Cubic interpolation provides a fast and accurate method to improve RR interval measurement resolution from low sampling rate ECGs.
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May enable RR-interval analysis from low-sampling-rate ECG devices; leaves open prospective clinical validation before routine use.
The measurement of successive RR intervals, obtained from the electrocardiogram (ECG), is the basis of any subsequent method for the assessment of variations in heart rate, for example using intervalograms, histograms, trend curves, spectral analysis, etc. The accuracy of measurement directly depends on the sampling rate used for the acquisition of the ECG signal. Depending on specific applications, rates down to 128 Hz are not uncommon. This considerably limits the resolution if RR interval data are to be derived. Interpolation is often employed for solving problems of this type. Linear, cubic and spline interpolations, obtained directly from the MATLAB software product, were applied and compared for the purpose of RR interval measurement. The cubic method was found to combine the improvement of resolution (+/-1 ms) at sampling rates successfully down to 100 Hz, with a rapid operating speed. Comparison examples are given with ECG signals acquired with 1000 Hz, 16-bit sampling.
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Daskalov et al. (1997) studied this question.
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