Your browser doesn't support javascript.
loading
A new algorithm to reduce T-wave over-sensing based on phase space reconstruction in S-ICD system.
Chen, Hanjie; Wiles, Benedict M; Roberts, Paul R; Morgan, John M; Maharatna, Koushik.
Afiliación
  • Chen H; School of Electronics and Computer Science, University of Southampton, Southampton, UK. Electronic address: hc4y15@soton.ac.uk.
  • Wiles BM; Cardiac Rhythm Management Research, University Hospital Southampton NHS Foundation Trust, Southampton, UK; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Roberts PR; Cardiac Rhythm Management Research, University Hospital Southampton NHS Foundation Trust, Southampton, UK; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Morgan JM; Faculty of Medicine, University of Southampton, Southampton, UK.
  • Maharatna K; School of Electronics and Computer Science, University of Southampton, Southampton, UK.
Comput Biol Med ; 137: 104804, 2021 10.
Article en En | MEDLINE | ID: mdl-34478924
ABSTRACT
BACKGROUND AND

OBJECTIVE:

The subcutaneous implantable cardioverter defibrillator (S-ICD) reduces mortality in individuals at high risk of sudden arrhythmic death, by rapid defibrillation of life-threatening arrhythmia. Unfortunately, S-ICD recipients are also at risk of inappropriate shock therapies, which themselves are associated with increased rates of mortality and morbidity. The commonest cause of inappropriate shock therapies is T wave oversensing (TWOS), where T waves are incorrectly counted as R waves leading to an overestimation of heart rate. It is important to develop a method to reduce TWOS and improve the accuracy of R-peak detection in S-ICD system.

METHODS:

This paper introduces a novel algorithm to reduce TWOS based on phase space reconstruction (PSR); a common method used to analyse the chaotic characteristics of non-linear signals.

RESULTS:

The algorithm was evaluated against 34 records from University Hospital Southampton (UHS) and all 48 records from the MIT-BIH arrhythmia database. In the UHS analysis we demonstrated a sensitivity of 99.88%, a positive predictive value of 99.99% and an accuracy of 99.88% with reductions in TWOS episodes (from 166 to 0). Whilst in the MIT-BIH analysis we demonstrated a sensitivity of 99.87%, a positive predictive value of 99.99% and an accuracy of 99.91% for R wave detection. The average processing time for 1 min ECG signals from all records is 2.9 s.

CONCLUSIONS:

Our algorithm is sensitive for R-wave detection and can effectively reduce the TWOS with low computational complexity, and it would therefore have the potential to reduce inappropriate shock therapies in S-ICD recipients, which would significantly reduce shock related morbidity and mortality, and undoubtedly improving patient's quality of life.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Desfibriladores Implantables Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Desfibriladores Implantables Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2021 Tipo del documento: Article