A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring
Acoustical analysis of snoring provides a new approach for the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS). A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. The acoustical features of snoring wer...
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| Format: | Article |
| Language: | English |
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Institute of Fundamental Technological Research Polish Academy of Sciences
2020-02-01
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| Series: | Archives of Acoustics |
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| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/2459 |
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| author | Can WANG Jianxin PENG Xiaowen ZHANG |
| author_facet | Can WANG Jianxin PENG Xiaowen ZHANG |
| author_sort | Can WANG |
| collection | DOAJ |
| description | Acoustical analysis of snoring provides a new approach for the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS). A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. The acoustical features of snoring were extracted from a full night’s recording of 6 OSAHS patients, and regular snoring sounds and snoring sounds related to respiratory disorder events were classified using a support vector machine (SVM)
method. The mean recognition rate for simple snoring sounds and snoring sounds related to respiratory disorder events is more than 91.14% by using the grid search, a genetic algorithm and particle swarm optimization methods. The predicted AHI from the present study has a high correlation with the AHI from polysomnography and the correlation coefficient is 0.976. These results demonstrate that the proposed method can classify the snoring sounds of OSAHS patients and can be used to provide guidance for diagnosis of OSAHS. |
| format | Article |
| id | doaj-art-4e9e40dccaaa4417bb5b8edfe090a7c6 |
| institution | Kabale University |
| issn | 0137-5075 2300-262X |
| language | English |
| publishDate | 2020-02-01 |
| publisher | Institute of Fundamental Technological Research Polish Academy of Sciences |
| record_format | Article |
| series | Archives of Acoustics |
| spelling | doaj-art-4e9e40dccaaa4417bb5b8edfe090a7c62025-08-20T03:33:35ZengInstitute of Fundamental Technological Research Polish Academy of SciencesArchives of Acoustics0137-50752300-262X2020-02-0145110.24425/aoa.2020.132490A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of SnoringCan WANG0Jianxin PENG1Xiaowen ZHANG2South China University of TechnologySouth China University of TechnologyGuangzhou Medical UniversityAcoustical analysis of snoring provides a new approach for the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS). A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. The acoustical features of snoring were extracted from a full night’s recording of 6 OSAHS patients, and regular snoring sounds and snoring sounds related to respiratory disorder events were classified using a support vector machine (SVM) method. The mean recognition rate for simple snoring sounds and snoring sounds related to respiratory disorder events is more than 91.14% by using the grid search, a genetic algorithm and particle swarm optimization methods. The predicted AHI from the present study has a high correlation with the AHI from polysomnography and the correlation coefficient is 0.976. These results demonstrate that the proposed method can classify the snoring sounds of OSAHS patients and can be used to provide guidance for diagnosis of OSAHS.https://acoustics.ippt.pan.pl/index.php/aa/article/view/2459acoustical analysisfeature extractionsupport vector machinesnoring sound |
| spellingShingle | Can WANG Jianxin PENG Xiaowen ZHANG A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring Archives of Acoustics acoustical analysis feature extraction support vector machine snoring sound |
| title | A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring |
| title_full | A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring |
| title_fullStr | A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring |
| title_full_unstemmed | A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring |
| title_short | A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring |
| title_sort | classification method related to respiratory disorder events based on acoustical analysis of snoring |
| topic | acoustical analysis feature extraction support vector machine snoring sound |
| url | https://acoustics.ippt.pan.pl/index.php/aa/article/view/2459 |
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