Adaptive Filtering Improved Apnea Detection Performance Using Tracheal Sounds in Noisy Environment: A Simulation Study.
Objective. Tracheal sounds were used to detect apnea on various occasions. However, ambient noises can contaminate tracheal sounds which result in poor performance of apnea detection. The objective of this paper was to apply the adaptive filtering (AF) algorithm to improve the quality of tracheal so...
| Published in: | BioMed Research International pp. 1 - 9 |
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| Main Authors: | , , , , |
| Format: | equations & formulas pictorial research tables/charts Journal Article |
| Published: |
Wiley-Blackwell
5/27/2020
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=143456063&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 143456063 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 5/27/2020 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 143456063 143456063 143456063 10.1155/2020/7429345 143456063 ppf: 1 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Adaptive Filtering Improved Apnea Detection Performance Using Tracheal Sounds in Noisy Environment: A Simulation Study. aug: au: Wu, Yanan Liu, Jing He, Baolin Zhang, Xiaotong Yu, Lu affil: Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang, Liaoning, China sug: subj: Algorithms Sleep Apnea Syndromes Diagnosis Trachea Physiology Sound Evaluation Noise Sensitivity and Specificity Human Simulations Transducers Predictive Value of Tests Adolescence Young Adult Adult Body Mass Index kappa Statistic Adolescent: 13-18 years Adult: 19-44 years ab: Objective. Tracheal sounds were used to detect apnea on various occasions. However, ambient noises can contaminate tracheal sounds which result in poor performance of apnea detection. The objective of this paper was to apply the adaptive filtering (AF) algorithm to improve the quality of tracheal sounds and examine the accuracy of the apnea detection algorithm using tracheal sounds after AF. Method. Tracheal sounds were acquired using a primary microphone encased in a plastic bell, and the ambient noises were collected using a reference microphone resting outside the plastic bell in quiet and noisy environments, respectively. Simultaneously, the flow pressure signals and thoracic and abdominal movement were obtained as the standard signals to determine apnea events. Then, the normalized least mean square (NLMS) AF algorithm was applied to the tracheal sounds mixed with noises. Finally, the algorithm of apnea detection was used to the tracheal sounds with AF and the tracheal sounds without AF. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and Cohen's kappa coefficient of apnea detection were calculated. Results. Forty-six healthy subjects, aged 18-35 years and with BMI < 21.4 , were included in the study. The apnea detection performance using tracheal sounds was as follows: in the quiet environment, the tracheal sounds without AF detected apnea with 97.2% sensitivity, 99.9% specificity, 99.8% PPV, 99.4% NPV, 99.5% accuracy, and 0.982 kappa coefficient. The tracheal sounds with AF detected apnea with 98.2% sensitivity, 99.9% specificity, 99.4% PPV, 99.6% NPV, 99.6% accuracy, and 0.985 kappa coefficient. While in the noisy environment, the tracheal sounds without AF detected apnea with 81.1% sensitivity, 96.9% specificity, 85.1% PPV, 96% NPV, 94.2% accuracy, and 0.795 kappa coefficient and the tracheal sounds with AF detected apnea with 91.5% sensitivity, 97.4% specificity, 88.4% PPV, 98.2% NPV, 96.4% accuracy, and 0.877 kappa coefficient. Conclusion. The performance of apnea detection using tracheal sounds with the NLMS AF algorithm in the noisy environment proved to be accurate and reliable. The AF technology could be applied to the respiratory monitoring using tracheal sounds. 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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