Suppr超能文献

构音障碍病例中的肺-语音-关节协调评估:一项横断面研究

Pneumo-phono-articulatory coordination assessment in dysarthria cases: a cross-sectional study.

作者信息

Chappaz Rebeca de Oliveira, Barreto Simone Dos Santos, Ortiz Karin Zazo

机构信息

Speech-Language Pathologist, Department of Speech, Language and Hearing Sciences, Escola Paulista de Medicina, Universidade Federal de São Paulo (EPM-UNIFESP), São Paulo (SP), Brazil.

MSc, PhD. Speech-Language Pathologist and Adjunct Professor III, Department of Specific Training in Speech, Language and Hearing Sciences, Instituto de Saúde de Nova Friburgo, Universidade Federal Fluminense (ISNF-UFF), Nova Friburgo (RJ), Brazil.

出版信息

Sao Paulo Med J. 2018 May-Jun;136(3):216-221. doi: 10.1590/1516-3180.2017.0320161217. Epub 2018 Jun 18.

Abstract

BACKGROUND

Pneumo-phono-articulatory coordination is often impaired in dysarthric patients. Because all speech is produced upon exhalation, adequate respiratory support and coordination are essential for communication. Nevertheless, studies investigating respiratory parameters for speech are scarce. The objectives of the present study were to analyze and compare the numbers of words and syllables (universal measurement) per exhalation among healthy and dysarthric speakers, in different speech tasks.

DESIGN AND SETTING

A cross-sectional analytical study with a control group was conducted at the Department of Speech, Language and Hearing Sciences at UNIFESP.

METHODS

The study sample consisted of 62 individuals: 31 dysarthric patients and 31 healthy individuals matched for sex, age and education level. All participants performed number counting and text reading tests in which the numbers of words and syllables per exhalation were recorded. All measurements obtained from the two groups were compared.

RESULTS

Statistically significant differences between the dysarthric and healthy groups were found in the two tasks (counting of syllables and words per exhalation) (P < 0.001). In contrast, the performance of the dysarthric patients did not vary according to the task: reading and number counting in syllables/exhalation (P = 0.821) or words/exhalation (P = 0.785).

CONCLUSIONS

The mean numbers of words and syllables per exhalation among dysarthric subjects did not vary according to the speech task used but they clearly showed differences between dysarthric patients and normal healthy subjects. The study also made it possible to obtain preliminary data on the average numbers of words and syllables per expiration produced by healthy individuals during their speech production.

摘要

背景

构音障碍患者常常存在呼吸-发声-构音协调障碍。由于所有言语都是在呼气时产生的,因此充足的呼吸支持与协调对于交流至关重要。然而,针对言语呼吸参数的研究却很匮乏。本研究的目的是分析并比较健康受试者与构音障碍受试者在不同言语任务中每次呼气时说出的单词数和音节数(通用测量指标)。

设计与地点

在圣保罗联邦大学言语、语言与听力科学系开展了一项设有对照组的横断面分析研究。

方法

研究样本包括62名个体:31名构音障碍患者和31名在性别、年龄和教育水平方面相匹配的健康个体。所有参与者进行了数字计数和文本朗读测试,记录每次呼气时说出的单词数和音节数。对两组获得的所有测量结果进行比较。

结果

在两项任务(每次呼气时的音节计数和单词计数)中,构音障碍组与健康组之间存在统计学显著差异(P < 0.001)。相比之下,构音障碍患者的表现并不因任务而有所不同:音节/呼气(P = 0.821)或单词/呼气(P = 0.785)的朗读和数字计数。

结论

构音障碍受试者每次呼气时的平均单词数和音节数不因所使用的言语任务而变化,但他们与正常健康受试者之间存在明显差异。该研究还使得获取健康个体在言语产生过程中每次呼气时说出的平均单词数和音节数的初步数据成为可能。

相似文献

5
Regularized Speaker Adaptation of KL-HMM for Dysarthric Speech Recognition.正则化说话人自适应 KL-HMM 在构音障碍语音识别中的应用。
IEEE Trans Neural Syst Rehabil Eng. 2017 Sep;25(9):1581-1591. doi: 10.1109/TNSRE.2017.2681691. Epub 2017 Mar 13.
8
Vocal tract representation in the recognition of cerebral palsied speech.声道特征在脑瘫语音识别中的应用。
J Speech Lang Hear Res. 2012 Aug;55(4):1190-207. doi: 10.1044/1092-4388(2011/11-0223). Epub 2012 Jan 23.

本文引用的文献

4
Prevalence of stroke--United States, 2005.2005年美国中风患病率
MMWR Morb Mortal Wkly Rep. 2007 May 18;56(19):469-74.
6
Trends of stroke subtypes mortality in Sao Paulo, Brazil (1996-2003).巴西圣保罗卒中亚型死亡率趋势(1996 - 2003年)
Arq Neuropsiquiatr. 2005 Dec;63(4):951-5. doi: 10.1590/s0004-282x2005000600009. Epub 2005 Dec 15.
10
Speech breathing in Parkinson's disease.帕金森病中的言语呼吸
J Speech Hear Res. 1993 Apr;36(2):294-310. doi: 10.1044/jshr.3602.294.

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验