Long Distance Dual SpO2 Monitoring in Premature Babies Via Bluetooth Communication

Nugraha, Priyambada Cahya; Mak’ruf, Muhammad Ridha; Lusiana, Lusiana; Luthfiyah, Sari; Caesarendra, Wahyu

doi:10.35882/jeeemi.v3i2.7

Cited by 3 publications

(3 citation statements)

References 9 publications

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“…Based on M. Syahrul Azam [25], the results of his research obtained the error value of the highest SpO2 sensor of 0.68% and the smallest 0.17%. While other similar studies stated the error value in the range of 0.0123% [26], 1% [27], >3% [28], 0.38% [29], 0.81% [30], 1% [31], and other study revealed deviation value approximately 1.62% [32].…”

Section: Discussionmentioning

confidence: 79%

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Fauzi,

Maharesi,

Setiyadi

2023

Journal of Robotics and Control

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Hypothermia is a drop in body temperature below 36.5°C in newborns. It results in an internal distribution of body heat from the nucleus to the periphery, followed by heat loss greater than metabolic production. Hypothermia is one of the factors predisposing to metabolic disorders, intracranial hemorrhage, respiratory distress, and Necrotizing enterocolitis. Hypothermia problems can be treated with infant warmers. Thus, the need for a infant warmer is considered to improve survival in newborns. This study aims to improve the accuracy of temperature monitoring, increase security, and enable remote monitoring. The temperature sensor of the device is calibrated with comparable devices such as Incubator Analyzer and Thermo hygrometer while the SpO2 sensor is calibrated with Spotlight SpO2 Functional Tester and Thermo hygrometer. Achievement and validation of temperature and oxygen saturation use a calibration comparison tool. The results of the temperature sensor measurements, including air temperature and skin sensor temperature, namely: air temperature error tolerance ≤2°C and skin sensor temperature error tolerance ± 0.5 ° C. All two indicators have the same standard deviation value of ±0.49. The SpO2 indicator reached an error tolerance value of ± 1% O2 with a standard deviation value of ± 0.6-0.9 from six trials. Then the pulse rate indicator obtained an error tolerance of ±5% with a standard deviation value of ±0.6. The smart infant warmer tool provides benefits to avoid excessive heat from the heater and minimize low temperatures that cause hypothermia through the Internet of Things technology. Furthermore, this research can be improved with machine learning technology to increase efficiency and effectiveness in patient treatment.

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Section: Discussionmentioning

confidence: 79%

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Fauzi,

Maharesi,

Setiyadi

2023

Journal of Robotics and Control

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“…Births that occur between 38 and 40 weeks of pregnancy and with babies weighing between 2500 and 4000 grams are considered full-term [1][2][3][4] [5]. Premature birth is a risk factor for infant mortality [6]because to the vulnerability of premature babies' bodies to harm and their immature organ systems such the lungs, heart, kidneys, liver, and digestive tract [7] [8]. Therefore, further precautions must be taken, such as recreating the conditions of the womb in terms of temperature, humidity, and oxygen levels.…”

Section: Introductionmentioning

confidence: 99%

Monitoring Baby Incubator Central through Internet of Things (IoT) based on Raspberry Pi Zero W with Computer Monitoring)

Ningsih,

Irianto,

Lamidi

et al. 2023

Indones.J.electronic.electromed.med.inf

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Premature infants, with a gestational age of 37 weeks or less and weighing less than 2500 grams, face challenges in adapting to the outside world due to the underdeveloped state of their organ systems. Special care is essential to support their growth and development, including maintaining optimal temperature, humidity, and oxygen levels similar to those experienced in the mother's womb. Baby incubators play a crucial role in providing these conditions. This study aims to develop a convenient monitoring tool for midwives and healthcare workers responsible for multiple baby incubators. The tool operates independently and is compatible with various brands of baby incubators. Leveraging an IoT system, it utilizes ESP32 and Raspberry Pi Zero W modules for data transmission. The tool incorporates a DS18B20 sensor for monitoring skin temperature and a DHT22 sensor for monitoring the temperature inside the incubator chamber. Using a pre-experimental design with an after-only research design, the tool's measurements are compared against an incubator analyzer. The study reveals that the developed module still exhibits some measurement errors. However, despite these limitations, the research is expected to greatly assist medical personnel in simultaneously monitoring multiple baby incubators. Keywords : Premature infants, Baby incubators, IoT, Temperature, ESP32, Raspberry Pi Zero W

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“…Then the last one was developed by Azkiyak et al and other studies; this device is already portable using an Android display and is equipped with storage. However, there are still shortcomings, namely errors that still exceed 5% [13]- [17]. The biggest error on the DS18B20 sensor is 4.33325%, while the biggest error on the K-type Thermocouple temperature sensor is 7.3138%.…”

Section: Introductionmentioning

confidence: 99%

INCU Analyzer for Infant Incubator Based on Android Application Using Bluetooth Communication to Improve Calibration Monitoring

et al. 2022

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Worldwide, over 4 million babies die within a month of birth each year. Of these, 3.9 million are in developing countries. A proportion approximately 25% of these deaths are due to complications of premature birth, most commonly inadequate thermoregulation, water loss, and neonatal jaundice. An infant incubator provides stable temperature, relative humidity, and airflow values. A periodical calibration should be applied on infant incubator to monitor the functionality. The study aims to develop a calibration device that measures temperature, humidity, airflow, and noise in the baby incubator based on an Android application with Bluetooth communication to improve the calibration monitoring process. This is to achieve a better performance of the conventional INCU analyzer. The contribution of this research is that the values of the temperature, humidity, airflow, and noise can be displayed on both devices, the INCU analyzer machine, and mobile phone; thus, the user can monitor the measurement activities wirelessly. Furthermore, the statistical calculation for all measurements can be saved on a mobile phone device. The main design consists of temperature sensor LM35, humidity sensor DHT22, airflow sensor MPX5010DP, an analog signal conditioning circuit, an Arduino Mega microcontroller, Bluetooth module HC05, and Android mobile phone. The resulting design was compared to the standard or calibrator INCU analyzer machine (Fluke Biomedical INCU II). This study found that the smallest error is -1.72%°C, -0.106 % RH, -1.727% dB, and <0.1% m/s for temperature, humidity, noise, and airflow parameters, respectively. After the evaluation process, this device can be used as an INCU analyzer to calibrate the infant incubator.

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Long Distance Dual SpO2 Monitoring in Premature Babies Via Bluetooth Communication

Cited by 3 publications

References 9 publications

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Implementation of IoT of an Electric Infant Warmer to Prevent Hypothermia in Newborns

Monitoring Baby Incubator Central through Internet of Things (IoT) based on Raspberry Pi Zero W with Computer Monitoring)

INCU Analyzer for Infant Incubator Based on Android Application Using Bluetooth Communication to Improve Calibration Monitoring

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