A Multi-Center Clinical Trial for Wireless Stethoscope-Based Diagnosis and Prognosis of Children Community-Acquired Pneumonia
Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In th...
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| Published in | IEEE transactions on biomedical engineering Vol. 70; no. 7; pp. 2215 - 2226 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
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United States
IEEE
01.07.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| Online Access | Get full text |
| ISSN | 0018-9294 1558-2531 1558-2531 |
| DOI | 10.1109/TBME.2023.3239372 |
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| Abstract | Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In this paper, we carried out a multi-center clinical trial in four hospitals to investigate the feasibility of using a wireless stethoscope for children CAP diagnosis and prognosis. The trial collects both the left and right lung sounds from children with CAP at the time of diagnosis, improvement, and recovery. A bilateral pulmonary audio-auxiliary model (BPAM) is proposed for lung sound analysis. It learns the underlying pathological paradigm for the CAP classification by mining the contextual information of audio while preserving the structured information of breathing cycle. The clinical validation shows that the specificity and sensitivity of BPAM are over 92% in both the CAP diagnosis and prognosis for the subject-dependent experiment, over 50% in CAP diagnosis and 39% in CAP prognosis for the subject-independent experiment. Almost all benchmarked methods have improved performance by fusing left and right lung sounds, indicating the direction of hardware design and algorithmic improvement. |
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| AbstractList | Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In this paper, we carried out a multi-center clinical trial in four hospitals to investigate the feasibility of using a wireless stethoscope for children CAP diagnosis and prognosis. The trial collects both the left and right lung sounds from children with CAP at the time of diagnosis, improvement, and recovery. A bilateral pulmonary audio-auxiliary model (BPAM) is proposed for lung sound analysis. It learns the underlying pathological paradigm for the CAP classification by mining the contextual information of audio while preserving the structured information of breathing cycle. The clinical validation shows that the specificity and sensitivity of BPAM are over 92% in both the CAP diagnosis and prognosis for the subject-dependent experiment, over 50% in CAP diagnosis and 39% in CAP prognosis for the subject-independent experiment. Almost all benchmarked methods have improved performance by fusing left and right lung sounds, indicating the direction of hardware design and algorithmic improvement. Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In this paper, we carried out a multi-center clinical trial in four hospitals to investigate the feasibility of using a wireless stethoscope for children CAP diagnosis and prognosis. The trial collects both the left and right lung sounds from children with CAP at the time of diagnosis, improvement, and recovery. A bilateral pulmonary audio-auxiliary model (BPAM) is proposed for lung sound analysis. It learns the underlying pathological paradigm for the CAP classification by mining the contextual information of audio while preserving the structured information of breathing cycle. The clinical validation shows that the specificity and sensitivity of BPAM are over 92% in both the CAP diagnosis and prognosis for the subject-dependent experiment, over 50% in CAP diagnosis and 39% in CAP prognosis for the subject-independent experiment. Almost all benchmarked methods have improved performance by fusing left and right lung sounds, indicating the direction of hardware design and algorithmic improvement.Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In this paper, we carried out a multi-center clinical trial in four hospitals to investigate the feasibility of using a wireless stethoscope for children CAP diagnosis and prognosis. The trial collects both the left and right lung sounds from children with CAP at the time of diagnosis, improvement, and recovery. A bilateral pulmonary audio-auxiliary model (BPAM) is proposed for lung sound analysis. It learns the underlying pathological paradigm for the CAP classification by mining the contextual information of audio while preserving the structured information of breathing cycle. The clinical validation shows that the specificity and sensitivity of BPAM are over 92% in both the CAP diagnosis and prognosis for the subject-dependent experiment, over 50% in CAP diagnosis and 39% in CAP prognosis for the subject-independent experiment. Almost all benchmarked methods have improved performance by fusing left and right lung sounds, indicating the direction of hardware design and algorithmic improvement. |
| Author | Wang, Lingwei Huang, Dongmin Wang, Wenjin |
| Author_xml | – sequence: 1 givenname: Dongmin surname: Huang fullname: Huang, Dongmin organization: Department of Biomedical Engineering, Southern University of Science and Technology, China – sequence: 2 givenname: Lingwei surname: Wang fullname: Wang, Lingwei organization: Department of Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, China – sequence: 3 givenname: Wenjin orcidid: 0000-0001-7832-5444 surname: Wang fullname: Wang, Wenjin email: wangwj3@sustech.edu.cn organization: Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China |
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| SubjectTerms | Audio data Child Children Clinical trials Community-acquired pneumonia Diagnosis Hospitals Humans Lung lung sound analysis Lungs machine learning Medical instruments Monitoring methods Pediatrics Pneumonia Pneumonia - diagnosis Pneumonia - pathology Prognosis Prognostics and health management Respiratory Sounds - diagnosis Stethoscope Stethoscopes Tachypnea Wireless communication |
| Title | A Multi-Center Clinical Trial for Wireless Stethoscope-Based Diagnosis and Prognosis of Children Community-Acquired Pneumonia |
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