Heartbeat detection from high-density EMG electrodes on the upper arm at different EMG intensity levels using Zephlet.
ECG
EMG
Heartbeat detection
Phase shift
SWT
Zephlet
Journal
Computer methods and programs in biomedicine
ISSN: 1872-7565
Titre abrégé: Comput Methods Programs Biomed
Pays: Ireland
ID NLM: 8506513
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
16
09
2022
revised:
11
09
2023
accepted:
22
09
2023
medline:
14
11
2023
pubmed:
21
10
2023
entrez:
20
10
2023
Statut:
ppublish
Résumé
A significant number of global deaths caused by cardiac arrhythmias can be prevented with accurate and immediate identification. Wearable devices can play a critical role in such identification by continuously monitoring cardiac activity using electrocardiogram (ECG). The existing body of research has focused on extracting cardiac information from the body surface by investigating various electrode locations and algorithm development for ECG interpretation. The present study was designed for heartbeat detection using the signals recorded from the upper arm. Firstly, optimal electrode locations on the upper arm were identified for Rest and elbow flexion (EF) conditions. Next, a synthesized ECG was generated using the selected electrodes with generalized weights over subjects and trials, and then zero-phase wavelet (Zephlet) was applied for feature extraction. Heartbeat detection was finally performed using the extracted detail coefficients incorporated with a multiagent detection scheme (MDS). The F1-score for heartbeat detection was 0.94 ± 0.16, 0.86 ± 0.22, 0.79 ± 0.26, and 0.67 ± 0.31 for Rest and EF with three different levels of muscle contraction (C These findings make several contributions to the current literature, summarized as precise and consistent electrode localization for various muscle contraction levels and accurate heartbeat detection method development for each of these conditions.
Sections du résumé
BACKGROUND AND OBJECTIVES
OBJECTIVE
A significant number of global deaths caused by cardiac arrhythmias can be prevented with accurate and immediate identification. Wearable devices can play a critical role in such identification by continuously monitoring cardiac activity using electrocardiogram (ECG). The existing body of research has focused on extracting cardiac information from the body surface by investigating various electrode locations and algorithm development for ECG interpretation. The present study was designed for heartbeat detection using the signals recorded from the upper arm.
METHODS
METHODS
Firstly, optimal electrode locations on the upper arm were identified for Rest and elbow flexion (EF) conditions. Next, a synthesized ECG was generated using the selected electrodes with generalized weights over subjects and trials, and then zero-phase wavelet (Zephlet) was applied for feature extraction. Heartbeat detection was finally performed using the extracted detail coefficients incorporated with a multiagent detection scheme (MDS).
RESULTS
RESULTS
The F1-score for heartbeat detection was 0.94 ± 0.16, 0.86 ± 0.22, 0.79 ± 0.26, and 0.67 ± 0.31 for Rest and EF with three different levels of muscle contraction (C
CONCLUSION
CONCLUSIONS
These findings make several contributions to the current literature, summarized as precise and consistent electrode localization for various muscle contraction levels and accurate heartbeat detection method development for each of these conditions.
Identifiants
pubmed: 37863012
pii: S0169-2607(23)00494-7
doi: 10.1016/j.cmpb.2023.107828
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
107828Informations de copyright
Copyright © 2023 Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.