Contextual information in atrial arrhythmia analysis.
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Atrial Fibrillation↗
Biomedical subjects
G I Rowlandson
Publications and source records attributed to G I Rowlandson.
Evaluation of Fourier transform filter for high-resolution ECG.
The high-resolution electrocardiography has become an important clinical tool for analyzing the high-frequency content of electrocardiograms (ECGs). Recent emphasis has been on the detection of ventricular late potential activity due to its ability to predict ventricular tachycardia (VT) in myocardial infarction (MI) patients. To accentuate the high-frequency components, the signal-averaged ECG data are filtered using high-pass filters. Two types of filters used in commercial systems, bidirectional Butterworth and Fourier transform filters, are compared using a common signal-averaged ECG data base. Signal-averaged ECG data acquired at two clinical sites (Mayo Clinic and Bowman Gray School of Medicine) using the MAC15 HIRES system were filtered using a 40-Hz fast Fourier transform (FFT) filter with a 6 dB/octave rolloff on an IBM-compatible personal computer. The same average data were filtered using a 40-Hz bidirectional Butterworth filter with similar rolloff. Using a common algorithm, outputs of both filters were used to compute vector magnitude and to obtain the measurements to quantify high-frequency, low-amplitude (HFLA) signals. The measurements include total QRS duration, duration of HFLA signals, root mean square voltage, and mean voltage in the terminal 40 msec. Applying the published criteria for late potentials, sensitivity and specificity were computed for both filters on data obtained from 59 patients of old MI (group 1, 29 with clinical or inducible VT and group 2, 30 with no history of VT and noninducible). The results were very similar, and both filters were found to be functionally equivalent.
Action Potentials↗
High-resolution ECG on a standard ECG cart.
High-resolution (HI-RES) ECG analysis software and a new front end have been designed for a standard 12-lead ECG cart, MAC-12. The front end acquires orthogonal ECG at 1,000 samples/sec and 1.2 microV/bit and transmits to the cart. The HI-RES software delineates QRS complexes and correlates them with a template in frequency domain to compute an average cardiac complex (P, QRS, and T). This complex is used for analysis of late potentials, bundle of His activity, and detection of coronary artery disease using its high-frequency content. Both time- and frequency-domain methods are implemented for analysis of ventricular late potentials. In the time-domain method, the average beat is bandpass filtered using three lower cutoff frequencies--25, 40, and 80 Hz--with the higher cutoff at 250 Hz. For each of these frequencies, the following features are extracted: RMS voltages in terminal 40 and 50 msec; ventricular activation time; and duration of high-frequency, low-amplitude signals. The frequency-domain analysis examines the spectral contents of the windowed segment of terminal QRS; ST-segment; and a combined segment of QRS and ST. The spectral features include ratios of magnitudes of Fourier coefficients and areas above 20 Hz, dB drop at 40 Hz, and areas after 60 dB offset. Initial testing of this system is complete, and it is due for clinical trials soon.
Bundle of His↗
Data compression for storage of resting ECGs digitized at 500 samples/second.
Data compression of resting electrocardiograms (ECGs) digitized at 500 samples per second (sps) is presented. Tradeoffs between the fidelity of reconstructed data and the overall compression are examined. Data of the median (average) complexes are retained at 500 sps and full resolution and encoded only to reduce redundancy. The raw data for rhythm analysis are evaluated for lowpass filtering and down-sampling (decimation) and requantization. After subtracting the medians from the raw data, the resulting residue signal is examined in detail for data reduction and encoding. Various options for compression of the residue signal are presented. Specific issues examined are the acceptable decimation and requantization of the residue signal. Another important aspect evaluated is the bimodal decimation of the QRS and the rest of the cardiac complex. Here, the QRS complexes are kept at 500 sps and the rest of the data decimated to lower sampling rates. This novel approach reduces data distortion while achieving significant compression. Details of the compression scheme and its evaluation on uncompressed 500-sps ECGs from the European Common Standards for Electrocardiography (CSE) database (128 ECGs with normal sinus rhythm, atrioventricular blocks, atrial fibrillation and flutter, ventricular arrhythmias, and excessive noise) are elucidated. Performance indexes [root mean square (RMS) error, percent RMS difference, normalized RMS difference, maximum peak error, and compression ratio] are computed. To validate the compression method, qualitative evaluation was performed by two physicians overreading the ECGs by comparing the reconstructed waveforms with the original uncompressed data. The median data are retained at 500 sps and full precision. For rhythm data, the bimodal decimation of the residue signal to 125 sps at 10 microvolts resolution preserved the fidelity of the ECG signals well, while giving good data compression. Abnormal atrial activity was well preserved and the QRS was retained without distortion. The average size of a 10-sec compressed ECG with the medians is around 4.5 kilobytes.
Diagnosis, Computer-Assisted↗