demonstrated to reduce the computational cost and maintain accuracy.

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
Pages208-212
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

  • Electrocardiogram
  • Photoplethysmography
  • QRS
  • Wearable

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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