Biosignal time-series analysis

Serkan Kiranyaz, Turker Ince, Muhammad E.H. Chowdhury, Aysen Degerli, Moncef Gabbouj

Research output: Chapter in Book/Report/Conference proceedingChapter or book articleScientificpeer-review

Abstract

In this chapter, recent state-of-the-art techniques in biosignal time-series analysis will be presented. We shall start with the problem of patient-specific ECG beat classification where the objective is to discriminate the arrhythmic beats from the normal (healthy) beats of an individual patient. So, we will answer the ultimate question of how to design person-specific, real-time, and accurate monitoring of ECG signals. We shall then move on to the recent solution of a related problem, an early warning system that can alert an individual the instant his/her heart deviates from its normal rhythm. This is a far challenging problem since the detection of the arrhythmia beats should be performed without knowing them.

Original languageEnglish
Title of host publicationDeep Learning for Robot Perception and Cognition
EditorsAlexandros Iosifidis, Anastasios Tefas
PublisherAcademic Press
Pages491-539
Number of pages49
ISBN (Electronic)9780323857871
ISBN (Print)9780323885720
DOIs
Publication statusPublished - 1 Jan 2022
MoE publication typeA3 Part of a book or another research book

Keywords

  • Deep learning
  • Arrhythmia detection
  • Myocardial infarction
  • COVID-19
  • Mortality risk prediction

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