The Evaluation System for the Computer Simulation of the Crackles in Respirations

被引:0
作者
Hsueh, Meng-Lun [1 ]
Wu, Huey-Dong [2 ]
Lu, Bing-Yuh [3 ]
机构
[1] Hwa Hsia Univ Technol, Dept Elect Engn, New Taipei, Taiwan
[2] Natl Taiwan Univ Hosp, Dept Integrated Diagnost & Therapeut, Sect Respirat Therapy, Taipei, Taiwan
[3] Tungnan Univ, Dept Elect Engn, New Taipei, Taiwan
来源
2019 21ST INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION TECHNOLOGY (ICACT): ICT FOR 4TH INDUSTRIAL REVOLUTION | 2019年
关键词
crackle; evaluation system; computer simulation; lung sound; respiration; amplitude modulation; frequency modulation; LUNG SOUNDS; HEART SOUNDS; REDUCTION; NOISE;
D O I
10.23919/icact.2019.8701997
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
The computer synthesized crackles were simulated by 1) respiration signal in the approaching saw tooth wave; 2) modulation (amplitude modulation and frequency modulation); 3) adding noises and pulses of the crackle sources; 4) Butterworth filter; and 5) the output in wave, audio signal and spectrogram. The output of the computer simulations should be examined by the medical doctors. Therefore, an online questionnaire has been created for the evaluation of the computer simulations. The assessment of the computer synthesized crackles is the references to modify the parameters for the computer simulation. Therefore, the better quality of the computer simulation for the crackles will be expected as well as the human-like breaths will be successfully implemented.
引用
收藏
页码:583 / 588
页数:6
相关论文
共 22 条
[1]  
Bohadana A, 2014, NEW ENGL J MED, V370, P2053, DOI [10.1056/NEJMra1302901, 10.1056/NEJMc1403766]
[2]  
Chamberlain D, 2016, IEEE ENG MED BIO, P804, DOI 10.1109/EMBC.2016.7590823
[3]   Using K-Nearest Neighbor Classification to Diagnose Abnormal Lung Sounds [J].
Chen, Chin-Hsing ;
Huang, Wen-Tzeng ;
Tan, Tan-Hsu ;
Chang, Cheng-Chun ;
Chang, Yuan-Jen .
SENSORS, 2015, 15 (06) :13132-13158
[4]   Dacomitinib compared with placebo in pretreated patients with advanced or metastatic non-small-cell lung cancer (NCIC CTG BR.26): a double-blind, randomised, phase 3 trial [J].
Ellis, Peter M. ;
Shepherd, Frances A. ;
Millward, Michael ;
Perrone, Francesco ;
Seymour, Lesley ;
Liu, Geoffrey ;
Sun, Sophie ;
Cho, Byoung Chul ;
Morabito, Alessandro ;
Leighl, Natasha B. ;
Stockler, Martin R. ;
Lee, Christopher W. ;
Wierzbicki, Rafal ;
Cohen, Victor ;
Blais, Normand ;
Sangha, Randeep S. ;
Favaretto, Adolfo G. ;
Kang, Jin Hyoung ;
Tsao, Ming-Sound ;
Wilson, Carolyn F. ;
Goldberg, Zelanna ;
Ding, Keyue ;
Goss, Glenwood D. ;
Bradbury, Penelope Ann .
LANCET ONCOLOGY, 2014, 15 (12) :1379-1388
[5]   MEASUREMENT AND THEORY OF WHEEZING BREATH SOUNDS [J].
GAVRIELY, N ;
PALTI, Y ;
ALROY, G ;
GROTBERG, JB .
JOURNAL OF APPLIED PHYSIOLOGY, 1984, 57 (02) :481-492
[6]   Recursive least squares adaptive noise cancellation filtering for heart sound reduction in lung sounds recordings [J].
Gnitecki, J ;
Moussavi, Z ;
Pasterkamp, H .
PROCEEDINGS OF THE 25TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: A NEW BEGINNING FOR HUMAN HEALTH, 2003, 25 :2416-2419
[7]  
Gogus F.Z., 2015, Int. J. Signal Process. Syst, V3, P106, DOI [10.12720/ijsps.3.2.106-111, DOI 10.12720/IJSPS.3.2.106-111]
[8]   Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: A systematic review and meta-analysis [J].
Gurung, Arati ;
Scrafford, Carolyn G. ;
Tielsch, James M. ;
Levine, Orin S. ;
Check, William .
RESPIRATORY MEDICINE, 2011, 105 (09) :1396-1403
[9]   Adaptive reduction of heart sounds from lung sounds using fourth-order statistics [J].
Hadjileontiadis, LJ ;
Panas, SM .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 1997, 44 (07) :642-648
[10]   Neural classification of lung sounds using wavelet coefficients [J].
Kandaswamy, A ;
Kumar, CS ;
Ramanathan, RP ;
Jayaraman, S ;
Malmurugan, N .
COMPUTERS IN BIOLOGY AND MEDICINE, 2004, 34 (06) :523-537