Using complexity –entropy planes to detect Parkinson’s disease from short segments of haemodynamic signals

Objective . There is emerging evidence that analysing the entropy and complexity of biomedical
signals can detect underlying changes in physiology which may be reflective of disease pathology.
This approach can be used even when only short recordings of biomedical signals are available. This
study aimed to determine whether entropy and complexity measures can detect differences between
subjects with Parkinsons disease and healthy controls (HCs). Approach . A method based on a diagram
of entropy versus complexity, named complexity –entropy plane, was used to re-analyse a dataset of
cerebral haemodynamic signals from subjects with Parkinsons disease and HCs obtained under
poikilocapnic conditions. A probability distribution for a set of ordinal patterns, designed to
capture regularities in a time series, was computed from each signal under analysis. Four types of
entropy and ten types of complexity measures were estimated from these distributions. Mean values of
entrop...

Source: Physiological Measurement - August 26, 2021 Category: Physiology Authors: J L Jara, Catalina Morales-Rojas, Juan Fern ández-Muñoz, Victoria J Haunton and Max Chacón Source Type: research