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. 2022 Feb;151(2):1033.
doi: 10.1121/10.0009487.

A wearable multi-modal acoustic system for breathing analysis

Lloyd E Emokpae  1 , Roland N Emokpae Jr  1 , Ese Bowry  1 , Jaeed Bin Saif  2 , Muntasir Mahmud  2 , Wassila Lalouani  2 , Mohamed Younis  2 , Robert L Joyner Jr  3
Affiliations

A wearable multi-modal acoustic system for breathing analysis

Lloyd E Emokpae et al. J Acoust Soc Am. 2022 Feb.

Abstract

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide with over 3 × 106 deaths in 2019. Such an alarming figure becomes frightening when combined with the number of lost lives resulting from COVID-caused respiratory failure. Because COPD exacerbations identified early can commonly be treated at home, early symptom detections may enable a major reduction of COPD patient readmission and associated healthcare costs; this is particularly important during pandemics such as COVID-19 in which healthcare facilities are overwhelmed. The standard adjuncts used to assess lung function (e.g., spirometry, plethysmography, and CT scan) are expensive, time consuming, and cannot be used in remote patient monitoring of an acute exacerbation. In this paper, a wearable multi-modal system for breathing analysis is presented, which can be used in quantifying various airflow obstructions. The wearable multi-modal electroacoustic system employs a body area sensor network with each sensor-node having a multi-modal sensing capability, such as a digital stethoscope, electrocardiogram monitor, thermometer, and goniometer. The signal-to-noise ratio (SNR) of the resulting acoustic spectrum is used as a measure of breathing intensity. The results are shown from data collected from over 35 healthy subjects and 3 COPD subjects, demonstrating a positive correlation of SNR values to the health-scale score.

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Figures

FIG. 1.
FIG. 1.
(Color online) An illustration of our WearME system, used for bilateral lung data processing. WearME employs a body area sensor network with each sensor-node having a multi-modal sensing capability, such as a digital stethoscope, ECG, thermometer, and goniometer. In this paper, we mainly focus on our acoustic sensing and lung function metric, namely, the signal-to-noise ratio (SNR) in which the noise also reflects the turbulence caused by airflow obstruction.
FIG. 2.
FIG. 2.
(Color online) The bilateral SNR with varying material thickness. For this subject, the left thorax breathing level has an increase of approximately 8 dB in the SNR over the right thorax.
FIG. 3.
FIG. 3.
(Color online) The unilateral breathing sequence performed during the pilot testing of a 72-year-old male healthy subject. The power spectrum analysis shows the distinguishable frequency features between normal and deep breathing exercises.
FIG. 4.
FIG. 4.
(Color online) The bilateral breathing power spectrum of both anterior lungs simultaneously from a 23-year-old healthy subject. The motion was also captured and depicts slight forward-backward motions during the breathing assessment. The subject was seated and at rest during the assessment. The combined array processing yields a gain in the SNR of ∼7 dB.
FIG. 5.
FIG. 5.
(Color online) An image of a healthy baseline runner using our WearME system for breathing analysis (left). The sample subject breathing distribution (right) shows a higher SNR for subjects with a higher health scale. We collected data from 35 healthy subjects and 3 COPD subjects with comparable results.
FIG. 6.
FIG. 6.
(Color online) The distribution of the normalized SNR values to the respective health scale averaged over the recorded data sets. The results show a positive correlation to the health scale to the normalized SNR of the subject. The average health scale for the three COPD subjects was found to be 5.5/10.
See this image and copyright information in PMC

References

    1. Lozano R., Naghavi M., Foreman K., Lim S., Shibuya K., Aboyans V., Abraham J., Adair T., Aggrawal R., Ahn S. Y., AlMazroa M. A., Alvarado M., Anderson H. R., Anderson L. M., Andrews K. G., Atkinson C., Baddour L. M., Barker-Collo S., Bartels D. H., Bell M. L., Benjamin E. J., Bennett D., Bhalla K., Bikbov B., Abdulhak A. B., Birbeck G., Blyth F., Bolliger I., Boufous S., Bucello C., Burch M., Burney P., Carapetis J., Chen H., Chou D., Chugh S. S., Coffeng L. E., Colan S. D., Colquhoun S., Colson K. E., Condon J., Connor M. D., Cooper L. T., Corriere M., Cortinovis M., Courville de Vaccaro K., Couser W., Cowie B. C., Criqui M. H., Cross M., Dabhadkar K. C., Dahodwala N., De Leo D., Degenhardt L., Delossantos A., Denenberg J., Des Jarlais D. C., Dharmaratne S. D., Dorsey E. R., Driscoll T., Duber H., Ebel B., Erwin P. J., Espindola P., Ezzati M., Feigin V., Flaxman A. D., Forouzanfar M. H., Fowkes F. G. R., Franklin R., Fransen M., Freeman M. K., Gabriel S. E., Gakidou E., Gaspari F., Gillum R. F., Gonzalez-Medina D., Halasa Y. A., Haring D., Harrison J. E., Havmoeller R., Hay R. J., Hoen B., Hotez P. J., Hoy D., Jacobsen K. H., James S. L., Jasrasaria R., Jayaraman S., Johns N., Karthikeyan G., Kassebaum N., Keren A., Khoo J.-P., Knowlton L. M., Kobusingye O., Koranteng A., Krishnamurthi R., Lipnick M., Lipshultz S. E., Ohno S. L., Mabweijano J., MacIntyre M. F., Mallinger L., March L., Marks G. B., Marks R., Matsumori A., Matzopoulos R., Mayosi B. M., McAnulty J. H., McDermott M. M., McGrath J., Memish Z. A., Mensah G. A., Merriman T. R., Michaud C., Miller M., Miller T. R., Mock C., Mocumbi A. O., Mokdad A. A., Moran A., Mulholland K., Nair M. N., Naldi L., Narayan K. M. V., Nasseri K., Norman P., O'Donnell M., Omer S. B., Ortblad K., Osborne R., Ozgediz D., Pahari B., Pandian J. D., Panozo Rivero A., Perez Padilla R., Perez-Ruiz F., Perico N., Phillips D., Pierce K., Pope C. A. III, Porrini E., Pourmalek F., Raju M., Ranganathan D., Rehm J. T., Rein D. B., Remuzzi G., Rivara F. P., Roberts T., De León F. R., Rosenfeld L. C., Rushton L., Sacco R. L., Salomon J. A., Sampson U., Sanman E., Schwebel D. C., Segui-Gomez M., Shepard D. S., Singh D., Singleton J., Sliwa K., Smith E., Steer A., Taylor J. A., Thomas B., Tleyjeh I. M., Towbin J. A., Truelson T., Undurraga E. A., Venketasubramanian N., Vijayakumar L., Vos T., Wagner G. R., Wang M., Wang W., Watt K., Weinstock M. A., Weintraub R., Wilkinson J. D., Woolf A. D., Wulf S., Yeh P.-H., Yip P., Zabetian A., Zheng Z.-J., Lopez A. D., and Murray C. J. L., “ Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010,” Lancet 380(9859), 2095–2128 (2012). 10.1016/S0140-6736(12)61728-0 - DOI - PMC - PubMed
    1. Rabbani G., Islam S. M. S., Rahman M. A., Amin N., Marzan B., Robin R. C., and Alif S. M., “ Pre-existing COPD is associated with an increased risk of mortality and severity in COVID-19: A rapid systematic review and meta-analysis,” Expert Rev. Respir. Med. 15(5), 705–716 (2021). 10.1080/17476348.2021.1866547 - DOI - PubMed
    1. Ferguson G. T., Beck B., Clerisme-Beaty E., Liu D., Thomashow B. M., Wise R. A., ZuWallack R., and Make B. J., “ Recruiting patients after hospital discharge for acute exacerbation of COPD: Challenges and lessons learned,” Chronic Obstr. Pulm. Dis. 4(4), 265–278 (2017). 10.15326/jcopdf.4.4.2016.0176 - DOI - PMC - PubMed
    1. Qureshi H., Sharafkhaneh A., and Hanania N. A., “ Chronic obstructive pulmonary disease exacerbations: Latest evidence and clinical implications,” Ther. Adv. Chronic Dis. 5(5), 212–227 (2014). 10.1177/2040622314532862 - DOI - PMC - PubMed
    1. Portillo E. C., Wilcox A., Seckel E., Margolis A., Montgomery J., Balasubramanian P., Abshire G., Lewis J., Hildebrand C., Mathur S., Bridges A., and Kakumanu S., “ Reducing COPD readmission rates: Using a COPD care service during care transitions,” Fed. Pract.: Health Care Prof. VA, DoD, PHS 35(11), 30–36 (2018). - PMC - PubMed

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