4.7 Article

Analysis of emotional prosody as a tool for differential diagnosis of cognitive impairments: a pilot research

Journal

FRONTIERS IN PSYCHOLOGY
Volume 14, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fpsyg.2023.1129406

Keywords

dementia; mild cognitive impairment; emotion; prosody; acoustic analysis; listener perception; diagnosis

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This pilot research examines if prosodic features can be used to differentiate between dementia of the Alzheimer's type (DAT), vascular dementia (VaD), mild cognitive impairment (MCI), and healthy cognition. The study utilizes both acoustic measurements and listeners' perception of emotional prosody differences. The results indicate that both the acoustic data and perceptual data can successfully distinguish between the four groups. This study suggests that using acoustic measures of prosodic features may be a useful method for differentiating these cognitive conditions.
IntroductionThis pilot research was designed to investigate if prosodic features from running spontaneous speech could differentiate dementia of the Alzheimer's type (DAT), vascular dementia (VaD), mild cognitive impairment (MCI), and healthy cognition. The study included acoustic measurements of prosodic features (Study 1) and listeners' perception of emotional prosody differences (Study 2). MethodsFor Study 1, prerecorded speech samples describing the Cookie Theft picture from 10 individuals with DAT, 5 with VaD, 9 with MCI, and 10 neurologically healthy controls (NHC) were obtained from the DementiaBank. The descriptive narratives by each participant were separated into utterances. These utterances were measured on 22 acoustic features via the Praat software and analyzed statistically using the principal component analysis (PCA), regression, and Mahalanobis distance measures. ResultsThe analyses on acoustic data revealed a set of five factors and four salient features (i.e., pitch, amplitude, rate, and syllable) that discriminate the four groups. For Study 2, a group of 28 listeners served as judges of emotions expressed by the speakers. After a set of training and practice sessions, they were instructed to indicate the emotions they heard. Regression measures were used to analyze the perceptual data. The perceptual data indicated that the factor underlying pitch measures had the greatest strength for the listeners to separate the groups. DiscussionThe present pilot work showed that using acoustic measures of prosodic features may be a functional method for differentiating among DAT, VaD, MCI, and NHC. Future studies with data collected under a controlled environment using better stimuli are warranted.

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