Development of Monitoring Parameters of Oxygen Concentration, Oxygen Flow Rate, Temperature and Humidity in IoT-Based CPAP Bubble (Oxygen and Humidity Concentration)

  • Ratna Ika Puspitasari D4 AJ Poltekkes Kemenkes Surabaya
  • DYAH TITISARI Department of electromedical engineering poltekkes Kemenkes surabaya
  • Lamidi Lamidi Department of electromedical engineering poltekkes Kemenkes surabaya
Keywords: Bubble CPAP, Oxygen Concentration, Humidity, OCS-3f, DHT 22


Bubble Continuous Positive Airway Pressure (CPAP) is a device to maintain positive pressure in the neonate's airway as long as it can breathe spontaneously. FiO2 percentage, flowmeter, humidifier mode, PEEP depth are parameters that must be set for oxygen therapy using a cpap bubble device, but this tool has minimal monitoring. It has been developed by several previous researchers but has several shortcomings, namely there is no digital result display, no measurement of oxygen rate, oxygen concentration, temperature and humidity. The purpose of this research is to design a parameter monitoring tool on the cpap bubble so that it can monitor the baby's condition in real time and can be used as an indicator of achieving the desired concentration setting. The contribution in this study is a monitoring system or remote monitoring so that nurses and doctors can monitor the baby's condition even though they are not accompanying him. In order to facilitate the process of monitoring and diagnosing patients, a parameter monitoring tool on the cpap bubble based on the Internet of Things is made with notifications on telegrams so that patients can be treated quickly. The design of this tool uses OCS-3f as a sensor for detecting oxygen concentration and DHT22 as a sensor for detecting humidity. The output of oxygen and humidity concentrations is then processed by the ESP32 microcontroller into the ADC pin. Data that has been processed from analog sensor data into digital data on the ESP32 is then sent to the site using the internet network via the wifi module contained in the ESP32 module build-in. In measuring positioned in the settings of 21% to 95%. The largest error value obtained is 4.6% and the smallest is 0.04%.


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[1] D. A. Pfeffer et al., “Quantification of glucose-6-phosphate dehydrogenase activity by spectrophotometry: A systematic review and meta-analysis,” PLoS Med., vol. 17, no. 5, pp. 1–18, 2020, doi: 10.1371/journal.pmed.1003084.
[2] K. A. Mohammad, A. Zekry, and M. Abouelatta, “LED Based Spectrophotometer can compete with conventional one,” Int. J. Eng. Technol., vol. 4, no. 2, p. 399, 2015, doi: 10.14419/ijet.v4i2.4504.
[3] D. A. Suffredini and M. G. Allison, “A Rationale for Use of High Flow Nasal Cannula for Select Patients With Suspected or Confirmed Severe Acute Respiratory Syndrome Coronavirus-2 Infection,” J. Intensive Care Med., vol. 36, no. 1, pp. 9–17, 2021, doi: 10.1177/0885066620956630.
[4] A. Widiatmoko, I. D. Gede, H. Wisana, and T. Rahmawati, “Design and Build of Oxygen Concentration Meter on Bubble CPAP,” no. 8, pp. 182–188, 2019.
[5] P. L. Silva and P. R. M. Rocco, “The basics of respiratory mechanics : ventilator-derived parameters,” vol. 6, no. 19, pp. 1–11, 2018, doi: 10.21037/atm.2018.06.06.
[6] D. C. Lain, R. DiBenedetto, S. L. Morris, A. Nguyen, R. Saulters, and D. Causey, “Pressure control inverse ratio ventilation as a method to reduce peak inspiratory pressure and provide adequate ventilation and oxygenation,” Chest, vol. 95, no. 5, pp. 1081–1088, 1989, doi: 10.1378/chest.95.5.1081.
[7] W. P. King et al., “Emergency ventilator for COVID-19,” PLoS One, vol. 15, no. 12 December, 2020, doi: 10.1371/journal.pone.0244963.
[8] C. Kaur, A. Sema, R. S. Beri, and J. M. Puliyel, “A simple circuit to deliver bubbling CPAP,” Indian Pediatr., vol. 45, no. 4, pp. 312–314, 2008.
[9] T. Abuzairi, A. Irfan, and Basari, “COVENT-Tester: A low-cost, open source ventilator tester,” HardwareX, vol. 9, p. e00196, 2021, doi: 10.1016/j.ohx.2021.e00196.
[10] Y. N. Firdaus, S. Syaifudin, and M. P. A. Tetra Putra, “‘Measuring Oxygen Concentration And Flow In The Ventilator,’” J. Teknokes, vol. 12, no. 1, pp. 27–32, 2019, doi: 10.35882/teknokes.v12i1.5.
[11] N. M. Anggarianto, M. P. A. T. P, S. T. M. Si, and J. T. Elektromedik, “Oxygen Analyzer Equipped With Microcontroller Based Data Storage,” pp. 1–11, 2016.
[12] Z. P. Sullivan, L. Zazzeron, L. Berra, D. R. Hess, E. A. Bittner, and M. G. Chang, “Noninvasive respiratory support for COVID-19 patients: when, for whom, and how?,” J. Intensive Care, vol. 10, no. 1, pp. 1–10, 2022, doi: 10.1186/s40560-021-00593-1.
[13] M. M. Islam, S. Mahmud, L. J. Muhammad, M. R. Islam, S. Nooruddin, and S. I. Ayon, “Wearable Technology to Assist the Patients Infected with Novel Coronavirus (COVID-19),” SN Comput. Sci., vol. 1, no. 6, pp. 1–9, 2020, doi: 10.1007/s42979-020-00335-4.
[14] N. Sianturi, M. Prastawa, and A. Tetra, “Analysis of Input Pressure Differences at CPAP Bubble Output Concentration Show TFT,” vol. 2 no. 1, pp. 1–8, 2020.
[15] J. P. T. Ward, “Oxygen sensors in context,” Biochim. Biophys. Acta - Bioenerg., vol. 1777, no. 1, pp. 1–14, 2008, doi: 10.1016/j.bbabio.2007.10.010.
[16] N. A. A. Bakar, W. M. W. Ramli, and N. H. Hassan, “The internet of things in healthcare: Anoverview, challenges and model plan for security risks management process,” Indones. J. Electr. Eng. Comput. Sci., vol. 15, no. 1, pp. 414–420, 2019, doi: 10.11591/ijeecs.v15.i1.pp414-420.
[17] Taryudi, I. Prasetyo, A. W. Nugraha, and R. S. Ammar, “Health Care Monitoring System Based-on Internet of Things,” J. Phys. Conf. Ser., vol. 1413, no. 1, 2019, doi: 10.1088/1742-6596/1413/1/012008.
[18] T. Juwariyah, L. Krisnawati, and S. Sulasminingsih, “Design of IoT-Based Smart Bins Integrated Monitoring System Using Blynk,” IOP Conf. Ser. Mater. Sci. Eng., vol. 1125, no. 1, p. 012078, 2021, doi: 10.1088/1757-899x/1125/1/012078.
[19] M. Bogdan, “How to Use the DHT22 Sensor for Measuring Temperature and Humidity with the Arduino Board,” ACTA Univ. Cibiniensis, vol. 68, no. 1, pp. 22–25, 2016, doi: 10.1515/aucts-2016-0005.
[20] I. A. Abdulrazzak, H. Bierk, and L. A. Aday, “Humidity and temperature monitoring,” Int. J. Eng. Technol., vol. 7, no. 4, pp. 5174–5177, 2018, doi: 10.14419/ijet.v7i4.23225.
[21] G. National and H. Pillars, “ARDUINO MEGA,” vol. 2560.
[22] E. S. Muhammad Khosyi’in , Agus Suprajitno, “Volume Counter and Oxygen Usage Timer,” Vol. Count. Oxyg. Usage Timer, vol. d, pp. 1–8, 2017.
[23] A. Nurrrahmawati and H. Harmadi, “Design and Build of a Measuring Tool for Oxygen Concentration Produced by a Photobioreactor of Microalgae Chlorella vulgaris Using the SK-25F Sensor,” J. Phys. Unand, vol. 6, no. 3, pp. 255–262, 2017, doi: 10.25077/jfu.6.3.255-262.2017.
[24] M. Bar, “Oxygen Sensor Holder,” no. 3903306, p. 3903306.
[25] F. Duprez et al., “Accuracy of Medical Oxygen Flowmeters: A Multicentric Field Study,” Health (Irvine. Calif)., vol. 06, no. 15, pp. 1978–1983, 2014, doi: 10.4236/health.2014.615232.
[26] L. Aditya and R. d. Wahyuni, “Design and Build a Non Invasive Oxygen Level Measuring Device Using a Max30100 Sensor,” Electrokrisna Sci. J., vol. 8, no. 3, pp. 62–69, 2020.
[27] U. Thome, A. Töpfer, P. Schaller, and F. Pohlandt, “The effect of positive endexpiratory pressure, peak inspiratory pressure, and inspiratory time on functional residual capacity in mechanically ventilated preterm infants,” Eur. J. Pediatr., vol. 157, no. 10, pp. 831–837, 1998, doi: 10.1007/s004310050946.
How to Cite
R. Puspitasari, D. TITISARI, and L. Lamidi, “Development of Monitoring Parameters of Oxygen Concentration, Oxygen Flow Rate, Temperature and Humidity in IoT-Based CPAP Bubble (Oxygen and Humidity Concentration)”, Jurnal Teknokes, vol. 16, no. 2, Jul. 2023.
Biomedical Engineering