Multi-scale similarity entropy as a new descriptor to differentiate healthy to suffering foetus

摘要

To characterize the complexity of time series extracted from a nonlinear dynamical system, a certain number of descriptors can be used. Here we proposed to use a new descriptor named “similarity-entropy”. This new definition is a modified definition of the well-known sample entropy. As for sample entropy, our definition can be generalized to the multi-scale principle. This new approach is an interesting alternative to the multi-scale sample entropy since, unlike multi-scale sample entropy, it is able to distinguish between healthy and suffering foetus for a large range of scale.