Enhancement of low-level ECG components in noise with time-sequenced adaptive filtering

Observation of low amplitude components in the ECG motivated our interest in time-sequenced adaptive filtering. This technique is applicable to signals that are cyclic in nature. Two simultaneously acquired signals are used in the technique. It is assumed that the underlying signal is correlated and that noise is uncorrelated between the two channels. Instead of one enhancer that continuously adjusts its characteristics over the time course of the signal, each cycle is subdivided into intervals; a given enhancer is used only on the same corresponding interval in successive cycles. This minimizes the signal range over which the enhancer must adjust its characteristics. In the time-sequenced approach, it is important that the enhancers adapt at the same rate. Thus, each has its own feedback coefficient derived from an average of 10 consecutive ECG cycles and an estimate of noise in intervals where no signal is present. Each feedback coefficient is augmented over the first 10 beats. To improve adaptation, a means to update each filter on the preceding beat and the current beat was developed. Lastly, a weight averaging scheme was developed to circumvent weight stalling. The procedure has enabled observation of both His activity and late potentials in individual beats from signals acquired from the chest surface.