[Adaptive Cardiopulmonary Resuscitation Artifacts Elimination Algorithm Based on Empirical Mode Decomposition and Independent Component Analysis].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
; 33(5): 834-41, 2016 Oct.
Article
en Zh
| MEDLINE
| ID: mdl-29714929
ABSTRACT
Artifacts produced by chest compression during cardiopulmonary resuscitation(CPR)seriously affect the reliability of shockable rhythm detection algorithms.In this paper,we proposed an adaptive CPR artifacts elimination algorithm without needing any reference channels.The clean electrocardiogram(ECG)signals can be extracted from the corrupted ECG signals by incorporating empirical mode decomposition(EMD)and independent component analysis(ICA).For evaluating the performance of the proposed algorithm,a back propagation neural network was constructed to implement the shockable rhythm detection.A total of 1 484 corrupted ECG samples collected from pigs were included in the analysis.The results of the experiments indicated that this method would greatly reduce the effects of the CPR artifacts and thereby increase the accuracy of the shockable rhythm detection algorithm.
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Bases de datos:
MEDLINE
Asunto principal:
Algoritmos
/
Reanimación Cardiopulmonar
/
Artefactos
/
Electrocardiografía
Tipo de estudio:
Prognostic_studies
Límite:
Animals
/
Humans
Idioma:
Zh
Revista:
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi
Asunto de la revista:
ENGENHARIA BIOMEDICA
Año:
2016
Tipo del documento:
Article