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SARA-共济失调性言语障碍自动评估的可行性

SARA-Feasibility of automated assessment of ataxic speech disturbance.

作者信息

Grobe-Einsler M, Faber J, Taheri A, Kybelka J, Raue J, Volkening J, Helmhold F, Synofzik M, Klockgether T

机构信息

German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

Department of Neurology, University Hospital Bonn, Bonn, Germany.

出版信息

NPJ Digit Med. 2023 Mar 16;6(1):43. doi: 10.1038/s41746-023-00787-x.

Abstract

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' ratings of speech disturbance according to item 4 of the Scale for Assessment and rating of ataxia (SARA) in 80% of cases. We thereby demonstrate feasibility of computer-assisted voice analysis for automated assessment of severity of speech disturbance.

摘要

共济失调是一组运动障碍,其特征是平衡能力逐渐丧失、协调能力受损和言语障碍,这些共同导致生活质量显著下降。言语障碍通过临床诊断,但缺乏客观评估严重程度的方法。我们使用来自共济失调患者的71组语音记录,开发了一个自动分类系统。该分类系统在±1分的容差范围内,在80%的病例中根据共济失调评估和分级量表(SARA)第4项正确预测了专家对言语障碍的评级。我们由此证明了计算机辅助语音分析用于自动评估言语障碍严重程度的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9244/10020430/d4ea97eef2cf/41746_2023_787_Fig1_HTML.jpg

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