A novel approach for the averaging of magnetocardiographically recorded heart beats

Performing signal averaging in an efficient and correct way is indispensable since it is a prerequisite for a broad variety of magnetocardiographic (MCG) analysis methods. One of the most common procedures for performing the signal averaging to increase the signal-to-noise ratio (SNR) in magnetocardiography, as well as in electrocardiography (ECG), is done by means of spatial or temporal techniques. In this paper, an improvement of the temporal averaging method is presented. In order to obtain an accurate signal detection, temporal alignment methods and objective classification criteria are developed. The processing technique based on hierarchical clustering is introduced to take into account the non-stationarity of the noise and, to some extent, the biological variability of the signals reaching the optimum SNR. The method implemented is especially designed to run fast and does not require any interaction from the operator. The averaging procedure described in this work is applied to the averaging of MCG data as an example, but with its intrinsic properties it can also be applied to the averaging of ECG recording, averaging of body-surface-potential mapping (BSPM) and averaging of magnetoencephalographic (MEG) or electroencephalographic (EEG) signals.

[1]  R. Fenici,et al.  Magnetocardiographic Localization of a Pacing Catheter , 1989 .

[2]  M Hoke,et al.  Weighted averaging--theory and application to electric response audiometry. , 1984, Electroencephalography and clinical neurophysiology.

[3]  L Toivonen,et al.  Identification of patients with ventricular tachycardia after myocardial infarction by high-resolution magnetocardiography and electrocardiography. , 1993, Journal of electrocardiology.

[4]  V. Hombach,et al.  On the variability of QRS time-duration in magnetocardiographic recordings , 2003, Journal of medical engineering & technology.

[5]  L Trahms,et al.  Magnetocardiographic analysis of the two-dimensional distribution of intra-QRS fractionated activation. , 1999, Physics in medicine and biology.

[6]  C Elberling,et al.  Estimation of auditory brainstem response, ABR, by means of Bayesian inference. , 1985, Scandinavian audiology.

[7]  Birger Kollmeier,et al.  Single-sweep-based methods to improve the quality of auditory brain stem responses , 2001 .

[8]  Jacek M. Leski.  Robust weighted averaging [of biomedical signals] , 2002, IEEE Transactions on Biomedical Engineering.

[9]  R. Mühler,et al.  Reduction of Background Noise in Human Auditory Brainstem Response by Means of Classified Averaging , 1997 .

[10]  G. Stroink,et al.  Magnetocardiographic and Electrocardiographic Recordings of Patients with Ventricular Tachycardia , 1989 .

[11]  H von Specht,et al.  Sorted averaging--principle and application to auditory brainstem responses. , 1999, Scandinavian audiology.

[12]  D. Kreiseler,et al.  Fragmentation of bandpass-filtered QRS-complex of patients prone to malignant arrhythmia , 1998, Medical and Biological Engineering and Computing.

[13]  P. Werle,et al.  The limits of signal averaging in atmospheric trace-gas monitoring by tunable diode-laser absorption spectroscopy (TDLAS) , 1993 .

[14]  B. Lütkenhöner,et al.  Possibilities and limitations of weighted averaging , 2004, Biological Cybernetics.

[15]  Werner Moshage,et al.  Vergleich der Time-Domain-Analyse von Late Potentials im signalgemittelten Elektrokardiogramm und Magnetokardiogramm , 1996 .

[16]  O Rompelman,et al.  Coherent averaging technique: a tutorial review. Part 2: Trigger jitter, overlapping responses and non-periodic stimulation. , 1986, Journal of biomedical engineering.

[17]  S. N. Erné,et al.  Magnetocardiography under Clinical Conditions , 1999 .

[18]  William Craelius,et al.  Criteria for Optimal Averaging of Cardiac Signals , 1986, IEEE Transactions on Biomedical Engineering.

[19]  Michael E. Cain,et al.  Signal-averaged electrocardiography , 1996 .

[20]  H. H. Ros,et al.  Coherent averaging technique: a tutorial review. Part 1: Noise reduction and the equivalent filter. , 1986, Journal of biomedical engineering.

[21]  P. Caminal,et al.  Alignment methods for averaging of high-resolution cardiac signals: a comparative study of performance , 1991, IEEE Transactions on Biomedical Engineering.

[22]  M. Burghoff,et al.  Magnetocardiographic localization of accessory conduction pathway in patients suffering from WPW syndrome , 1995, Computers in Cardiology 1995.