Combining speech biomarkers for cognition and mood improves diagnostic accuracy between MCI and subjective cognitive decliners in a memory clinic sample

Abstract

AbstractIntroductionDepressive symptoms are a common comorbidity in an old age memory clinic population. Cognitive and affective syndromes coexist, and supposedly modulate each other. While, there have been separate research streams on analysing speech to infer cognitive performance, as well as mood related symptoms, they are seldom investigated side‐by‐side. We present results from a small sub sample of a larger MCI and dementia cohort indicating that modelling both depressive symptoms and cognitive problems from speech can improve the diagnostic accuracy for MCI above speech biomarkers for cognition alone.MethodsThe ki:e Speech Biomarker for cognition (ki:e SB‐C; Tröger et al., 2022) and a free speech task were collected from 35 memory clinic participants (12F) with 10 of them having an MCI diagnosis (compare Table 1). From the free speech tasks (“Tell me about your upcoming vacation plans.”) we extracted speech features using ki:elements proprietary speech analysis engine SIGMA. Free speech features were corrected for cognitive performance, sex and age and then combined into a mood speech biomarker. To benchmark the diagnostic utility of both cognitive and mood speech biomarker side by side, we trained two groups of simple classifiers (tree based classifiers with leave one participant out cross validation) once with SB‐C alone and once with both SB‐C and the newly‐composed mood speech biomarker.ResultsBy combining the speech biomarker for cognition and mood diagnostic performance was significantly improved (AUC of 88%) as compared to classification with the SB‐C alone (AUC of 74%). The mood biomarker correlates significantly with the Geriatric Depression Scale (r = 0.39, p < 0.05). Most important free speech features were jitter, number or pauses, mean pause duration or pronoun rate.ConclusionOverall we present rare evidences that combining speech‐based digital biomarkers tapping both into cognition but also mood‐related symptoms helps to improve diagnostic accuracy in MCI patients. Though just a small feasibility study, the results are clearly encouraging and point towards potential application in both clinical practice as well as clinical research.