Theoretical and experimental comparison of lag-based and time-based exponential moving average models of QT...

In the electrocardiogram, adaptation of the QT interval to variations in heart rate is not instantaneous. Quantification of this hysteresis phenomenon relies on mathematical models describing the relation between the RR and QT time series. These models reproduce hysteresis through an effective RR interval computed as a linear combination of the history of past RR intervals. This filter depends on a time constant parameter that may be used as a biomarker.

The most common hysteresis model is based on an autoregressive filter with an impulse response that decreases exponentially with the beat number (lag-based model). Recognizing that the QT time series is unevenly spaced, we propose two exponential moving average filters (time-based models) to define the effective RR interval: one with an impulse response that decreases exponentially with time in seconds, and one with a step response that relaxes exponentially with time in seconds. These two filters are neither linear nor time-invariant. Recurrence formulas are derived to enable efficient implementation.

Application to clinical signals recorded during tilt table test, exercise and 24 h Holter demonstrates that the three models perform similarly in terms of goodness-of-fit. When comparing the hysteresis time constant in two conditions with different heart rates, however, the time-based models are shown to reduce the bias on the hysteresis time constant caused by heart rate acceleration and deceleration.

Time-based models should be considered when intergroup differences in both heart rate and QT hysteresis are expected.