Making a Distinction Between Schizophrenia and Bipolar Disorder Based on Temporal Parameters in Spontaneous Speech

Schizophrenia is a heterogeneous chronic and severe mental disorder. There are several different theories for the development of schizophrenia from an etiological point of view: neurochemical, neuroanatomical, psychological and genetic factors may also be present in the background of the disease. In this study, we examined spontaneous speech productions by patients suffering from schizophrenia (SCH) and bipolar disorder (BD). We extracted 15 temporal parameters from the speech excerpts and used machine learning techniques for distinguishing the SCH and BD groups, their subgroups (SCH-S and SCH-Z) and subtypes (BD-I and BD-II). Our results indicated, that there is a notable difference between spontaneous speech productions of certain subgroups, while some appears to be indistinguishable for the used classification model. Firstly, SCH and BD groups were found to be different. Secondly, the results of SCH-S subgroup were distinct from BD. Thirdly, the spontaneous speech of the SCH-Z subgroup was found to be very similar to the BDI, however, it was sharply distinct from BD-II. Our detailed examination highlighted the indistinguishable subgroups and led to us to make our S and Z theory more clarified.