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Thingspeak-based respiratory rate streaming system for essential monitoring purposes

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Introduction: Chronic obstructive pulmonary diseases are the most common disease worldwide. Asthma and sleep apnea are the most prevalent of pulmonary diseases. Patients with such chronic diseases require special care and continuous monitoring to avoid any respiratory deterioration. Therefore, the development of a dedicated and reliable sensor with the aid of modern technologies for measuring and monitoring respiratory parameters is very necessary nowadays. Objective: This study aims to develop a small and costeffective respiratory rate sensor. Methods: A microcontroller and communication technology (NodeMCU) with the ThingSpeak platform is used in the proposed system to view and process the respiratory rate data every 60 s. The total current consumption of the proposed sensor is about 120 mA. Four able-bodied participants were recruited to test and validate the developed system. Results: The results show that the developed sensor and the proposed system can be used to measure and monitor the respiratory rate. Conclusions: The demonstrated system showed applicable, repeatable, and acceptable results.
Rocznik
Strony
art. no. 20200007
Opis fizyczny
Bibliogr. 26 poz., rys., tab.
Twórcy
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
  • Technical Engineering College, Northern Technical University, Mosul, Iraq
Bibliografia
  • 1. El-Gammal A, Phelan E, O’Connor ETM. Chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2019;199:660-8.
  • 2. Masoli M, Fabian D, Holt S, Beasley R. The global burden of asthma: executive summary of the GINA Dissemination Committee Report. Allergy Eur J Allergy Clin Immunol 2004;59: 469-78.
  • 3. Kalyoncu AF, Demir AU, Ozcakar B, Bozkurt B, Artvinli M. Asthma and allergy in Turkish university students: two cross-sectional surveys 5 years apart. Allergol Immunopathol (Madr) 2001;29: 264-71.
  • 4. Zahran HS, Bailey CM, Damon SA, Garbe PL, Breysse PN. Vital signs: asthma in children - United States, 2001–2016. Morb Mortal Wkly Rep 2018;67:149-55.
  • 5. Canora A, Nicoletta C, Ghinassi G, Bruzzese D, Rea G, Capaccio A, et al. First description of the hyperpnea-hypopnea periodic breathing in patients with interstitial lung disease-obstructive sleep apnea: treatment implications in a real-life setting. Int J Environ Res Publ Health 2019;16:1-12.
  • 6. Waugh A, Grant A. Ross and Wilson: anatomy and physiology in health and illness, 12th ed. Amsterdam: Elsevier Ltd; 2014.
  • 7. Folke M, Cernerud L, Ekström M, Hök B. Critical review of noninvasive respiratory monitoring in medical care. Med Biol Eng Comput 2003;41:377-83.
  • 8. Gupta AK. Respiration rate measurement based on impedance pneumography. Texas: Texas Instruments Inc.; 2011. pp. 1-11. Application Report.
  • 9. Strasburger H, Klenk D. Opto-electronic belts for recording respiration in psychophysiological experimentation and therapy. Psychophysiology 1983;20:230-8.
  • 10. Brink M, Müller CH, Schierz C. Contact-free measurement of heart rate, respiration rate, and body movements during sleep. Behav Res Methods 2006;38:511-21.
  • 11. Dodds D, Purdy J, Moulton C. The PEP transducer: a new way of measuring respiratory rate in the non-intubated patient. J Accid Emerg Med 1999;16:26-8.
  • 12. Alamäki H. Measurement of ECG, respiratory rate, tilt and temperature of a patient and wireless Zigbee data transmission. In: 2nd International symposium on medical information and communication technology. ISMICT, Oulu; 2007.
  • 13. Jones L, Deo N, Lockyer B. Wireless physiological sensor system for ambulatory use. In: Proceedings - BSN 2006: international workshop on wearable and implantable body sensor networks. IEEE, New Jersey; 2006.
  • 14. Ayoub MG, Farhan MN, Jarjees MS. Streaming in-patient BPM data to the cloud with a real-time monitoring system. TELKOMNIKA 2019;17:3130-5.
  • 15. Hassanalieragh M, Page A, Soyata T, Sharma G, Aktas M, Mateos G, et al. Health monitoring and management using internet-ofthings (IoT) sensing with cloud-based processing: opportunities and challenges. In: Proceedings - 2015 IEEE international conference on services computing. IEEE, New Jersey; 2015.
  • 16. Dimitrov DV. Medical internet of things and big data in healthcare. Healthcare Inform Res 2016;22:156-63.
  • 17. Amira A, Agoulmine N, Bensaali F, Bermak A, Dimitrakopoulos G. Special issue: empowering eHealth with smart internet of things (IoT) medical devices. J Sens Actuator Netw 2019;8. https://doi.org/10.3390/jsan8020033.
  • 18. Amri I, Atmajati ED, Salam RA, Yuliza E, Munir MM. Potentiometer a simple light dependent resistor-based digital. In: Proceeding - 2016 international seminar on sensors, instrumentation, measurement and metrology (ISSIMM). IEEE, Malang, Indonesia; 2016.
  • 19. Da Silva DF, Acosta-Avalos D. Light dependent resistance as a sensor in spectroscopy setups using pulsed light and compared with electret microphones. Sensors 2006;6:514-25.
  • 20. Shenzhen Ai-Thinker. Microcontroller and communication technology. NodeMCU Datasheet 2019. [Online]. Available from http://wiki.ai-thinker.com/_media/esp32/docs/nodemcu-32s_product_specification.pdf [Accessed 15 Apr 2020].
  • 21. Espressif-Systems. ESP8266EX. ESP8266EX Datasheet; Version 6.4 2020. [Online]. Available from https://www.espressif.com/sites/default/files/documentation/0a-esp8266ex_datasheet_en.pdf [Accessed 15 Apr 2020].
  • 22. Zohari MH, Bala V, Syamimi A, Ghafar A. Server monitoring based on IoT using ThingSpeak. J Electr Power Electron Syst 2019;1:1-4.
  • 23. Russo MA, Santarelli DM, O’Rourke D. The physiological effects of slow breathing in the healthy human. Breathe 2017;13:298-309.
  • 24. De Nardis L, Caso G, Di Benedetto MG. ThingsLocate: a ThingSpeak-based indoor positioning platform for academic research on location-aware internet of things. Technologies 2019;7:50.
  • 25. Gillum RF. From papyrus to the electronic tablet: a brief history of the clinical medical record with lessons for the digital age. Am J Med 2013;126:853-7. https://doi.org/10.1016/j.amjmed.2013.03.024.
  • 26. Raji A, Kanchana Devi P, Golda Jeyaseeli P, and Balaganesh N. Respiratory monitoring system for asthma patients based on IoT. In: Proceedings of 2016 online international conference on green engineering and technologies (IC-GET). IEEE, New Jersey; 2016.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-6ed1a101-ebef-459f-87fe-8ff73a003ce2
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