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> ECG-based monitoring of blood potassium concentration: Periodic versus principal component as lead transformation for biomarker robustness
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ECG-based monitoring of blood potassium concentration: Periodic versus principal component as lead transformation for biomarker robustness
Palmieri, Flavio
;
Gomis, Pedro
;
Ruiz, José Esteban
;
Ferreira, Dina
;
Martín-Yebra, Alba
;
Pueyo, Esther
(Universidad de Zaragoza)
;
Martínez, Juan Pablo
(Universidad de Zaragoza)
;
Ramírez, Julia
;
Laguna, Pablo
(Universidad de Zaragoza)
Resumen:
Objective: The aim of this study is to compare the performance of two electrocardiogram (ECG) lead-space reduction (LSR) techniques in generating a transformed ECG lead from which T-wave morphology markers can be reliably derived to non-invasively monitor blood potassium concentration ([K+]) in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD). These LSR techniques are: (1) principal component analysis (PCA), learned on the T wave, and (2) periodic component analysis (πCA), either learned on the whole QRST complex (πCB) or on the T wave (πCT). We hypothesized πCA is less sensitive to non-periodic disturbances, like noise and body position changes (BPC), than PCA, thus leading to more reliable T wave morphology markers. Methods: We compared the ability of T wave morphology markers obtained from PCA, πCB and πCT in tracking [K+] in an ESRD-HD dataset, including 29 patients, during and after HD (evaluated by correlation and residual fitting error analysis). We also studied their robustness to BPC using an annotated database, including 20 healthy individuals, as well as to different levels of noise using a simulation set-up (assessed by means of Mann–Whitney U test and relative error, respectively). Results: The performance of both πCB and πCT-based markers in following [K+]-variations during HD was comparable, and superior to that from PCA-based markers. Moreover, πCT-based markers showed superior robustness against BPC and noise. Conclusion: Both πCB and πCT outperform PCA in terms of monitoring [K+] in ESRD-HD patients, as well as of robustness against BPC and low SNR, with πCT showing the highest stability for continuous post-HD monitoring. Significance: The usage of πCA (i) increases the accuracy in monitoring dynamic [K+] variations in ESRD-HD patients and (ii) reduces the sensitivity to BPC and noise in deriving T wave morphology markers. © 2021 The Author(s)
Idioma:
Inglés
DOI:
10.1016/j.bspc.2021.102719
Año:
2021
Publicado en:
Biomedical Signal Processing and Control
68 (2021), 102719 [11 pp.]
ISSN:
1746-8094
Factor impacto JCR:
5.076 (2021)
Categ. JCR:
ENGINEERING, BIOMEDICAL
rank: 30 / 98 = 0.306
(2021)
- Q2
- T1
Factor impacto CITESCORE:
6.9 -
Engineering
(Q1) -
Medicine
(Q1) -
Computer Science
(Q1)
Factor impacto SCIMAGO:
1.211 -
Signal Processing
(Q1) -
Health Informatics
(Q1)
Financiación:
info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS group
Financiación:
info:eu-repo/grantAgreement/EUR/ERC-2014-StG-638284
Financiación:
info:eu-repo/grantAgreement/ES/MICINN-FEDER/PID2019-105674RB-I00
Financiación:
info:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00
Tipo y forma:
Article (Published version)
Área (Departamento):
Área Teoría Señal y Comunicac.
(
Dpto. Ingeniería Electrón.Com.
)
You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
Exportado de SIDERAL (2024-02-09-14:45:41)
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Record created 2022-01-19, last modified 2024-02-09
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