Figure 6.

Variable importance extracted from random forest model. (a) The degree of importance of each input feature in classifying the training dataset, represented as percentage: Contraction_time being the most important variable with 100% importance; followed by Contraction_number, Cilia, Rest and Bending. (b) Contribution of each feature to the mean decrease in Gini index (indication of node impurity). The higher the decrease in Gini index, the higher the contribution of the feature to the nodes homogeneity. (Online version in colour.)