Internet of things-assisted architecture for QRS complex detection in real time
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21220%2F21%3A00352784" target="_blank" >RIV/68407700:21220/21:00352784 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1016/j.iot.2021.100395" target="_blank" >https://doi.org/10.1016/j.iot.2021.100395</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>
Alternativní jazyky
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.
Klasifikace
Druh
J<sub>ost</sub> - Ostatní články v recenzovaných periodicích
CEP obor
—
OECD FORD obor
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Návaznosti výsledku
Projekt
—
Návaznosti
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Internet of Things
ISSN
2542-6605
e-ISSN
2542-6605
Svazek periodika
14
Číslo periodika v rámci svazku
March
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
15
Strana od-do
—
Kód UT WoS článku
000695695900048
EID výsledku v databázi Scopus
2-s2.0-85114805424