Dysarthria assessment in multiple sclerosis patients

Abstract

Background:

Speech patterns in multiple sclerosis (MS) are poorly characterized. Software such as Dysarthria Analyzer (DA) performs a detailed speech analysis.

Objective:

The objective of the study is (1) to explore speech features in patients with MS and (2) to investigate correlations between speech features and clinic-demographic characteristics.

Methods:

Patients underwent clinical assessments (Expanded Disability Status Scale (EDSS) and Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS)) and speech evaluation using the DA. Each patient performed 6 vocal tasks: phonation A, phonation I, reading, monologue, fast syllables repetitions. The DA extracted 23 speech features as age-, gender-, and education-adjusted z-scores against healthy controls. A principal component analysis was conducted. Correlations between the components and clinic-demographic features were assessed through stepwise analysis.

Results:

We enrolled 72 patients (50 females; mean age 48.1 ± 10.9 years; median EDSS of 3 (1.5–6.5)). Principal component analysis (PCA) identified a 7-component model: Voice Intensity, Voice Intensity Variation, Motor Coordination, Speech Diadochokinesis, Speech Speed, Voice Strength, Speech Latency. Higher EDSS is associated with worse Voice Intensity Variation (r = –0.23; p = 0.05), Speech Speed (r = –0.40; p = 0.001) and Speech Latency (r = –0.23; p = 0.05). Progressive MS patients showed worse Voice Intensity Variation (coeff. = −1.20; p = 0.002). Worse cognitive functioning correlated with worse Speech Speed (coeff. = −0.38; p = 0.02).

Conclusion:

Detailed speech analysis can reveal useful clinical information about physical and cognitive disability in MS possibly representing an additional tool to assess disability.