Digital filtering and regression algorithms for an accurate detection of the baseline in ECG signals

Time-varying digital filtering of ECG baseline wander

Time-varying filtering techniques are applied to the problem of baseline correction by letting the cut-off frequency of a linear filter be controlled by the low-frequency properties of the ECG signal. The time-varying filter is implemented as a bank of linear low-pass filters, in which each filter has a slightly differing cut-off frequency. Sampling rate decimation and interpolation are employed because the design of a filter for baseline reduction can be treated as a narrowband filtering problem. All filters have a linear phase response to reduce, for example, ST-segment distortion. The performance of the technique presented is studied on ECG signals with different types of simulated baseline wander. The results are compared with the performance of time-invariant linear filtering and cubic spline interpolation. The results show that an improvement in performance can be achieved when using time-varying filtering, especially at low heart rates or during episodes with excessive base-line wander.