Abstract
Traditional long-term oxygen therapy devices used in daily-life activities need to be manually adjusted depending on the level of intensity of the activity done. In this study, a system to automatically control a commercial POC devices is proposed with the aim of improving the used and efficacy of the therapy in patients with chronic obstructive pulmonary disease.
A patient unit and a control unit were designed and implemented to control a Inogen G2 oxygen concentrator. The patient unit included an inertial measurement unit to classify in real-time the physical activity performed by the user. The control unit receive via Bluetooth (BLE) the degree of activity and adjusted the oxygen concentrator automatically following the setting provided by clinician.
Data from a group of six volunteers were used to train and validated the system using different machine learning algorithms. A logistic regression model (LR) achieved the best accuracy (93.69%) in classifying the physical activity and consequently adjusting correctly the O2 dose.
The developed system may improve oxygenation through automatic adaptation to lifestyle, could contribute to improve the patient’s therapeutic compliance and may promote physical activity.
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References
Dunne, P.J.: Long-term oxygen therapy (LTOT) revisited: In defense of non-delivery LTOT technology. Rev. Port. Pneumol. 18 (2012)
Meena, M., Dixit, R., Kewlani, J.P., Kumar, S., Harish, S., Sharma, D., Singh, M.: Home-based long-term oxygen therapy and oxygen conservation devices: an updated review. Natl. J. Physiol. Pharm. Pharmacol. 5, 267–274 (2015)
Bye, P.T.P., Esau, S.A., Levy, R.D., Shiner, R.J., Macklem, P.T., Martin, J.G., Pardy, R.L.: Ventilatory muscle function during exercise in air and oxygen in patients with chronic air-flow limitation. Am. Rev. Respir. Dis. 132, 236–240 (1985)
British Lung Foundation: Chronic obstructive pulmonary disease (COPD) statistics. https://statistics.blf.org.uk/copd. Accessed 10 June 2019
Sanchez-Morillo, D., Olaby, O., Fernandez-Granero, M.A., Leon-Jimenez, A.: Physiological closed-loop control in intelligent oxygen therapy: a review. Comput. Methods Programs Biomed. 146, 1339–1351 (2017)
Sanchez-Morillo, D., Olaby, O., Fernandez-Granero, M.A., Leon-Jimenez, A.: Automatic recognition of daily physical activities for an intelligent-portable oxygen concentrator (iPOC). Lecture Notes Computer Science LNCS, vol. 10305, pp. 212–221 (2017)
Egton Medical Information Systems Limited: Use of Oxygen Therapy in COPD, pp. 4–7 (2015)
Yang, C.C., Hsu, Y.L.: A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors 10, 7772–7788 (2010)
Ainsworth, B.E., Haskell, W.I.L., Whitt, M.C.: e: Compendium of physical activities: an update of activity codes and MET intensities. Med. Sci. Sports Exerc. 32, S498–S504 (2000)
Funding
This work has been supported and funded by the EU FEDER ITI Grant for Cadiz Province PI-0006-2017 and by Consejería de Salud y Familias - Junta de Andalucía through Grant PIN-0053-2017.
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DSM, MAFG and ALJ are inventors of the utility model ES U201831680 with the title ‘Automatic flow-metering device for oxygen therapy equipment’. ALD and MPM have no conflict of interest.
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Lara-Doña, A., Sanchez-Morillo, D., Pérez-Morales, M., Fernandez-Granero, M.Á., Leon-Jimenez, A. (2020). A Prototype of Intelligent Portable Oxygen Concentrator for Patients with COPD Under Oxygen Therapy. In: Henriques, J., Neves, N., de Carvalho, P. (eds) XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019. MEDICON 2019. IFMBE Proceedings, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-31635-8_55
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DOI: https://doi.org/10.1007/978-3-030-31635-8_55
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