Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales
IntroductionStroke is usually accompanied by a range of complications, like post-stroke motor disorders. So far, its evaluation of motor function is developed on clinical scales, such as Fugl-Meyer Assessment (FMA), Instrumental Activities of Daily Living (IADL), etc. These scale results from behavi...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-11-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2022.1032696/full |
| _version_ | 1828187344684974080 |
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| author | Zhongpeng Wang Zhongpeng Wang Zhaoyang Liu Long Chen Shuang Liu Minpeng Xu Minpeng Xu Minpeng Xu Feng He Feng He Feng He Dong Ming Dong Ming Dong Ming |
| author_facet | Zhongpeng Wang Zhongpeng Wang Zhaoyang Liu Long Chen Shuang Liu Minpeng Xu Minpeng Xu Minpeng Xu Feng He Feng He Feng He Dong Ming Dong Ming Dong Ming |
| author_sort | Zhongpeng Wang |
| collection | DOAJ |
| description | IntroductionStroke is usually accompanied by a range of complications, like post-stroke motor disorders. So far, its evaluation of motor function is developed on clinical scales, such as Fugl-Meyer Assessment (FMA), Instrumental Activities of Daily Living (IADL), etc. These scale results from behavior and kinematic assessment are inevitably influenced by subjective factors, like the experience of patients and doctors, lacking neurological correlations and evidence.MethodsThis paper applied a microstate model based on modified k-means clustering to analyze 64-channel electroencephalogram (EEG) from 12 stroke patients and 12 healthy volunteers, respectively, to explore the feasibility of applying microstate analysis to stroke patients. We aimed at finding some possible differences between stroke and healthy individuals in resting-state EEG microstate features. We further explored the correlations between EEG microstate features and scales within the stroke group.Results and discussionBy statistical analysis, we obtained significant differences in EEG microstate features between the stroke and healthy groups and significant correlations between microstate features and scales within the stroke group. These results might provide some neurological evidence and correlations in the perspective of EEG microstate analysis for post-stroke rehabilitation and evaluation of motor disorders. Our work suggests that microstate analysis of resting-state EEG is a promising method to assist clinical and assessment applications. |
| first_indexed | 2024-04-12T07:34:32Z |
| format | Article |
| id | doaj.art-55866c06402648daada3a210e6085f22 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-04-12T07:34:32Z |
| publishDate | 2022-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-55866c06402648daada3a210e6085f222022-12-22T03:41:58ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2022-11-011610.3389/fnins.2022.10326961032696Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scalesZhongpeng Wang0Zhongpeng Wang1Zhaoyang Liu2Long Chen3Shuang Liu4Minpeng Xu5Minpeng Xu6Minpeng Xu7Feng He8Feng He9Feng He10Dong Ming11Dong Ming12Dong Ming13Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaTianjin International Joint Research Center for Neural Engineering, Tianjin, ChinaDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaTianjin International Joint Research Center for Neural Engineering, Tianjin, ChinaDepartment of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, ChinaAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, ChinaTianjin International Joint Research Center for Neural Engineering, Tianjin, ChinaIntroductionStroke is usually accompanied by a range of complications, like post-stroke motor disorders. So far, its evaluation of motor function is developed on clinical scales, such as Fugl-Meyer Assessment (FMA), Instrumental Activities of Daily Living (IADL), etc. These scale results from behavior and kinematic assessment are inevitably influenced by subjective factors, like the experience of patients and doctors, lacking neurological correlations and evidence.MethodsThis paper applied a microstate model based on modified k-means clustering to analyze 64-channel electroencephalogram (EEG) from 12 stroke patients and 12 healthy volunteers, respectively, to explore the feasibility of applying microstate analysis to stroke patients. We aimed at finding some possible differences between stroke and healthy individuals in resting-state EEG microstate features. We further explored the correlations between EEG microstate features and scales within the stroke group.Results and discussionBy statistical analysis, we obtained significant differences in EEG microstate features between the stroke and healthy groups and significant correlations between microstate features and scales within the stroke group. These results might provide some neurological evidence and correlations in the perspective of EEG microstate analysis for post-stroke rehabilitation and evaluation of motor disorders. Our work suggests that microstate analysis of resting-state EEG is a promising method to assist clinical and assessment applications.https://www.frontiersin.org/articles/10.3389/fnins.2022.1032696/fullresting-state EEGmicrostate analysispost-strokerehabilitation assessmentclinical scales |
| spellingShingle | Zhongpeng Wang Zhongpeng Wang Zhaoyang Liu Long Chen Shuang Liu Minpeng Xu Minpeng Xu Minpeng Xu Feng He Feng He Feng He Dong Ming Dong Ming Dong Ming Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales Frontiers in Neuroscience resting-state EEG microstate analysis post-stroke rehabilitation assessment clinical scales |
| title | Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales |
| title_full | Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales |
| title_fullStr | Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales |
| title_full_unstemmed | Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales |
| title_short | Resting-state electroencephalogram microstate to evaluate post-stroke rehabilitation and associate with clinical scales |
| title_sort | resting state electroencephalogram microstate to evaluate post stroke rehabilitation and associate with clinical scales |
| topic | resting-state EEG microstate analysis post-stroke rehabilitation assessment clinical scales |
| url | https://www.frontiersin.org/articles/10.3389/fnins.2022.1032696/full |
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