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A MEMS seismometer respiratory monitor for work of breathing assessment and adventitious lung sounds detection via deep learning

  • Bousquet, J., Khaltaev, N. G., Cruz, A. A. & World Health Organization. Global Surveillance, Prevention and Control of Chronic Respiratory Diseases : A Comprehensive Approach.

  • Dwyer-Lindgren, L. et al. Trends and patterns of differences in chronic respiratory disease mortality among US counties, 1980–2014. JAMA J. Am. Med. Assoc. 318, 1136–1149 (2017).

    Article 
    MATH 

    Google Scholar 

  • Ruuskanen, O., Lahti, E., Jennings, L. C. & Murdoch, D. R. Viral pneumonia. Lancet 377, 1264–1275 (2011).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Agustí, A., Vogelmeier, C. & Faner, R. COPD 2020: Changes and challenges. Am. J. Physiol. Lung Cell Mol. Physiol. 319, L879–L883. (2020).

    Article 
    PubMed 

    Google Scholar 

  • Confalonieri, M. et al. Acute respiratory failure in patients with severe community-acquired pneumonia a prospective randomized evaluation of noninvasive ventilation. Am. J. Respir. Crit. Care Med. 160, 1585–1591 (1999).

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar 

  • Calverley, P. M. A. Respiratory failure in chronic obstructive pulmonary disease. Eur. Respir. J. 22, 26s–30s (2003).

    Article 

    Google Scholar 

  • Quaderi, S. A. & Hurst, J. R. The unmet global burden of COPD. Glob. Health Epidemiol. Genomics (2018).

    Article 
    MATH 

    Google Scholar 

  • COPD Trends Brief: Burden. American Lung Association.

  • Agustí, A., Vogelmeier, C. & Faner, R. COPD 2020: Changes and challenges. Am. J. Physiol. Lung Cell. Mol. Physiol. 319, L879–L883. (2020).

    Article 
    PubMed 

    Google Scholar 

  • Wunsch, H. et al. The epidemiology of mechanical ventilation use in the United States. Crit. Care Med. 38, 1947–1953 (2010).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Vandevoorde, J. et al. Early detection of COPD: A case finding study in general practice. Respir. Med. 101, 525–530 (2007).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Sekine, Y., Katsura, H., Koh, E., Hiroshima, K. & Fujisawa, T. Early detection of COPD is important for lung cancer surveillance. Eur. Respir. J. 39, 1230–1240. (2012).

    Article 
    PubMed 

    Google Scholar 

  • Bedoya, A. D. et al. Unanticipated respiratory compromise and unplanned intubations on general medical and surgical floors. Respir. Care 65, 1233–1240 (2020).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Alqahtani, J. S. et al. Risk factors for all-cause hospital readmission following exacerbation of COPD: A systematic review and meta-analysis. Eur. Respir. Rev. 29, 1–16. (2020).

    Article 
    MATH 

    Google Scholar 

  • Gattarello, S. et al. Decrease in Mortality in severe community-acquired pneumococcal pneumonia: Impact of improving antibiotic strategies (2000–2013). Chest 146, 22–31 (2014).

    Article 
    PubMed 

    Google Scholar 

  • Houck, P. M., Bratzler, D. W., Nsa, W., Ma, A. & Bartlett, J. G. Timing of antibiotic administration and outcomes for medicare patients hospitalized with community-acquired pneumonia. Arch. Intern. Med. 164, 637–644 (2004).

    Article 
    PubMed 

    Google Scholar 

  • Warusevitane, A., Karunatilake, D., Sim, J., Smith, C. & Roffe, C. Early diagnosis of pneumonia in severe stroke: clinical features and the diagnostic role of C-Reactive protein. PLoS ONE 11, (2016).

  • Boniatti, M. M. et al. Delayed medical emergency team calls and associated outcomes. Crit. Care Med. 42, 26–30 (2014).

    Article 
    PubMed 

    Google Scholar 

  • Cyphers, V. E. et al. Labored Breathing Pattern: An Unmeasured Dimension of Respiratory Pathophysiology. (2024).

  • Vestbo, J. et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease GOLD executive summary. Am. J. Respir. Crit. Care Med. 187, 347–365. (2013).

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar 

  • Noah, B. et al. Impact of remote patient monitoring on clinical outcomes: an updated meta-analysis of randomized controlled trials. Npj Digit. Med. (2018).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Chau, J. P. C. et al. A feasibility study to investigate the acceptability and potential effectiveness of a telecare service for older people with chronic obstructive pulmonary disease. Int. J. Med. Inform. 81, 674–682 (2012).

    Article 
    PubMed 

    Google Scholar 

  • Dieffenderfer, J. et al. Low-power wearable systems for continuous monitoring of environment and health for chronic respiratory disease. IEEE J. Biomed. Health Inform. 20, 1251–1264 (2016).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Whitehead, D. & Conley, J. The next frontier of remote patient monitoring: Hospital at home. J. Med. Internet Res. 25, e42335 (2023).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Ashe, W. B. et al. Analysis of respiratory kinematics: a method to characterize breaths from motion signals. Physiol. Meas. 43, 015007 (2022).

    Article 
    MATH 

    Google Scholar 

  • Tulaimat, A. & Trick, W. E. DiapHRaGM: A mnemonic to describe the work of breathing in patients with respiratory failure. PLoS ONE 12, e0179641 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Apigo, M., Schechtman, J., Dhliwayo, N., Al Tameemi, M. & Gazmuri, R. J. Development of a work of breathing scale and monitoring need of intubation in COVID-19 pneumonia. Crit. Care (2020).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Fie, J. F. & Helms, C. M. Respiratory rate predicts cardiopulmonary arrest for internal medicine in patients. J. Gen. Intern. Med. 8, 354–360 (1993).

    Article 
    MATH 

    Google Scholar 

  • Cabello, B. & Mancebo, J. Work of breathing. Intensive Care Med. 32, 1311–1314 (2006).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Bellani, G. & Pesenti, A. Assessing effort and work of breathing. Curr. Opin. Crit. Care 20, 352–358. (2014).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Tulaimat, A., Gueret, R. M., Wisniewski, M. F. & Samuel, J. Association between rating of respiratory distress and vital signs, severity of illness, intubation, and mortality in acutely 111 subjects. Respir. Care 59, 1338–1344 (2014).

    Article 
    PubMed 

    Google Scholar 

  • Tulaimat, A., Patel, A., Wisniewski, M. & Gueret, R. The validity and reliability of the clinical assessment of increased work of breathing in acutely ill patients. J. Crit. Care 34, 111–115 (2016).

    Article 
    PubMed 

    Google Scholar 

  • Courtney, R. The functions of breathing and its dysfunctions and their relationship to breathing therapy. Int. J. Osteopathic Med. 12, 78–85 (2009).

    Article 
    MATH 

    Google Scholar 

  • Saraya, T., Shimoda, M., Hirata, A. & Takizawa, H. Paradoxical respiration: ‘Seesaw’ motion with massive pulmonary consolidation. BMJ Case Rep. (2016).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Jonkman, A. H. et al. Analysis and applications of respiratory surface EMG: report of a round table meeting. Crit. Care (2024).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Sarlabous, L. et al. Efficiency of mechanical activation of inspiratory muscles in COPD using sample entropy. Eur. Respir. J. 46, 1808–1811. (2015).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Sarlabous, L. et al. Inspiratory muscle activation increases with COPD severity as confirmed by non-invasive mechanomyographic analysis. PLoS ONE 12, e0177730 (2017).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Lozano-García, M. et al. Surface mechanomyography and electromyography provide non-invasive indices of inspiratory muscle force and activation in healthy subjects. Sci. Rep. (2018).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Beck, T. W. et al. Mechnomyographic amplitude and frequency responses during dynamic muscle actions: A comprehensive review. BioMed. Eng. Online (2005).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Sang, B. et al. Identification of S2 paradoxical splitting in aortic stenosis subjects via seismocardiogram signals from a wearable accelerometer contact microphone. IEEE Sens. J. (2023).

    Article 

    Google Scholar 

  • Sang, B., Wen, H., Junek, G., Di Francesco, L. & Ayazi, F. Detection of respiratory crackles and respiration phase using a wearable MEMS contact microphone. In 2023 IEEE 19th International Conference on Body Sensor Networks (BSN) 1–4 (Institute of Electrical and Electronics Engineers (IEEE, 2023).

  • Sang, B. et al. An accelerometer-based wearable patch for robust respiratory rate and wheeze detection using deep learning. Biosensors 14, 118 (2024).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Gupta, P., Wen, H., Di Francesco, L. & Ayazi, F. Detection of pathological mechano-acoustic signatures using precision accelerometer contact microphones in patients with pulmonary disorders. Sci. Rep. (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Dellinger, R. P. et al. Regional distribution of acoustic-based lung vibration as a function of mechanical ventilation mode. Crit. Care (2007).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Gupta, P., Wen, H., Daruwalla, A., Moghimi, M. & Ayazi, F. A hermetically-encapsulated unidirectional accelerometer contact microphone for wearable applications. 2019 IEEE Sens. (2019).

  • Gupta, P. et al. Precision wearable accelerometer contact microphones for longitudinal monitoring of mechano-acoustic cardiopulmonary signals. NPJ Digit. Med. (2020).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Sang, B. et al. Detection of normal and paradoxical splitting in second heart sound (S2) using a wearable accelerometer contact microphone. In 2022 IEEE Sensors 1–4 (IEEE, 2022). https://doi.org/10.1109/SENSORS52175.2022.9967056.

  • Bohadana, A., Izbicki, G. & Kraman, S. S. Fundamentals of lung auscultation. N. Engl. J. Med. 370, 744–751 (2014).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Nath, A. R. & Capel, L. H. Inspiratory crackles–early and late. Thorax 29, 223–227 (1974).

    Article 
    PubMed Central 
    MATH 

    Google Scholar 

  • Melbye, H., Aviles Solis, J. C., Jácome, C. & Pasterkamp, H. Inspiratory crackles-early and late-revisited: Identifying copd by crackle characteristics. BMJ Open Respir. Res. 8, e000852 (2021).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

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

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Arts, L., Lim, E. H. T., van de Ven, P. M., Heunks, L. & Tuinman, P. R. The diagnostic accuracy of lung auscultation in adult patients with acute pulmonary pathologies: a meta-analysis. Sci. Rep. 10, (2020).

  • Gavriely, N., Shee, T. R., Cugell, D. W. & Grotberg, J. B. Flutter in flow-limited collapsible tubes: A mechanism for generation of wheezes. J. Appl. Physiol. 66 (1989).

  • Cruz, J. D. L. T. et al. Monophonic and polyphonic wheezing classification based on constrained low-rank non-negative matrix factorization. Sensors 21, 1–23 (2021).

    MATH 

    Google Scholar 

  • Meslier, N., Charbonneau, G. & Racineux, J. L. Wheezes. Eur. Respir. J. 8, 1942–1948. (1995).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Pasterkamp, H., Kraman, S. S. & Wodicka, G. R. State of the art respiratory sounds advances beyond the stethoscope. Am. J. Respir. Crit. Care Med. 156, 974–987 (1997).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • Islam, M. A., Sundaraj, K., Ahmad, R. B. & Ahamed, N. U. Mechanomyogram for muscle function assessment: A review. PLoS ONE 8, e58902 (2013).

    Article 
    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • De Troyer, A., Kirkwood, P. A. & Wilson, T. A. Respiratory Action of the Intercostal Muscles. (2005).

  • Dellweg, D., Haidl, P., Siemon, K., Appelhans, P. & Kohler, D. Impact of breathing pattern on work of breathing in healthy subjects and patients with COPD. Respir. Physiol. Neurobiol. 161, 197–200 (2008).

    Article 
    PubMed 

    Google Scholar 

  • Assaad, S., Kratzert, W. B., Shelley, B., Friedman, M. B. & Perrino, A. Assessment of pulmonary edema: Principles and practice. J. Cardiothorac. Vasc. Anesth. 32, 901–914. (2018).

    Article 
    PubMed 

    Google Scholar 

  • Fukumitsu, T. et al. The acoustic characteristics of fine crackles predict honeycombing on high-resolution computed tomography. BMC Pulm. Med. (2019).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Sgalla, G. et al. ‘Velcro-type’ crackles predict specific radiologic features of fibrotic interstitial lung disease. BMC Pulm. Med. (2018).

    Article 
    PubMed 
    PubMed Central 

    Google Scholar 

  • Yoo, J. Y. et al. Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring. Nat. Med. 29, 3137–3148 (2023).

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar 

  • De Troyer, A., Kirkwood, P. A. & Wilson, T. A. Respiratory action of the intercostal muscles. Physiol. Rev. 85, 717–756 (2005).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Piirila, P. & Sovijarvi, A. R. A. Objective assessment of cough. Eur. Respir. J. 8, 1949–1956. (1995).

    Article 
    CAS 
    PubMed 
    MATH 

    Google Scholar 

  • Pfleger, A. & Eber, E. Assessment and causes of stridor. Paediatr. Respir. Rev. 18, 64–72. (2016).

    Article 
    PubMed 
    MATH 

    Google Scholar 

  • Homs-Corbera, A., Fiz, J. A., Morera, J. & Jané, R. Time-frequency detection and analysis of wheezes during forced exhalation. IEEE Trans. Biomed. Eng. 51, 182–186 (2004).

    Article 
    PubMed 

    Google Scholar 

  • Leng, S. et al. The electronic stethoscope. BioMed. Eng Online (2015).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Kim, Y. et al. Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning. Sci. Rep. 11, (2021).

  • Raper, A. J., Taliaferro Thompson, W., Shapiro, W. & Patterson, J. L. Scalene and sternomastoid muscle function. Am. Physiol. Soc. 21, 497–502 (1966).

    CAS 
    MATH 

    Google Scholar 

  • Kim, B. J., Kim, B. S., Mun, J. H., Lim, C. & Kim, K. H. An accurate deep learning model for wheezing in children using real world data. Sci. Rep. (2022).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • Hoon Lee, S. et al. Fully portable continuous real-time auscultation with a soft wearable stethoscope designed for automated disease diagnosis. Sci. Adv. (2022).

    Article 
    MATH 

    Google Scholar 

  • Wilkinson, T. M. A., Donaldson, G. C., Hurst, J. R., Seemungal, T. A. R. & Wedzicha, J. A. Early therapy improves outcomes of exacerbations of chronic obstructive pulmonary disease. Am. J. Respir. Crit. Care Med. 169, 1298–1303 (2004).

    Article 
    PubMed 

    Google Scholar 

  • Romei, M. et al. Effects of gender and posture on thoraco-abdominal kinematics during quiet breathing in healthy adults. Respir. Physiol. Neurobiol. 172, 184–191 (2010).

    Article 
    CAS 
    PubMed 

    Google Scholar 

  • McCollum, E. D. et al. Digital auscultation in PERCH: Associations with chest radiography and pneumonia mortality in children. Pediatr. Pulmonol. 55, 3197–3208 (2020).

    Article 
    PubMed 
    PubMed Central 
    MATH 

    Google Scholar 

  • McCollum, E. D. et al. Listening panel agreement and characteristics of lung sounds digitally recorded from children aged 1–59 months enrolled in the pneumonia etiology research for child health (PERCH) case–control study. BMJ Open Respir. Res. 4, (2017).