Automatic Lung Health Screening Using Respiratory Sounds.
Significant changes have been made on audio-based technologies over years in several different fields. Healthcare is no exception. One of such avenues is health screening based on respiratory sounds. In this paper, we developed a tool to detect respiratory sounds that come from respiratory infection...
| Publicado en: | Journal of Medical Systems Vol. 45; no. 2; pp. 1 - 10 |
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| Autores principales: | , , , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=148904076&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 148904076 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: 2021 vid: 45 iid: 2 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 148904076 148904076 148904076 10.1007/s10916-020-01681-9 148904076 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Automatic Lung Health Screening Using Respiratory Sounds. aug: au: Mukherjee, Himadri Sreerama, Priyanka Dhar, Ankita Obaidullah, Sk. Md. Roy, Kaushik Mahmud, Mufti Santosh, K.C. affil: Department of Computer Science, West Bengal State University, Kolkata, India sug: subj: Lung Diseases Diagnosis Health Screening Respiratory Sounds Physiopathology Instrument Construction Respiratory Tract Infections Human Comparative Studies Descriptive Statistics False Positive Results Intraclass Correlation Coefficient ab: Significant changes have been made on audio-based technologies over years in several different fields. Healthcare is no exception. One of such avenues is health screening based on respiratory sounds. In this paper, we developed a tool to detect respiratory sounds that come from respiratory infection carrying patients. Linear Predictive Cepstral Coefficient (LPCC)-based features were used to characterize such audio clips. With Multilayer Perceptron (MLP)-based classifier, in our experiment, we achieved the highest possible accuracy of 99.22% that was tested on a publicly available respiratory sounds dataset (ICBHI17) (Rocha et al. Physiol. Meas. 40(3):035,001 20) of size 6800+ clips. In addition to other popular machine learning classifiers, our results outperformed common works that exist in the literature. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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