How to Use Speech Related Digital Biomarkers in Patients With Depressive Disorder

Speech contains valuable insights into the speaker's physiology and potential pathophysiological conditions.Speech-related biomarkers hold promise in describing depressive disorders which modifies various bio-acoustic features of speech, and by quantifying and examining these alterations, conventional treatments can be augmented, leading to improved clinical outcomes.In this review, we utilize speech as a source to derive objective biomarkers for depression and review the key bio-acoustic characteristics often quantified in relation to depression.Moreover, we discuss how depression impacts speech production and influences bio-acoustic speech features.Furthermore, we summarize findings from speech-related biomarkers aimed at complementing clinical assessments, improving diagnosis, monitoring treatment response, enhancing healthcare quality, facilitating remote patient monitoring, and reducing assessment cost and time.Computerized speech processing has enabled objective analysis of speech patterns and the classification of speakers' conditions using machine learning algorithms.Promising early results indicate the potential for integrating depression screening into clinical practice using these technologies which enabled the automation of analysis, making it more accessible for real-world implementation.Emerging evidence supports the use of speech analysis to figure out objective biomarkers in major depressive disorder (MDD).Computerized speech processing has revolutionized the objective analysis of speech patterns, allowing for the feasibility of integrating depression screening into clinical practice through automated analysis.More and more evidences highlight the utility of speech analysis in identifying objective biomarkers for depression.In conclusion, speech-related biomarkers show possibilities for early detection of MDD and monitoring symptoms or treatment.Integrating linguistic and acoustic analysis could improve diagnostic accuracy.Future research should address confounders and standardization to improve reliability in screening and treatment monitoring for depression.We are expecting the integration of speech analysis into both clinical practice and everyday life is anticipated in the near future.