The entropy of chaotic transitions of EEG phase growth in bipolar disorder with lithium carbonate.

The application of chaos measures the association of EEG signals which allows for differentiating pre and post-medicated epochs for bipolar patients. We propose a new approach on chaos necessary for proof of EEG metastability. Shannon entropies of concealed patterns of Schwarzian derivatives from absolute instantaneous frequency transformations of EEG signals after Hilbert transform are compared and found significantly statistically different between pre and post-medication periods when fitted to von Bertalanffy's functions.

Corrigendum to "CFC delta-beta is related with mixed features and response to treatment in bipolar II depression" [Heliyon 5 (6) (June 2019) e01898].

[This corrects the article DOI: 10.1016/j.heliyon.

Comparison of the data classification approaches to diagnose spinal cord injury.

In our previous study, we have demonstrated that analyzing the skin impedances measured along the key points of the dermatomes might be a useful supplementary technique to enhance the diagnosis of spinal cord injury (SCI), especially for unconscious and noncooperative patients. Initially, in order to distinguish between the skin impedances of control group and patients, artificial neural networks (ANNs) were used as the main data classification approach. However, in the present study, we have proposed two more data classification approaches, that is, support vector machine (SVM) and hierarchical cluster tree analysis (HCTA), which improved the classification rate and also the overall performance.