nach oben

Artificial Intelligence Review

Erschienen in:

02.11.2019

Computerized acoustical techniques for respiratory flow-sound analysis: a systematic review

verfasst von: Priya Devi Muthusamy, Kenneth Sundaraj, Nurulfajar Abd Manap

Erschienen in: Artificial Intelligence Review | Ausgabe 5/2020

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Computerized respiratory sound analysis has recently captured the attention of researchers, and its implementation can assist physicians in the diagnosis of pulmonary pathologies. The relationship between respiratory sounds and breathing flow reveals the pathophysiology of the respiratory system and can be used as a basis for acoustical airflow estimation. Respiratory sound signals are also acoustically analysed for the detection of breath phases. Although this research area is being actively studied, the available literature has not been reviewed. This manuscript highlights the previous studies that focused on the use of computer-based acoustical techniques for the analysis of respiratory sounds and airflow. Articles related to computerized respiratory flow-sound analysis were identified through a search of the Scopus academic database, and 66 articles were ultimately selected for this systematic review. A brief overview of the subject details, auscultation sites, respiratory manoeuvres, sound parameters of interest and techniques used is provided. The findings revealed the following: (1) deterministic relationships can be established between airflow and respiratory sounds, (2) an established strong flow-sound correlation can be used for airflow estimation, (3) breath phase detection and identification without flow measuring devices remains in the infancy research stage and (4) further research needed to examine the potential of computerized respiratory sound analysis in revealing the pathophysiology of airways for future clinical implementation. This review concludes by discussing the possibilities and recommendations for further advancements in computerized acoustical flow-sound analysis.

Vorheriger Artikel A review of applications of artificial intelligent algorithms in wind farms

Nächster Artikel Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Anusha AR, Soodi AL, Kumar SP (2012) Design of low-cost hardware for lung sound acquisition and determination of inspiratory-expiratory phase using respiratory waveform. In: Proceedings of IEEE international conference on computing communication and networking technologies, pp 1–5

Beck R, Rosenhouse G, Mahagnah M, Chow RM, Cugell DW, Gavriely N (2005) Measurements and theory of normal tracheal breath sounds. Ann Biomed Eng 33(10):1344–1351

Bohadana AB, Peslin R, Uffholtz H (1978) Breath sounds in the clinical assessment of airflow obstruction. Thorax 33(3):345–351

Bohadana AB, Peslin R, Ufffioltz H, Pauli G (1995) Potential for lung sound monitoring during bronchial provocation testing. Thorax 50(9):955–961

Christensen MA, Leitner E, Levy B, Sathiyamoorthy BB, Burke DT, Sisson TH (2014) Breath sounds analysis for asthma monitoring: a method for automated detection of flow events from tracheal recordings. In: Proceedings of IEEE conference on healthcare innovations and point of care technologies, pp 331–334

Chuah JS, Moussavi ZK (2000) Automated respiratory phase detection by acoustical means. In: Proceedings of conference on systems, cybernatics & informatics, pp 228–231

Ciftci K, Kahya YP (2008) Respiratory airflow estimation by time varying autoregressive modeling. In: Proceedings of IEEE conference on engineering in medicine and biology society, pp 347–350

Fischer HS, Puder LC, Wilitzki S, Usemann J, Buhrer C, Godfrey S, Schmalisch G (2016) Relationship between computerized wheeze detection and lung function parameters in young infants. Pediatr Pulmonol 51:402–410

Fiz JA, Jané R, Lozano M, Gómez R, Ruiz J (2014) Detecting unilateral phrenic paralysis by acoustic respiratory analysis. PLoS ONE 9(4):e93595

Golabbakhsh M, Moussavi Z (2004) Relationship between airflow and frequency-based features of tracheal respiratory sound. In: Proceedings of IEEE Canadian conference on electrical and computer engineering, pp 751–754

Golabbakhsh M, Moussavi Z, Aboofazeli M (2005) Respiratory flow estimation from tracheal sound by adaptive filters. In: Proceedings of IEEE conference on engineering in medicine and biology, pp 4216–4219

Gomes LL, Oliveira NV, Tauil LM, Mattos RA, Melo PL (2018) Instrumentation for respiratory flow estimation using tracheal sounds analysis: design and evaluation in measurements of respiratory cycle periods and airflow amplitude. In: Proceedings of IOP Journal of Physics: Conference series, pp 1–7

Habukawa C, Nagasaka Y, Murakami K, Takemura T (2009) High-pitched breath sounds indicate airflow limitation in asymptomatic asthmatic children. Respirology 14(3):399–403

Hossain I, Moussavi Z (2002a) Respiratory airflow estimation by acoustical means. In: Proceedings of IEEE conference on biomedical engineering society/engineering in medicine and biology society, pp 1476–1477

Hossain I, Moussavi Z (2002b) Relationship between airflow and normal lung sounds. In: Proceedings of IEEE Canadian conference on electrical and computer engineering, pp 1120–1122

Hossain I, Moussavi Z (2004) Finding the lung sound-flow relationship in normal and asthmatic subjects. In: Proceedings of IEEE conference on engineering in medicine and biology society, pp 3852–3855

Huq S, Moussavi Z (2012) Acoustic breath-phase detection using tracheal breath sounds. Med Biol Eng Comput 50(3):297–308

Jin F, Sattar F (2016) Unsupervised phase detection for respiratory sounds using improved scale-space features. In: Proceedings of IEEE international symposium on signal processing and information technology, pp 1–6

Jin F, Sattar F, Goh DYT, Loius IM (2009) A robust respiratory phase identification scheme based on a new mixing index. In: Proceedings of European signal processing conference, pp 637–641

Jin F, Sattar F, Goh DYT (2014) New approaches for spectro-temporal feature extraction with applications to respiratory sound classification. Neurocomputing 123:362–371

Korenbaum VI, Kulakov YV, Tagiltsev AA (1997) Acoustic effects in the human respiraotry system under forced expiration. Acoust Phys 43:78–86

Korenbaum VI, Tagiltsev AA, Kulakov JV, Kilin AS, Avdeeva HV, Pochekutova IA (1998) An acoustic model of noise production in the human bronchial tree under forced expiration. J Sound Vib 213:377–382

Kraman SS (1984) The relationship between airflow and lung sound amplitude in normal subjects. Chest 86(2):225–229

Kulkas A, Huupponen E, Virkkala J, Tenhunen M, Saastamoinen A, Rauhala E, Himanen SL (2009) Intelligent methods for identifying respiratory cycle phases from tracheal sound signal during sleep. Comput Biol Med 39(11):1000–1005

Kulkas A, Huupponen E, Virkkala J, Saastamoinen A, Rauhala E, Tenhunen M, Himanen SL (2010) Tracheal sound parameters of respiratory cycle phases show differences between flow-limited and normal breathing during sleep. Physiol Meas 31(3):427–438

Laënnec RTH (1819) De l’Auscultation Médiate ou Traité du Diagnostic des Maladies des Poumons et du Coeur. Brosson & Chaudé, Paris

Le Cam S, Collet C, Salzenstein F (2008) Acoustical respiratory signal analysis and phase detection. In: Proceedings of IEEE international conference on acoustics, speech and signal processing, pp 3629–3632

Lessard CS, Wong WC (1986) Correlation of constant flow rate with frequency spectrum of respiratory sounds when measured at the trachea. IEEE Trans Biomed Eng 33(4):461–463

Lyubimov GA, Skobeleva IM, Dyachenko AI, Strongin MM (2013) Estimation of tracheal sound intensity during forced expiration. Hum Physiol 39(1):106–113

Macgregor CA, Moussavi Z (2014) A novel expert classifier approach to pre-screening obstructive sleep apnea during wakefulness. In: Proceedings of IEEE international conference on engineering in medicine and biology society, pp 4236–4239

Manecke GR Jr, Dilger JP, Kutner LJ, Poppers PJ (1997) Auscultation revisited the waveform and spectral characteristics of breath sounds during general anesthesia. Int J Clin Monit Comput 14(4):231–240

Messner E, Hagmuller M, Swatek P, Smolle-Juttner F, Pernkopf F (2017) Respiratory airflow estimation from lung sounds based on regression. In: Proceedings of IEEE international conference on acoustics, speech and signal processing, pp 1123–1127

Mondal A, Bhattacharya P, Saha G (2014) Detection of lungs status using morphological complexities of respiratory sounds. Sci World J 182938:1–9

Mondal A, Banerjee P, Tang H (2018) A novel feature extraction technique for pulmonary sound analysis based on EMD. Comput Methods Programs Biomed 159:199–209

Morillo DS, Moreno SA, Granero MAF, Jiménez AL (2013) Computerized analysis of respiratory sounds during COPD exacerbations. Comput Biol Med 43:914–921

Moussavi ZK, Leopando MT, Pasterkamp H, Rempel G (2000) Computerised acoustical respiratory phase detection without airflow measurement. Med Biol Eng Comput 38(2):198–203

Nabi FG, Sundaraj K, Lam CK, Palaniappan R, Sundaraj S (2017) Wheeze sound analysis using computer-based techniques: a systematic review. Biomed Tech 64(1):1–28

Niu J, Shi Y, Cai M, Cao Z, Wang D, Zhang Z, Zhang XD (2018) Detection of sputum by interpreting the time-frequency distribution of respiratory sound signal using image processing techniques. Bioinformatics 34:820–827

Oliveira A, Marques A (2014) Respiratory sounds in healthy people: a systematic review. Respir Med 108(4):550–570

Palaniappan R, Sundaraj K, Ahamed N, Arjunan A, Sundaraj S (2013a) Computer-based respiratory sound analysis: a systematic review. IETE Tech Rev 30(3):248–256

Palaniappan R, Sundaraj K, Ahamed NU (2013b) Machine learning in lung sound analysis: a systematic review. Biocybern Biomed Eng 33(3):129–135

Palaniappan R, Sundaraj K, Sundaraj S (2014) Artificial intelligence techniques used in respiratory sound analysis—a systematic review. Biomed Tech 59(1):7–18

Palaniappan R, Sundaraj K, Nabi FG (2015) An overview of breath phase detection—techniques & applications. J Telecommun Electron Comput Eng 10(2–7):33–36

Palaniappan R, Sundaraj K, Sundaraj S (2017) Adaptive neuro-fuzzy inference system for breath phase detection and breath cycle segmentation. Comput Methods Programs Biomed 145:67–72

Parida PK, Shanmugasundaram N, Gopalakrishnan S (2016) Clinico-radiological parameters predicting early diagnosis of foreign body aspiration in children. Turkish Journal of Ear Nose and Throat 26(5):268–275

Pasterkamp H, Carson C, Daien D, Oh Y (1989) Digital respirosonography. New images of lung sounds. Chest 96:1405–1412

Pochekutova IA, Korenbaum VI (2001) Analysis of tracheal forced exiratory noise in diagnostics of bronchial obstruction. In: Proceedings of XI session of Russian acoustical society, pp 704–707

Pochekutova IA, Korenbaum VI (2013) Diagnosis of hidden bronchial obstruction using computer-assessed tracheal forced expiratory noise time. Respirology 18:501–506

Poreva A, Karplyuk Y, Makarenkova A, Makarenkov A (2015) Detection of COPD’s diagnostic signs based on polyspectral lung sounds analysis of respiratory phases. In: Proceedings of IEEE international conference on electronics and nanotechnology, pp 351–355

Pramono RXA, Bowyer S, Rodriguez-Villegas E (2017) Automatic adventitious respiratory sound analysis: a systematic review. PLoS ONE 12(5):e0177926

Reyes BA, Charleston-Villalobos S, González-Camarena R, Aljama-Corrales T (2014a) Assessment of time-frequency representation techniques for thoracic sounds analysis. Comput Methods Programs Biomed 114:276–290

Reyes BA, Reljin N, Chon KH (2014b) Tracheal sounds acquisition using smartphones. Sensors 14(8):13830–13850

Saarinen A, Rihkanen H, Malmberg LP, Pekkanen L, Sovijärvi ARA (2001) Tracheal sounds and airflow dynamics in surgically treated unilateral vocal fold paralysis. Clin Physiol 21(2):223–228

Saha S, Bradley TD, Taheri M, Moussavi Z, Yadollahi A (2016) A subject-specific acoustic model of the upper airway for snoring sounds generation. Sci Rep 6:25730

Sanchez I, Avital A, Wong I, Tal A, Pasterkamp H (1993a) Acoustic vs. spirometric assessment of bronchial responsiveness to methacholine in children. Pediatr Pulmonol 15(1):28–35

Sanchez I, Powell RE, Pasterkamp H (1993b) Wheezing and airflow obstruction during methacholine challenge in children with cystic fibrosis and in normal children. Am Rev Respir Dis 147(3):705–709

Sarkar M, Madabhavi I, Niranjan N, Dogra M (2015) Auscultation of the respiratory system. Ann Thorac Med 10(3):158–168

Schreur HJW, Diamant Z, Vanderschoot J, Zwinderman AH, Dijkman JH, Sterk PJ (1996) Lung sounds during allergen-induced asthmatic responses in patients with asthma. Am J Respir Crit Care Med 153:1474–1480

Schudt F, Gross V, Weissflog A, Mursina L, Koehler U, Sohrabi K (2014) Estimation of respiratory flow by means of normal lung sound. Stud Health Technol Inform 198:232–237

Shykoff BE, Ploysongsang Y, Chang HK (1988) Airflow and normal lung sounds. Am Rev Respir Dis 137(4):872–876

Sohrabi KA, Basu D, Schudt F, Scholtes M, Seifert O, Koehler U, Gross V (2012) Quantification of nasal respiratory flow by tracheal sound analysis. Biomed Tech 57:733–735

Soufflet G, Charbonneau G, Polit M, Attal P, Denjean A, Escourrou P, Gaultier C (1990) Interaction between tracheal sound and flow rate: a comparison of some different flow evaluations from lung sounds. IEEE Trans Biomed Eng 37(4):384–391

Sovijärvi ARA, Malmberg LP, Paajanen E, Pürilä P, Kallio K, Katila T (1996) Averaged and time-gated spectral analysis of respiratory sounds: repeatability of spectral parameters in healthy men and in patients with fibrosing alveolitis. Chest 109(5):1283–1290

Sovijärvi ARA, Vanderschoot J, Earis JE (2000) Standardization of computerized respiratory sound analysis current methods used for computerized respiratory sound analysis. Eur Respir Rev 10(77):585

Yadollahi A, Moussavi ZMK (2006) A robust method for estimating respiratory flow using tracheal sounds entropy. IEEE Trans Biomed Eng 53(4):662–668

Yadollahi A, Moussavi Z (2008) Comparison of flow-sound relationship for different features of tracheal sound. In: Proceedings of IEEE conference on engineering in medicine and biology society, pp 805–808

Yadollahi A, Moussavi Z (2009) On arithmetic misconceptions of spectral analysis of biological signals, in particular respiratory sounds. In: Proceedings of IEEE conference on engineering in medicine and biology society, pp 388–391

Yadollahi A, Moussavi ZMK (2011) The effect of anthropometric variations on acoustical flow estimation: proposing a novel approach for flow estimation without the need for individual calibration. IEEE Trans Biomed Eng 58(6):1663–1670

Yadollahi A, Giannouli E, Moussavi Z (2010) Sleep apnea monitoring and diagnosis based on pulse oximetery and tracheal sound signals. Med Biol Eng Comput 48(11):1087–1097

Yadollahi A, Montazeri A, Azarbarzin A, Moussavi Z (2013) Respiratory flow-sound relationship during both wakefulness and sleep and its variation in relation to sleep apnea. Ann Biomed Eng 41(3):537–546

Yadollahi A, Rudzicz F, Mahallati S, Coimbra M, Bradley TD (2014) Acoustic estimation of neck fluid volume. Ann Biomed Eng 42:2132–2142

Yap YL, Moussavi Z (2001) Respiratory onset detection using variance fractal dimension. In: Proceedings of IEEE international conference on engineering in medicine and biology society, pp 1554–1556

Yap YL, Moussavi Z (2002) Acoustic airflow estimation from tracheal sound power. In: Proceedings of IEEE Canadian conference on electrical and computer engineering, pp 1073–1076

Yildirim I, Ansari R, Moussavi Z (2008) Automated respiratory phase and onset detection using only chest sound signal. In: Proceedings of IEEE international conference on engineering in medicine and biology society, pp 2578–2581

Yu L, Ting CK, Hill BE, Orr JA, Brewer LM, Johnson KB, Egan TD, Westenskow DR (2013) Using the entropy of tracheal sounds to detect apnea during sedation in healthy nonobese volunteers. Anesthesiology 118:1341–1349

Yuasa Y, Suzuki K (2019) Wearable device for monitoring respiratory phases based on breathing sound and chest movement. Adv Biomed Eng 8:85–91

Titel: Computerized acoustical techniques for respiratory flow-sound analysis: a systematic review
verfasst von: Priya Devi Muthusamy
Kenneth Sundaraj
Nurulfajar Abd Manap
Publikationsdatum: 02.11.2019
Verlag: Springer Netherlands
Erschienen in: Artificial Intelligence Review / Ausgabe 5/2020
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI: https://doi.org/10.1007/s10462-019-09769-6

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 5/2020

An efficient intrusion detection technique based on support vector machine and improved binary gravitational search algorithm

Neural networks for facial age estimation: a survey on recent advances

Opportunities and challenges in enhancing access to metadata of cultural heritage collections: a survey

Detecting the presence of anterior cruciate ligament injury based on gait dynamics disparity and neural networks

Explicit methods for attribute weighting in multi-attribute decision-making: a review study

A comparative evaluation of novelty detection algorithms for discrete sequences

Premium Partner