SampEn is a measure of complexity that can be easily applied to any type of time series data, including physiological data such as heart rate variability and EEG data.
SampEn is conceptually similar to approximate entropy (ApEn), but has following differences:
1) SampEn does not count self-matching. The possible trouble of having log(0) is avoided by taking logarithm at the latest step.
2) SampEn does not depend on the datasize as much as ApEn does. The comparison is shown in the graph above. This property makes it amenable to applications with relatively short data size.
This code uses the same vectorisation technique as in Fast Approximate Entropy, another submission from the same author. |