Detail publikace

Real-Time Quality Assessment of Long-Term ECG Signals Recorded by Wearables in Free-Living Conditions

SMITAL, L. HAIDER, C. VÍTEK, M. LEINVEBER, P. JURÁK, P. NĚMCOVÁ, A. SMÍŠEK, R. MARŠÁNOVÁ, L. PROVAZNÍK, I. FELTON, C. GILBERT, B. HOLMES, D.

Originální název

Real-Time Quality Assessment of Long-Term ECG Signals Recorded by Wearables in Free-Living Conditions

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

Objective: Nowadays, methods for ECG quality assessment are mostly designed to binary distinguish between good/bad quality of the whole signal. Such classification is not suitable to long-term data collected by wearable devices. In this paper, a novel approach to estimate long-term ECG signal quality is proposed. Methods: The real-time quality estimation is performed in a local time window by calculation of continuous signal-to-noise ratio (SNR) curve. The layout of the data quality segments is determined by analysis of SNR waveform. It is distinguished between three levels of ECG signal quality: signal suitable for full wave ECG analysis, signal suitable only for QRS detection, and signal unsuitable for further processing. Results: The SNR limits for reliable QRS detection and full ECG waveform analysis are 5 and 18 dB respectively. The method was developed and tested using synthetic data and validated on real data from wearable device. Conclusion: The proposed solution is a robust, accurate and computationally efficient algorithm for annotation of ECG signal quality that will facilitate the subsequent tailored analysis of ECG signals recorded in free-living conditions. Significance: The field of long-term ECG signals self-monitoring by wearable devices is swiftly developing. The analysis of massive amount of collected data is time consuming. It is advantageous to characterize data quality in advance and thereby limit consequent analysis to useable signals.

Klíčová slova

Electrocardiography; Signal to noise ratio; Estimation; Biomedical monitoring; Performance evaluation; Real-time systems; ECG delineation; ECG signal; QRS detection; signal quality; signal segmentation; SNR estimation

Autoři

SMITAL, L.; HAIDER, C.; VÍTEK, M.; LEINVEBER, P.; JURÁK, P.; NĚMCOVÁ, A.; SMÍŠEK, R.; MARŠÁNOVÁ, L.; PROVAZNÍK, I.; FELTON, C.; GILBERT, B.; HOLMES, D.

Vydáno

27. 1. 2020

Nakladatel

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

Místo

PISCATAWAY

ISSN

1558-2531

Periodikum

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING

Ročník

67

Číslo

10

Stát

Spojené státy americké

Strany od

2721

Strany do

2734

Strany počet

14

URL

https://ieeexplore.ieee.org/document/8970507

BibTex

@article{BUT165449,
  author="Lukáš {Smital} and Clifton {Haider} and Martin {Vítek} and Pavel {Leinveber} and Pavel {Jurák} and Andrea {Němcová} and Radovan {Smíšek} and Lucie {Šaclová} and Valentine {Provazník} and Christopher L. {Felton} and Barry {Gilbert} and David {Holmes}",
  title="Real-Time Quality Assessment of Long-Term ECG Signals Recorded by Wearables in Free-Living Conditions",
  journal="IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING",
  year="2020",
  volume="67",
  number="10",
  pages="2721--2734",
  doi="10.1109/TBME.2020.2969719",
  issn="1558-2531",
  url="https://ieeexplore.ieee.org/document/8970507"
}