Abstract
Detection of mood changes can be useful for the efficacy of drug treatment of psychiatric disorders in major depression. This paper presents an approach for detecting major time points of mood transitions under the influence of antidepressants. These time points, which are indicated by critical fluctuations in time series, can be discovered using change point detection and time-frequency analysis of fuzzy recurrence entropy of mood data. The mood transitions identified by the fuzzy recurrence entropy agree with results that were clinically validated and reported in literature. The proposed approach can detect early mood transitions in a fully objective way that does not require the manual analysis of fluctuations in the signal dynamics.