Internet of things-assisted architecture for QRS complex detection in real time

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F21%3A43896294" target="_blank" >RIV/44555601:13440/21:43896294 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S2542660521000391" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2542660521000391</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.iot.2021.100395" target="_blank" >10.1016/j.iot.2021.100395</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Internet of things-assisted architecture for QRS complex detection in real time

Popis výsledku v původním jazyce

This paper presents the development of an Internet of Things-assisted architecture for QRS complex detection in an electrocardiogram regardless of the age and physiological characteristics of the patient. Detection of the QRS complex is affected by the abnormalities and quality in electrocardiogram recordings; the proposed method can detect QRS complex despite these challenges. Electrocardiogram continuous signal acquisition is performed with the BITalino biomedical data acquisition card. Electrocardiogram signals typically suffer from (a) premature atrial complexes, (b) premature ventricular complexes, (c) low signal-to-noise ratio, (d) right bundle branch blocks, (e) left bundle branch blocks, and (f) non-stationary effects. Interestingly, the signal processing is implemented by means of a bandpass filter, followed by a numerical derivative. Next, the Hilbert transform and the adaptive threshold technique are implemented to detect the QRS complex. Tests are performed to evaluate the Internet of Things-assisted architecture using the obtained signal in real time. Results, and the simplicity of the architecture, demonstrate that it is suitable for wearable, portable, and battery-operated electrocardiogram acquisition card.

Název v anglickém jazyce

Internet of things-assisted architecture for QRS complex detection in real time

Popis výsledku anglicky

This paper presents the development of an Internet of Things-assisted architecture for QRS complex detection in an electrocardiogram regardless of the age and physiological characteristics of the patient. Detection of the QRS complex is affected by the abnormalities and quality in electrocardiogram recordings; the proposed method can detect QRS complex despite these challenges. Electrocardiogram continuous signal acquisition is performed with the BITalino biomedical data acquisition card. Electrocardiogram signals typically suffer from (a) premature atrial complexes, (b) premature ventricular complexes, (c) low signal-to-noise ratio, (d) right bundle branch blocks, (e) left bundle branch blocks, and (f) non-stationary effects. Interestingly, the signal processing is implemented by means of a bandpass filter, followed by a numerical derivative. Next, the Hilbert transform and the adaptive threshold technique are implemented to detect the QRS complex. Tests are performed to evaluate the Internet of Things-assisted architecture using the obtained signal in real time. Results, and the simplicity of the architecture, demonstrate that it is suitable for wearable, portable, and battery-operated electrocardiogram acquisition card.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Internet of Things Journal

ISSN

2543-1536

e-ISSN

2542-6605

Svazek periodika

2021

Číslo periodika v rámci svazku

14

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

15

Strana od-do

1-15

Kód UT WoS článku

000695695900048

EID výsledku v databázi Scopus

2-s2.0-85114805424