A Study of Early Detection of Subthreshold Depression Based on the Pentatonic Theory

Subthreshold depression(SD) is a prodromal state of depression that both affects quality of life and increases the risk of developing major depression. Early intervention is challenging due to the difficulty of accurate identification by conventional diagnostic methods. Speech, as a natural, non-invasive signal rich in emotional information, has the potential to recognise SD. There is a lack of data related to SD in existing publicly available datasets, so this study established a specialised voice database by self-mining data. The theory of pentatonic can comprehensively reflect the physiological and psychological state of an individual, and has unique advantages that cannot be covered by traditional speech features. Based on this theory, this paper extracted the pentatonic features, i.e., the sum of the energies of the corresponding frequency bands of the five phonemes: Gong, Shang, Jue, Zhi, and Yu. Comparing the distribution of pentatonic energy between SD and healthy people, we found that the pentatonic energy of healthy people is higher than that of SD, and the trend of pentatonic energy is the same in both groups. The results provide a new idea and basis for the early detection and intervention of SD.