Biosignal Time-Series Analysis
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Date
2022
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Open Access Color
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
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. © 2022 Elsevier Inc. All rights reserved.
Description
Keywords
Arrhythmia detection, COVID-19, Deep learning, Mortality risk prediction, Myocardial infarction, Myocardial infarction, Arrhythmia detection, COVID-19, Deep learning, Mortality risk prediction
Fields of Science
Citation
WoS Q
N/A
Scopus Q
N/A

OpenCitations Citation Count
2
Source
Deep Learning for Robot Perception and Cognition
Volume
Issue
Start Page
491
End Page
539
PlumX Metrics
Citations
CrossRef : 2
Scopus : 4
Captures
Mendeley Readers : 7
SCOPUS™ Citations
4
checked on Mar 22, 2026
Page Views
2
checked on Mar 22, 2026
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