Key result
Algorithms based on interpolating techniques introduced the least error with 16-bit data, while least-squares data fit methods performed best on less accurate 8-bit data.
Population
Model derivative of the left ventricular pressure waveform with 8, 12, and 16 bit quantization noise
Comparison
Five commonly used algorithms for digital… vs Comparison among the five algorithms
Design
Other
Authors
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Match algorithm to bit depth for minimal LV pressure derivative error; leaves open clinical validation in patient waveforms.
The optimal digital differentiation algorithm for computing the derivative of left ventricular pressure depends on the quantization noise level, with interpolating techniques better for 16-bit data and least-squares methods better for 8-bit data.
Marble et al. (1981) studied this question. Digital differentiation algorithms vs. Alternative algorithms was evaluated on rms error between a model derivative of the left ventricular pressure waveform and the approximate results of each algorithm. Algorithms based on interpolating techniques introduced the least error with 16-bit data, while least-squares data fit methods performed best on less accurate 8-bit data.
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