A new method to estimate the amplitude spectrum analysis of ventricular fibrillation during cardiopulmonary resuscitation

Men Tzung Lo, Lian Yu Lin, Wan Hsin Hsieh, Patrick Chow In Ko, Yen Bin Liu, Chen Lin, Yi Chung Chang, Cheng Yen Wang, Vincent Hsu Wen Young, Wen Chu Chiang, Jiunn Lee Lin, Wen Jone Chen, Matthew Huei Ming Ma

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

AIMS: Accurate ventricular fibrillation (VF) waveform analysis usually requires rescuers to discontinue cardiopulmonary resuscitation (CPR). However, prolonged "hands-off" time has a deleterious impact on the outcome. We developed a new filter technique that could clean the CPR artifacts and help preserve the shockability index of VF. METHODS: We analyzed corrupted ECGs, which were constructed by randomly adding different scaled CPR artifacts to the VF waveforms. A newly developed algorithm was used to identify the CPR fluctuations. The algorithm contained two steps. First, decomposing the raw data by empirical mode decomposition (EMD) into several intrinsic mode fluctuations (IMFs) and combining the dominant IMFs to reconstruct a new signal. Second, calculating each CPR cycle frequency from the new signal and fitting the new signal to the original corrupted ECG by least square mean (LSM) method to derive the CPR artifacts. The estimated VF waveform was derived by subtraction of the CPR artifacts from the corrupted ECG. We then performed amplitude spectrum analysis (AMSA) for original VF, corrupted ECG and estimated VF. RESULTS: A total of 150 OHCA subjects with initial VF rhythm were included for analysis. Ten CPR artifacts signals were used to construct corrupted ECG. Even though the correlations of AMSA between the corrupted ECG vs. the original VF and the estimated VF vs. the original VF are all high (all p<. 0.001), the values of AMSA were obviously biased in corrupted ECG with wide limits of agreement in Bland-Altman mean-difference plot. ROC analysis of the AMSA in the prediction of defibrillation success showed that the new algorithm could preserve the cut-off AMSA value for CPR artifacts with power ratio to VF from 0 to 6. dB. CONCLUSION: The new algorithm could efficiently filter the CPR-related artifacts of the VF ECG and preserve the shockability index of the original VF waveform.

Original languageEnglish
Pages (from-to)1505-1511
Number of pages7
JournalResuscitation
Volume84
Issue number11
DOIs
Publication statusPublished - Nov 1 2013
Externally publishedYes

Fingerprint

Cardiopulmonary Resuscitation
Ventricular Fibrillation
Spectrum Analysis
Electrocardiography
Artifacts
Least-Squares Analysis
ROC Curve
Hand

Keywords

  • Amplitude spectrum analysis
  • Automated external defibrillator
  • Empirical mode decomposition
  • Least mean square
  • Ventricular fibrillation

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine
  • Emergency
  • Emergency Medicine

Cite this

A new method to estimate the amplitude spectrum analysis of ventricular fibrillation during cardiopulmonary resuscitation. / Lo, Men Tzung; Lin, Lian Yu; Hsieh, Wan Hsin; Ko, Patrick Chow In; Liu, Yen Bin; Lin, Chen; Chang, Yi Chung; Wang, Cheng Yen; Young, Vincent Hsu Wen; Chiang, Wen Chu; Lin, Jiunn Lee; Chen, Wen Jone; Ma, Matthew Huei Ming.

In: Resuscitation, Vol. 84, No. 11, 01.11.2013, p. 1505-1511.

Research output: Contribution to journalArticle

Lo, MT, Lin, LY, Hsieh, WH, Ko, PCI, Liu, YB, Lin, C, Chang, YC, Wang, CY, Young, VHW, Chiang, WC, Lin, JL, Chen, WJ & Ma, MHM 2013, 'A new method to estimate the amplitude spectrum analysis of ventricular fibrillation during cardiopulmonary resuscitation', Resuscitation, vol. 84, no. 11, pp. 1505-1511. https://doi.org/10.1016/j.resuscitation.2013.07.004
Lo, Men Tzung ; Lin, Lian Yu ; Hsieh, Wan Hsin ; Ko, Patrick Chow In ; Liu, Yen Bin ; Lin, Chen ; Chang, Yi Chung ; Wang, Cheng Yen ; Young, Vincent Hsu Wen ; Chiang, Wen Chu ; Lin, Jiunn Lee ; Chen, Wen Jone ; Ma, Matthew Huei Ming. / A new method to estimate the amplitude spectrum analysis of ventricular fibrillation during cardiopulmonary resuscitation. In: Resuscitation. 2013 ; Vol. 84, No. 11. pp. 1505-1511.
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AU - Lin, Lian Yu

AU - Hsieh, Wan Hsin

AU - Ko, Patrick Chow In

AU - Liu, Yen Bin

AU - Lin, Chen

AU - Chang, Yi Chung

AU - Wang, Cheng Yen

AU - Young, Vincent Hsu Wen

AU - Chiang, Wen Chu

AU - Lin, Jiunn Lee

AU - Chen, Wen Jone

AU - Ma, Matthew Huei Ming

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N2 - AIMS: Accurate ventricular fibrillation (VF) waveform analysis usually requires rescuers to discontinue cardiopulmonary resuscitation (CPR). However, prolonged "hands-off" time has a deleterious impact on the outcome. We developed a new filter technique that could clean the CPR artifacts and help preserve the shockability index of VF. METHODS: We analyzed corrupted ECGs, which were constructed by randomly adding different scaled CPR artifacts to the VF waveforms. A newly developed algorithm was used to identify the CPR fluctuations. The algorithm contained two steps. First, decomposing the raw data by empirical mode decomposition (EMD) into several intrinsic mode fluctuations (IMFs) and combining the dominant IMFs to reconstruct a new signal. Second, calculating each CPR cycle frequency from the new signal and fitting the new signal to the original corrupted ECG by least square mean (LSM) method to derive the CPR artifacts. The estimated VF waveform was derived by subtraction of the CPR artifacts from the corrupted ECG. We then performed amplitude spectrum analysis (AMSA) for original VF, corrupted ECG and estimated VF. RESULTS: A total of 150 OHCA subjects with initial VF rhythm were included for analysis. Ten CPR artifacts signals were used to construct corrupted ECG. Even though the correlations of AMSA between the corrupted ECG vs. the original VF and the estimated VF vs. the original VF are all high (all p<. 0.001), the values of AMSA were obviously biased in corrupted ECG with wide limits of agreement in Bland-Altman mean-difference plot. ROC analysis of the AMSA in the prediction of defibrillation success showed that the new algorithm could preserve the cut-off AMSA value for CPR artifacts with power ratio to VF from 0 to 6. dB. CONCLUSION: The new algorithm could efficiently filter the CPR-related artifacts of the VF ECG and preserve the shockability index of the original VF waveform.

AB - AIMS: Accurate ventricular fibrillation (VF) waveform analysis usually requires rescuers to discontinue cardiopulmonary resuscitation (CPR). However, prolonged "hands-off" time has a deleterious impact on the outcome. We developed a new filter technique that could clean the CPR artifacts and help preserve the shockability index of VF. METHODS: We analyzed corrupted ECGs, which were constructed by randomly adding different scaled CPR artifacts to the VF waveforms. A newly developed algorithm was used to identify the CPR fluctuations. The algorithm contained two steps. First, decomposing the raw data by empirical mode decomposition (EMD) into several intrinsic mode fluctuations (IMFs) and combining the dominant IMFs to reconstruct a new signal. Second, calculating each CPR cycle frequency from the new signal and fitting the new signal to the original corrupted ECG by least square mean (LSM) method to derive the CPR artifacts. The estimated VF waveform was derived by subtraction of the CPR artifacts from the corrupted ECG. We then performed amplitude spectrum analysis (AMSA) for original VF, corrupted ECG and estimated VF. RESULTS: A total of 150 OHCA subjects with initial VF rhythm were included for analysis. Ten CPR artifacts signals were used to construct corrupted ECG. Even though the correlations of AMSA between the corrupted ECG vs. the original VF and the estimated VF vs. the original VF are all high (all p<. 0.001), the values of AMSA were obviously biased in corrupted ECG with wide limits of agreement in Bland-Altman mean-difference plot. ROC analysis of the AMSA in the prediction of defibrillation success showed that the new algorithm could preserve the cut-off AMSA value for CPR artifacts with power ratio to VF from 0 to 6. dB. CONCLUSION: The new algorithm could efficiently filter the CPR-related artifacts of the VF ECG and preserve the shockability index of the original VF waveform.

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KW - Least mean square

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KW - Amplitude spectrum analysis

KW - Automated external defibrillator

KW - Empirical mode decomposition

KW - Least mean square

KW - Ventricular fibrillation

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