SARAspeech-Feasibility of automated assessment of ataxic speech disturbance.
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ABSTRACT:
SUBMITTER: Grobe-Einsler M
PROVIDER: S-EPMC10020430 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
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SARA<sup>speech</sup>-Feasibility of automated assessment of ataxic speech disturbance.
Grobe-Einsler M M Faber J J Taheri A A Kybelka J J Raue J J Volkening J J Helmhold F F Synofzik M M Klockgether T T
NPJ digital medicine 20230316 1
Ataxias are a group of movement disorders that are characterized by progressive loss of balance, impaired coordination and speech disturbance, which together lead to markedly reduced quality of life. Speech disturbance is clinically diagnosed, but methods for objective assessment of severity are lacking. Using 71 sets of speech recordings from ataxia patients, we developed an automated classification system. With a tolerance of ±1 point, this classification system correctly predicted experts' ra ...[more]
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Project description:ObjectiveTo examine the usefulness of the Scale for the Assessment and Rating of Ataxia (SARA) in ataxic stroke patients.MethodThis was a retrospective study of 54 patients following their first ataxic stroke. The data used in the analysis comprised ambulation status on admission and scores on the SARA, the Korean version of the Modified Barthel Index (K-MBI) and the Berg Balance Scale (BBS). The subjects were divided into four groups by gait status and into five groups by level of dependency in activities of daily living (ADLs) based on their K-MBI scores. Data were subjected to a ROC curve analysis to obtain cutoff values on the SARA for individual gait status and levels of activity dependency. The correlations between the SARA, K-MBI and BBS scores were also computed.ResultsThere was significant correlation between the SARA and the K-MBI scores (p<0.001), and this correlation (r=-0.792) was higher than that found between the BBS and the K-MBI scores (r=0.710). The SARA scores of upper extremity ataxia categories were significantly related to the K-MBI scores of upper extremity related function (p<0.001). The SARA scores were also significantly correlated negatively with ambulation status (p<0.001) and positively with ADL dependency (p<0.001). In the ROC analysis, patients with less than 5.5 points on the SARA had minimal dependency in ADL, while those with more than 23 points showed total dependency.ConclusionSARA corresponds well with gait status and ADL dependency in ataxic stroke patients and is considered to be a useful functional measure in that patient group.
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Project description:Ataxia as the main complaint in a young patient prompts to diagnose neurodegenerative diseases. Not all ataxias are irreversible. We present a video of a patient in the clinic with ataxia diagnosed as subacute combined degeneration of the cord.
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Project description:Background and hypothesisQuantitative acoustic and textual measures derived from speech ("speech features") may provide valuable biomarkers for psychiatric disorders, particularly schizophrenia spectrum disorders (SSD). We sought to identify cross-diagnostic latent factors for speech disturbance with relevance for SSD and computational modeling.Study designClinical ratings for speech disturbance were generated across 14 items for a cross-diagnostic sample (N = 334), including SSD (n = 90). Speech features were quantified using an automated pipeline for brief recorded samples of free speech. Factor models for the clinical ratings were generated using exploratory factor analysis, then tested with confirmatory factor analysis in the cross-diagnostic and SSD groups. The relationships between factor scores and computational speech features were examined for 202 of the participants.Study resultsWe found a 3-factor model with a good fit in the cross-diagnostic group and an acceptable fit for the SSD subsample. The model identifies an impaired expressivity factor and 2 interrelated disorganized factors for inefficient and incoherent speech. Incoherent speech was specific to psychosis groups, while inefficient speech and impaired expressivity showed intermediate effects in people with nonpsychotic disorders. Each of the 3 factors had significant and distinct relationships with speech features, which differed for the cross-diagnostic vs SSD groups.ConclusionsWe report a cross-diagnostic 3-factor model for speech disturbance which is supported by good statistical measures, intuitive, applicable to SSD, and relatable to linguistic theories. It provides a valuable framework for understanding speech disturbance and appropriate targets for modeling with quantitative speech features.
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