Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people
Purpose This study aimed to calculate and analyze the differences in electroencephalogram (EEG) between major depression disorder (MDD) patients and healthy controls using the method of brainwave music to provide evidence of physiological parameters for clinical diagnosis of MDD. Methods We translat...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | Brain-Apparatus Communication |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/27706710.2022.2112535 |
| _version_ | 1797685724160458752 |
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| author | Liang Xi Xi Wang Jiu Ju Wu Dan Quan Wen Xiang Song Yan Ping Tong Yu Xin Dong Wen Tian |
| author_facet | Liang Xi Xi Wang Jiu Ju Wu Dan Quan Wen Xiang Song Yan Ping Tong Yu Xin Dong Wen Tian |
| author_sort | Liang Xi Xi |
| collection | DOAJ |
| description | Purpose This study aimed to calculate and analyze the differences in electroencephalogram (EEG) between major depression disorder (MDD) patients and healthy controls using the method of brainwave music to provide evidence of physiological parameters for clinical diagnosis of MDD. Methods We translated the 5-minute resting EEG data of 20 MDD patients and 20 healthy controls, which were collected by Peking University Sixth Hospital, into brainwave music; and calculated the pitch, volume, duration and corresponding scaling exponents to analyze the differences between MDD patients and healthy people. Then combined the analysis methods of nonlinear dynamics and brain network structure to verify the validity of the proposed method. Results The pitch, volume, and Lemple-Ziv complexity (LZC) in the frontal lobe of MDD patients were higher than those of healthy people. In the central, occipital, and temporal regions of the left hemisphere, the scaling exponents, degrees, and clustering coefficient of MDD patients were lower than those of healthy people (P < 0.05). Conclusions This study has shown that brainwave music analysis can reflect the differences between MDD patients and healthy controls from a new perspective, and these differences may provide a scientific basis for the clinical diagnosis and brainwave music therapy of MDD. |
| first_indexed | 2024-03-12T00:55:26Z |
| format | Article |
| id | doaj.art-b01bc2bf1183494fa7a30ac7d93d1d2b |
| institution | Directory Open Access Journal |
| issn | 2770-6710 |
| language | English |
| last_indexed | 2024-03-12T00:55:26Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Brain-Apparatus Communication |
| spelling | doaj.art-b01bc2bf1183494fa7a30ac7d93d1d2b2023-09-14T13:24:41ZengTaylor & Francis GroupBrain-Apparatus Communication2770-67102022-12-011110712510.1080/27706710.2022.21125352112535Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy peopleLiang Xi Xi0Wang Jiu Ju1Wu Dan2Quan Wen Xiang3Song Yan Ping4Tong Yu Xin5Dong Wen Tian6School of Computer and Information Technology, Beijing JiaoTong UniversityPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental DisordersSchool of Computer and Information Technology, Beijing JiaoTong UniversityPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental DisordersPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental DisordersPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental DisordersPeking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental DisordersPurpose This study aimed to calculate and analyze the differences in electroencephalogram (EEG) between major depression disorder (MDD) patients and healthy controls using the method of brainwave music to provide evidence of physiological parameters for clinical diagnosis of MDD. Methods We translated the 5-minute resting EEG data of 20 MDD patients and 20 healthy controls, which were collected by Peking University Sixth Hospital, into brainwave music; and calculated the pitch, volume, duration and corresponding scaling exponents to analyze the differences between MDD patients and healthy people. Then combined the analysis methods of nonlinear dynamics and brain network structure to verify the validity of the proposed method. Results The pitch, volume, and Lemple-Ziv complexity (LZC) in the frontal lobe of MDD patients were higher than those of healthy people. In the central, occipital, and temporal regions of the left hemisphere, the scaling exponents, degrees, and clustering coefficient of MDD patients were lower than those of healthy people (P < 0.05). Conclusions This study has shown that brainwave music analysis can reflect the differences between MDD patients and healthy controls from a new perspective, and these differences may provide a scientific basis for the clinical diagnosis and brainwave music therapy of MDD.http://dx.doi.org/10.1080/27706710.2022.2112535depressioneegbrainwave musicnonlinear dynamicbrain network |
| spellingShingle | Liang Xi Xi Wang Jiu Ju Wu Dan Quan Wen Xiang Song Yan Ping Tong Yu Xin Dong Wen Tian Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people Brain-Apparatus Communication depression eeg brainwave music nonlinear dynamic brain network |
| title | Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people |
| title_full | Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people |
| title_fullStr | Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people |
| title_full_unstemmed | Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people |
| title_short | Comparative analysis of brainwave music translated from spontaneous EEG between major depression disorders and healthy people |
| title_sort | comparative analysis of brainwave music translated from spontaneous eeg between major depression disorders and healthy people |
| topic | depression eeg brainwave music nonlinear dynamic brain network |
| url | http://dx.doi.org/10.1080/27706710.2022.2112535 |
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