Analysis of Changes in Flow Setting Against Rise Time Using Gas Board 7500E Sensor on Bubble CPAP

Respiratory distress syndrome (RDS) is a breathing disorder that occurs in newborns, often in premature babies born before 28 weeks of gestation. The bubble CPAP (Continuous Positive Airways Pressure) is a device used to provide positive pressure to newborns who can breathe spontaneously but are still prone to apnoea. The rise time is the time it takes for the airway pressure to reach the maximum standard value. The aim of this study is to analyze the changes in flow regulation during the rise time using a 7500E gas sensor card on a bubble CPAP probe. The method used in this study is to use the mean hijacking of the sensor to reduce the noise generated by the sensor. When analyzing the data, the researcher recorded data up to five times and calculated the mean measurement error. The research design is calibrated to confirm the correctness of the displayed values. The results of the data analysis are a mean error value of 0.88% at a setting of 30% oxygen content, 0.78% at a setting of 50%, and 0.95% at a setting of 90%. For liters per minute (LPM) at the 1 LPM and 5 LPM settings, the mean error values are 0.18 % and 0.03 % for the 10 LPM setting. From the test results with 3 bubble CPAP devices, it appears that when a high LPM setting is used, the oxygen concentration is reached faster with a mean value of ±10 seconds. The conclusion from this study shows that increasing the oxygen flow rate affects the duration of the rise in bubble CPAP oxygen concentration. The implication of this study is that this data will help add artificial intelligence to bubble CPAP to automatically determine settings by combining breathing data from patients.

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Publication Details

Journal
Indonesian Journal of Electronics Electromedical Engineering and Medical Informatics
Published
2025-08-17
DOI
https://doi.org/10.35882/ijeeemi.v4i2.143
Primary Topic
Fluid Dynamics and Mixing
Type
article
Field-Weighted Citation Impact
0.00
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article

Analysis of Changes in Flow Setting Against Rise Time Using Gas Board 7500E Sensor on Bubble CPAP

Shubhrojit Misra, Andjar Pudji, Lamidi Lamidi, Yenda Mita Barus et al.
Indonesian Journal of Electronics Electromedical Engineering and Medical Informatics
Fluid Dynamics and Mixing
article

Analysis of Changes in Flow Setting Against Rise Time Using Gas Board 7500E Sensor on Bubble CPAP

Shubhrojit Misra, Andjar Pudji, Lamidi Lamidi, Yenda Mita Barus, Sari Luthfiyah, Nur Hasanah Ahniar, Farid Amrinsani, Lusiana Lusiana
article en

Abstract

Respiratory distress syndrome (RDS) is a breathing disorder that occurs in newborns, often in premature babies born before 28 weeks of gestation. The bubble CPAP (Continuous Positive Airways Pressure) is a device used to provide positive pressure to newborns who can breathe spontaneously but are still prone to apnoea. The rise time is the time it takes for the airway pressure to reach the maximum standard value. The aim of this study is to analyze the changes in flow regulation during the rise time using a 7500E gas sensor card on a bubble CPAP probe. The method used in this study is to use the mean hijacking of the sensor to reduce the noise generated by the sensor. When analyzing the data, the researcher recorded data up to five times and calculated the mean measurement error. The research design is calibrated to confirm the correctness of the displayed values. The results of the data analysis are a mean error value of 0.88% at a setting of 30% oxygen content, 0.78% at a setting of 50%, and 0.95% at a setting of 90%. For liters per minute (LPM) at the 1 LPM and 5 LPM settings, the mean error values are 0.18 % and 0.03 % for the 10 LPM setting. From the test results with 3 bubble CPAP devices, it appears that when a high LPM setting is used, the oxygen concentration is reached faster with a mean value of ±10 seconds. The conclusion from this study shows that increasing the oxygen flow rate affects the duration of the rise in bubble CPAP oxygen concentration. The implication of this study is that this data will help add artificial intelligence to bubble CPAP to automatically determine settings by combining breathing data from patients.

Indonesian Journal of Electronics Electromedical Engineering and Medical InformaticsVol. 4(2)
Jadavpur University (IN), Universitas Negeri Surabaya (ID), Institut Kesenian Jakarta (ID)
Openalex Percentile: Top 80%
Fluid Dynamics and Mixing
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