AIM OF THE STUDY: To evaluate influence of the skeletal muscle activity (SMA) on time and frequency domain properties of ECG during VF. MATERIALS AND METHODS: We studied the first 9min of electrically induced VF (N=7). We recorded Lead II ECG, 247 unipolar epicardial ventricular electrograms (UEGs) and 3 bipolar skeletal electromyograms (EMGs) near the positions of the ECG electrodes (sampling rate, 500Hz). We reconstructed ECG (RECG) from UEGs using forward-solution transformation matrix. Spectral properties of ECG, RECG, UEGs and MEGs were assessed in the range 2-250Hz by the median frequency (MF) and the upper limit of frequency range containing 99% of spectral energy (Flim(99)). Scaling exponent of ECG, RECG and EMGs was calculated in the ranges of 1-8 and 5-20 sampling intervals (ScE1-8 and ScE5-20, respectively). RESULTS: We observed non-monotonic increases in MF and Flim(99) of the ECG, but not UEGs and RECG, at 1-5min of VF. Maximum values of MF and Flim(99) in ECG, UEGs and RECG were (in Hz): 32+/-29 and 166+/-67; 11+/-2 and 36+/-7; 10+/-2 and 32+/-6, respectively. The transient increases in the high-frequency content of the ECG were correlated with enhanced activity in EMGs, characterized by an almost uniform spectrum in the range 2-250Hz (MF=92+/-29; Flim(99)=245+/-4Hz). Peak values of ScE(1-8) were the highest in EMGs (1.95+/-0.04), intermediate in the ECG (1.59+/-0.26), and the lowest in RECG (1.088+/-0.007). CONCLUSION: SMA significantly contributes to ECG during VF and can bias metrics used for assessment of VF organization.
AIM OF THE STUDY: To evaluate influence of the skeletal muscle activity (SMA) on time and frequency domain properties of ECG during VF. MATERIALS AND METHODS: We studied the first 9min of electrically induced VF (N=7). We recorded Lead II ECG, 247 unipolar epicardial ventricular electrograms (UEGs) and 3 bipolar skeletal electromyograms (EMGs) near the positions of the ECG electrodes (sampling rate, 500Hz). We reconstructed ECG (RECG) from UEGs using forward-solution transformation matrix. Spectral properties of ECG, RECG, UEGs and MEGs were assessed in the range 2-250Hz by the median frequency (MF) and the upper limit of frequency range containing 99% of spectral energy (Flim(99)). Scaling exponent of ECG, RECG and EMGs was calculated in the ranges of 1-8 and 5-20 sampling intervals (ScE1-8 and ScE5-20, respectively). RESULTS: We observed non-monotonic increases in MF and Flim(99) of the ECG, but not UEGs and RECG, at 1-5min of VF. Maximum values of MF and Flim(99) in ECG, UEGs and RECG were (in Hz): 32+/-29 and 166+/-67; 11+/-2 and 36+/-7; 10+/-2 and 32+/-6, respectively. The transient increases in the high-frequency content of the ECG were correlated with enhanced activity in EMGs, characterized by an almost uniform spectrum in the range 2-250Hz (MF=92+/-29; Flim(99)=245+/-4Hz). Peak values of ScE(1-8) were the highest in EMGs (1.95+/-0.04), intermediate in the ECG (1.59+/-0.26), and the lowest in RECG (1.088+/-0.007). CONCLUSION: SMA significantly contributes to ECG during VF and can bias metrics used for assessment of VF organization.
Authors: H E Wang; J J Menegazzi; C B Lightfoot; C W Callaway; K C Fertig; L D Sherman; M Hsieh Journal: Acad Emerg Med Date: 2001-08 Impact factor: 3.451
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