Cargando…
Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks
Dysarthria may present during the natural course of many degenerative neurological conditions. Hypokinetic and ataxic dysarthria are common in movement disorders and represent the underlying neuropathology. We developed an artificial intelligence (AI) model to distinguish ataxic dysarthria and hypok...
Autores principales: | , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165837/ https://www.ncbi.nlm.nih.gov/pubmed/35658000 http://dx.doi.org/10.1371/journal.pone.0268337 |
_version_ | 1784720476170354688 |
---|---|
author | Song, Joomee Lee, Ju Hwan Choi, Jungeun Suh, Mee Kyung Chung, Myung Jin Kim, Young Hun Park, Jeongho Choo, Seung Ho Son, Ji Hyun Lee, Dong Yeong Ahn, Jong Hyeon Youn, Jinyoung Kim, Kyung-Su Cho, Jin Whan |
author_facet | Song, Joomee Lee, Ju Hwan Choi, Jungeun Suh, Mee Kyung Chung, Myung Jin Kim, Young Hun Park, Jeongho Choo, Seung Ho Son, Ji Hyun Lee, Dong Yeong Ahn, Jong Hyeon Youn, Jinyoung Kim, Kyung-Su Cho, Jin Whan |
author_sort | Song, Joomee |
collection | PubMed |
description | Dysarthria may present during the natural course of many degenerative neurological conditions. Hypokinetic and ataxic dysarthria are common in movement disorders and represent the underlying neuropathology. We developed an artificial intelligence (AI) model to distinguish ataxic dysarthria and hypokinetic dysarthria from normal speech and differentiate ataxic and hypokinetic speech in parkinsonian diseases and cerebellar ataxia. We screened 804 perceptual speech analyses performed in the Samsung Medical Center Neurology Department between January 2017 and December 2020. The data of patients diagnosed with parkinsonian disorders or cerebellar ataxia were included. Two speech tasks (numbering from 1 to 50 and reading nine sentences) were analyzed. We adopted convolutional neural networks and developed a patch-wise wave splitting and integrating AI system for audio classification (PWSI-AI-AC) to differentiate between ataxic and hypokinetic speech. Of the 395 speech recordings for the reading task, 76, 112, and 207 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. Of the 409 recordings of the numbering task, 82, 111, and 216 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. The reading and numbering task recordings were classified with 5-fold cross-validation using PWSI-AI-AC as follows: hypokinetic dysarthria vs. others (area under the curve: 0.92 ± 0.01 and 0.92 ± 0.02), ataxia vs. others (0.93 ± 0.04 and 0.89 ± 0.02), hypokinetic dysarthria vs. ataxia (0.96 ± 0.02 and 0.95 ± 0.01), hypokinetic dysarthria vs. none (0.86 ± 0.03 and 0.87 ± 0.05), and ataxia vs. none (0.87 ± 0.07 and 0.87 ± 0.09), respectively. PWSI-AI-AC showed reliable performance in differentiating ataxic and hypokinetic dysarthria and effectively augmented data to classify the types even with limited training samples. The proposed fully automatic AI system outperforms neurology residents. Our model can provide effective guidelines for screening related diseases and differential diagnosis of neurodegenerative diseases. |
format | Online Article Text |
id | pubmed-9165837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-91658372022-06-05 Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks Song, Joomee Lee, Ju Hwan Choi, Jungeun Suh, Mee Kyung Chung, Myung Jin Kim, Young Hun Park, Jeongho Choo, Seung Ho Son, Ji Hyun Lee, Dong Yeong Ahn, Jong Hyeon Youn, Jinyoung Kim, Kyung-Su Cho, Jin Whan PLoS One Research Article Dysarthria may present during the natural course of many degenerative neurological conditions. Hypokinetic and ataxic dysarthria are common in movement disorders and represent the underlying neuropathology. We developed an artificial intelligence (AI) model to distinguish ataxic dysarthria and hypokinetic dysarthria from normal speech and differentiate ataxic and hypokinetic speech in parkinsonian diseases and cerebellar ataxia. We screened 804 perceptual speech analyses performed in the Samsung Medical Center Neurology Department between January 2017 and December 2020. The data of patients diagnosed with parkinsonian disorders or cerebellar ataxia were included. Two speech tasks (numbering from 1 to 50 and reading nine sentences) were analyzed. We adopted convolutional neural networks and developed a patch-wise wave splitting and integrating AI system for audio classification (PWSI-AI-AC) to differentiate between ataxic and hypokinetic speech. Of the 395 speech recordings for the reading task, 76, 112, and 207 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. Of the 409 recordings of the numbering task, 82, 111, and 216 were from normal, ataxic dysarthria, and hypokinetic dysarthria subjects, respectively. The reading and numbering task recordings were classified with 5-fold cross-validation using PWSI-AI-AC as follows: hypokinetic dysarthria vs. others (area under the curve: 0.92 ± 0.01 and 0.92 ± 0.02), ataxia vs. others (0.93 ± 0.04 and 0.89 ± 0.02), hypokinetic dysarthria vs. ataxia (0.96 ± 0.02 and 0.95 ± 0.01), hypokinetic dysarthria vs. none (0.86 ± 0.03 and 0.87 ± 0.05), and ataxia vs. none (0.87 ± 0.07 and 0.87 ± 0.09), respectively. PWSI-AI-AC showed reliable performance in differentiating ataxic and hypokinetic dysarthria and effectively augmented data to classify the types even with limited training samples. The proposed fully automatic AI system outperforms neurology residents. Our model can provide effective guidelines for screening related diseases and differential diagnosis of neurodegenerative diseases. Public Library of Science 2022-06-03 /pmc/articles/PMC9165837/ /pubmed/35658000 http://dx.doi.org/10.1371/journal.pone.0268337 Text en © 2022 Song et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Song, Joomee Lee, Ju Hwan Choi, Jungeun Suh, Mee Kyung Chung, Myung Jin Kim, Young Hun Park, Jeongho Choo, Seung Ho Son, Ji Hyun Lee, Dong Yeong Ahn, Jong Hyeon Youn, Jinyoung Kim, Kyung-Su Cho, Jin Whan Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title | Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title_full | Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title_fullStr | Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title_full_unstemmed | Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title_short | Detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
title_sort | detection and differentiation of ataxic and hypokinetic dysarthria in cerebellar ataxia and parkinsonian disorders via wave splitting and integrating neural networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165837/ https://www.ncbi.nlm.nih.gov/pubmed/35658000 http://dx.doi.org/10.1371/journal.pone.0268337 |
work_keys_str_mv | AT songjoomee detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT leejuhwan detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT choijungeun detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT suhmeekyung detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT chungmyungjin detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT kimyounghun detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT parkjeongho detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT chooseungho detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT sonjihyun detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT leedongyeong detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT ahnjonghyeon detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT younjinyoung detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT kimkyungsu detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks AT chojinwhan detectionanddifferentiationofataxicandhypokineticdysarthriaincerebellarataxiaandparkinsoniandisordersviawavesplittingandintegratingneuralnetworks |