Wheeze sound analysis using computer-based techniques: a systematic review

References

[1] Alic A, Lackovic I, Bilas V, Sersic D, Magjarevic R. A novel approach to wheeze detection. IFMBE Conf Proc 2007: 963–966.10.1007/978-3-540-36841-0_229Search in Google Scholar

[2] Bahoura M. Pattern recognition methods applied to respiratory sounds classification into normal and wheeze classes. Comput Biol Med 2009; 39: 824–843.10.1016/j.compbiomed.2009.06.011Search in Google Scholar PubMed

[3] Bahoura M, Pelletier C. New parameters for respiratory sound classification. IEEE CCECE Conf Proc 2003: 1457–1460.10.1109/CCECE.2003.1226178Search in Google Scholar

[4] Bahoura M, Pelletier C. Respiratory sounds classification using cepstral analysis and Gaussian mixture models. IEEE IEMBS Conf Proc 2004: 9–12.10.1109/IEMBS.2004.1403077Search in Google Scholar PubMed

[5] Bahoura M, Pelletier C. Respiratory sounds classification using gaussian mixture models. IEEE CCECE Conf Proc 2004: 1309–1312.10.1109/CCECE.2004.1349639Search in Google Scholar

[6] Bokov P, Mahut B, Flaud P, Delclaux C. Wheezing recognition algorithm using recordings of respiratory sounds at the mouth in a pediatric population. Comput Biol Med 2016; 70: 40–50.10.1016/j.compbiomed.2016.01.002Search in Google Scholar PubMed

[7] Bor-Shing L, Bor-Shys L. Automatic wheezing detection using speech recognition technique. J Med Biol Eng 2016; 36: 545–554.10.1007/s40846-016-0161-9Search in Google Scholar

[8] Bor-Shing L, Huey-Dong W, Sao-Jie C. Automatic wheezing detection based on signal processing of spectrogram and back-propagation neural network. J HealthC Eng 2015; 6: 649–672.10.1260/2040-2295.6.4.649Search in Google Scholar PubMed

[9] Charbonneau G, Ademovic E, Cheetham BMG, et al. Basic techniques for respiratory sound analysis. Eur Respir Rev 2000; 10: 625–635.Search in Google Scholar

[10] Chen C-H, Huang W-T, Tan T-H, Chang C-C, Chang Y-J. Using k-nearest neighbor classification to diagnose abnormal lung sounds. Sensors 2015; 15: 13132–13158.10.3390/s150613132Search in Google Scholar PubMed PubMed Central

[11] Chronic obstruction pulmonary disease (COPD) [http://www.who.int/mediacentre/factsheets/fs315/en/] (Accessed on 29 October, 2016).Search in Google Scholar

[12] Chronic respiratory diseases [http://www.who.int/respiratory/asthma/en/] (Accessed on 29 October, 2016).Search in Google Scholar

[13] Earis JE, Cheetham BMG. Current methods used for computerized respiratory sound analysis. Eur Respir Rev 2000; 10: 586–590.Search in Google Scholar

[14] Emrani S, Gentimis T, Krim H. Persistent homology of delay embeddings and its application to wheeze detection. IEEE Signal Proc Let 2014; 21: 459–463.10.1109/LSP.2014.2305700Search in Google Scholar

[15] Emrani S, Chintakunta H, Krim H. Real time detection of harmonic structure: a case for topological signal analysis. IEEE ICASSP Conf Proc 2014: 3445–3449.10.1109/ICASSP.2014.6854240Search in Google Scholar

[16] Fenton TR, Pasterkamp H, Tal A, Chernick V. Automated spectral characterization of wheezing in asthmatic children. IEEE T Bio-Med Eng 1985; 32: 50–55.10.1109/TBME.1985.325616Search in Google Scholar PubMed

[17] Fiz JA, Jané R, Salvatella D, et al. Analysis of tracheal sounds during forced exhalation in asthma patients and normal subjects: bronchodilator response effect. Chest 1999; 116: 633–638.10.1378/chest.116.3.633Search in Google Scholar PubMed

[18] Fiz JA, Jané R, Homs A, et al. Detection of wheezing during maximal forced exhalation in patients with obstructed airways. Chest 2002; 122: 186–191.10.1378/chest.122.1.186Search in Google Scholar PubMed

[19] Fiz JA, Jané R, Lozano M, Gómez R, Ruiz J. Detecting unilateral phrenic paralysis by acoustic respiratory analysis. PLoS One 2014; 9: e93595.10.1371/journal.pone.0093595Search in Google Scholar PubMed PubMed Central

[20] Gross V, Dittmar A, Penzel T, Schuttler F, Von Wichert P. The relationship between normal lung sounds, age, and gender. Am J Resp Crit Care 2000; 162: 905–909.10.1164/ajrccm.162.3.9905104Search in Google Scholar PubMed

[21] Gross V, Hadjileontiadis L, Penzel T, Koehler U, Vogelmeier C. Multimedia database “Marburg Respiratory Sounds (MARS)”. IEEE EMBS Conf Proc 2003: 456–457.10.1109/IEMBS.2003.1279717Search in Google Scholar

[22] Gurung A, Scrafford CG, Tielsch JM, Levine OS, Checkley W. Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: A systematic review and meta-analysis. Resp Med 2011; 105: 1396–1403.10.1016/j.rmed.2011.05.007Search in Google Scholar PubMed PubMed Central

[23] Homs-Corbera A, Fiz JA, Morera J, Jané R. Time-frequency detection and analysis of wheezes during forced exhalation. IEEE T Bio-Med Eng 2004; 51: 182–186.10.1109/TBME.2003.820359Search in Google Scholar PubMed

[24] Jácome C, Marques A. Computerized respiratory sounds in patients with COPD: a systematic review. COPD 2015; 12: 104–112.10.3109/15412555.2014.908832Search in Google Scholar PubMed

[25] Jin F, Krishnan S, Sattar F. Adventitious sounds identification and extraction using temporal-spectral dominance-based features. IEEE T Bio-Med Eng 2011; 58: 3078–3087.10.1109/TBME.2011.2160721Search in Google Scholar

[26] Kraman SS, Wodicka GR, Oh Y, Pasterkamp H. Measurement of respiratory acoustic signals: effect of microphone air cavity width, shape, and venting. Chest 1995; 108: 1004–1008.10.1378/chest.108.4.1004Search in Google Scholar PubMed

[27] Li S-H, Lin B-S, Tsai C-H, Yang C-T, Lin B-S. Design of wearable breathing sound monitoring system for real-time wheeze detection. Sensors 2017; 17:171.10.3390/s17010171Search in Google Scholar

[28] Lin B-S, Yen T-S. An FPGA-based rapid wheezing detection system. Int J Env Res Pub He 2014; 11: 1573–1593.10.3390/ijerph110201573Search in Google Scholar

[29] Lozano M, Fiz J, Jané R. Automatic differentiation of normal and continuous adventitious respiratory sounds using ensemble empirical mode decomposition and instantaneous frequency. IEEE J Biomed Health 2016; 20: 486–497.10.1109/JBHI.2015.2396636Search in Google Scholar

[30] Lozano M, Fiz JA, Jané R. Performance evaluation of the Hilbert-Huang transform for respiratory sound analysis and its application to continuous adventitious sound characterization. Signal Process 2016; 120: 99–116.10.1016/j.sigpro.2015.09.005Search in Google Scholar

[31] Mazić I, Sovilj S, Magjarevic R. Analysis of respiratory sounds in asthmatic infants. Meas Sci Rev 2003; 3: 9–12.Search in Google Scholar

[32] Mazić I, Bonković M, Džaja B. Two-level coarse-to-fine classification algorithm for asthma wheezing recognition in children’s respiratory sounds. Biomed Signal Proces 2015; 21: 105–118.10.1016/j.bspc.2015.05.002Search in Google Scholar

[33] Meslier N, Charbonneau G, Racineux JL. Wheezes. Eur Respir J 1995; 8: 1942–1948.10.1183/09031936.95.08111942Search in Google Scholar PubMed

[34] National Asthma Education and Prevention Program – Guidelines for the Diagnosis and Management of Asthma (NAEPP National Asthma Education and Prevention Program) [http://www.nhlbi.nih.gov/guidelines/asthma/asthgdln.pdf].Search in Google Scholar

[35] Naves R, Barbosa BHG, Ferreira DD. Classification of lung sounds using higher-order statistics: a divide-and-conquer approach. Comput Meth Prog Bio 2016; 129: 12–20.10.1016/j.cmpb.2016.02.013Search in Google Scholar

[36] Oud M. Classification and recognition of asthmatic breathing sounds. EEAN Conf Proc 1996: 414–418.Search in Google Scholar

[37] Oud M. Lung function interpolation by means of neural-network-supported analysis of respiration sounds. Med Eng Phys 2003; 25: 309–316.10.1016/S1350-4533(02)00198-4Search in Google Scholar PubMed

[38] Oud M, Dooijes EH. Automated breath sound analysis. IEMBS Conf Proc 1996: 990–992.10.1109/IEMBS.1996.652675Search in Google Scholar

[39] Oud M, Dooijes EH, Van der Veen MJ. Classification of asthmatic lung sound spectra. IFMBE Conf Proc 1998: 440–448.Search in Google Scholar

[40] Oud M, Dooijes EH, Van der Zee JS. Asthmatic airways obstruction assessment based on detailed analysis of respiratory sound spectra. IEEE T BioMed Eng 2000; 47: 1450–1455.10.1109/10.880096Search in Google Scholar PubMed

[41] Palaniappan R, Sundaraj K, Ahamed NU, Arjunan A, Sundaraj S. Computer-based respiratory sound analysis: a systematic review. IETE Tech Rev 2013; 30: 248–256.10.4103/0256-4602.113524Search in Google Scholar

[42] Palaniappan R, Sundaraj K, Ahamed NU. Machine learning in lung sound analysis: a systematic review. Biocybern Biomed Eng 2013; 33: 129–135.10.1016/j.bbe.2013.07.001Search in Google Scholar

[43] Palaniappan R, Sundaraj K, Sundaraj S. Artificial intelligence techniques used in respiratory sound analysis – a systematic review. Biomed Eng-Biomed TE 2014; 59: 7–18.10.1515/bmt-2013-0074Search in Google Scholar PubMed

[44] Palaniappan R, Sundaraj K, Sundaraj S. Adaptive neuro-fuzzy inference system for breath phase detection and breath cycle segmentation. Comput Meth Prog Bio 2017; 145: 67–72.10.1016/j.cmpb.2017.04.013Search in Google Scholar PubMed

[45] Pasterkamp H, Kraman SS, DeFrain PD, Wodicka GR. Measurement of respiratory acoustical signals: comparison of sensors. Chest 1993; 104: 1518–1526.10.1378/chest.104.5.1518Search in Google Scholar PubMed

[46] Pneumonia [http://www.who.int/mediacentre/factsheets/fs331/en/] (Accessed on 29 October, 2016).Search in Google Scholar

[47] Pramono RXA, Bowyer S, Rodriguez-Villegas E. Automatic adventitious respiratory sound analysis: a systematic review. PLoS One 2017; 12: e0177926.10.1371/journal.pone.0177926Search in Google Scholar PubMed PubMed Central

[48] Qiu Y, Whittaker AR, Lucas M, Anderson K. Automatic wheeze detection based on auditory modelling. Proc Inst Mech Eng H 2005; 219: 219–227.10.1243/095441105X28551Search in Google Scholar PubMed

[49] Riella RJ, Nohama P, Maia JM. Method for automatic detection of wheezing in lung sounds. Braz J Med Biol Res 2009; 42: 674–684.10.1590/S0100-879X2009000700013Search in Google Scholar PubMed

[50] Rietveld S, Oud M, Dooijes EH. Classification of asthmatic breath sounds: preliminary results of the classifying capacity of human examiners versus artificial neural networks. Comput Biomed Res 1999; 32: 440–448.10.1006/cbmr.1999.1522Search in Google Scholar PubMed

[51] Rossi M, Sovijärvi ARA, Piirilä P, et al. Environmental and subject conditions and breathing manoeuvres for respiratory sound recordings. Eur Respir Rev 2000; 10: 611–615.Search in Google Scholar

[52] Sengupta N, Sahidullah Md, Saha G. Lung sound classification using cepstral-based statistical features. Comput Biol Med 2016; 75: 118–129.10.1016/j.compbiomed.2016.05.013Search in Google Scholar PubMed

[53] Shabtai-Musih Y, Grotberg JB, Gavriely N. Spectral content of forced expiratory wheezes during air, He, and SF6 breathing in normal humans. J Appl Physiol 1992; 72: 629–635.10.1152/jappl.1992.72.2.629Search in Google Scholar PubMed

[54] Sokolovsky V, Furman G, Malinin S, Yakovleva E, Furman E. Computer-assisted assay of respiratory sounds of children suffering from bronchial asthma. M Tech Med 2014; 6: 83–87.Search in Google Scholar

[55] Sovijärvi ARA, Malmberg LP, Charbonneau G, et al. Characteristics of breath sounds and adventitious respiratory sounds. Eur Respir Rev 2000; 10: 591–596.Search in Google Scholar

[56] Styliani A. Taplidou LJH, Ilias K. Kitsas, Konstantinos I. Panoulas. On applying continuous wavelet transform in wheeze analysis. IEEE EMBS Conf Proc 2004: 3832–3835.Search in Google Scholar

[57] Taplidou SA, Hadjileontiadis LJ. Nonlinear analysis of wheezes using wavelet bicoherence. Comput Biol Med 2007; 37: 563–570.10.1016/j.compbiomed.2006.08.007Search in Google Scholar PubMed

[58] Taplidou SA, Hadjileontiadis LJ. Wheeze detection based on time-frequency analysis of breath sounds. Comput Biol Med 2007; 37: 1073–1083.10.1016/j.compbiomed.2006.09.007Search in Google Scholar PubMed

[59] Taplidou SA, Hadjileontiadis LJ. Analysis of wheezes using wavelet higher order spectral features. IEEE T Bio-Med Eng 2010; 57: 1596–1610.10.1109/TBME.2010.2041777Search in Google Scholar PubMed

[60] Taplidou SA, Hadjileontiadis LJ, Penzel T, Gross V, Panas SM. WED: an efficient wheezing-episode detector based on breath sounds spectrogram analysis. IEEE EMBS Conf Proc 2003: 2531–2534.10.1109/IEMBS.2003.1280431Search in Google Scholar

[61] The GOLD Workshop Panel, Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Pulmonary Disease: Pocket guide to COPD diagnosis, management, and prevention – A guide for health care professionals. [http://itarget.com.br/newclients/sbpt.org.br/2011/downloads/arquivos/Dir_DPOC_Int/Global_Strategy_for_Diagnosis_Management_Prevention_Chronic_Obstructive_Pulmonary_Disease_AJRCCM_2007.pdf].Search in Google Scholar

[62] The RALE Repository (Respiratory Sounds) [http://www.rale.ca/repository.htm] (Accessed on 19 May, 2016).Search in Google Scholar

[63] Vannuccini L, Earis JE, Helisto P, et al. Capturing and preprocessing of respiratory sounds. Eur Respir Rev 2000; 10: 616–620.Search in Google Scholar

[64] Waris M, Helisto P, Haltsonen S, Saarinen A, Sovijärvi ARA. A new method for automatic wheeze detection. Technol Health Care 1998; 6: 33–40.10.3233/THC-1998-6105Search in Google Scholar PubMed

[65] Wilkins RL, Hodgkin JE, Lopez B. Fundamentals of lung and heart sounds. 3rd ed. Maryland Heights, MO, USA: Mosby 2004.Search in Google Scholar

[66] Williams L. Wilkins. Auscultation skills: breath and heart sounds. 4th ed. Princeton, NJ, USA: Princeton Univ. Press 2009.Search in Google Scholar

[67] Wisniewski M, Zielinski TP. Joint application of audio spectral envelope and tonality index in an e-asthma monitoring system. IEEE J Biomed Health 2015; 19: 1009–1018.10.1109/JBHI.2014.2352302Search in Google Scholar PubMed

[68] Wodicka GR, Kraman SS, Zenk GM, Pasterkamp H. Measurement of respiratory acoustic signals: effect of microphone air cavity depth. Chest 1994; 106: 1140–1144.10.1378/chest.106.4.1140Search in Google Scholar PubMed

[69] Wrigley D. Heart & Lung Sounds Reference Library. In PESI HealthCare (CD); 2011.Search in Google Scholar

[70] Yu C, Tsai T-H, Huang S-I, Lin C-W. Soft stethoscope for detecting asthma wheeze in young children. Sensors 2013; 13: 7399–7413.10.3390/s130607399Search in Google Scholar PubMed PubMed Central