A Low Cost Baby Incubator Design Equipped with Vital Sign Parameters

Lamidi, Lamidi; Kholiq, Abd; Ali, Muslim

doi:10.35882/ijeeemi.v3i2.3

Cited by 11 publications

(11 citation statements)

References 5 publications

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“…Then the error tolerance reached approximately 0.5°C. This also happened in the previous study, the difference in temperature sensor measurements was only about 0.13-0.182°C with the largest error of the system reaching 0.517% [33] and other studies achieved an error rate of only 0.28% [25]. Then based on other research, the results obtained for the error value were also less than 0.5°C [34]- [36].…”

Section: Discussionsupporting

confidence: 71%

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: Discussionsupporting

confidence: 71%

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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“…This study has three hypotheses. The first hypotheses is that heat loss factors account for the control system performance testing supporting system decision making [9], [37]. The second hypotheses is heat transfer due to negligible radiation [38]- [40], and the third hypotheses is that the fan curves and the interpolations around the setpoint are accurate enough in various operating conditions resulting in the incubator equation as shown on (1) [41].…”

Section: Methodsmentioning

confidence: 99%

An enhancement to the FLC-based baby incubator system using genetic algorithm

Budiyanto,

Silalahi,

Gunawan

et al. 2023

J.INFOTEL

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This research problem focuses on treating premature babies due to hypothermia so that the baby must be put in an incubator for several days. Conventional intensive care method in premature babies, namely skin-to-skin care method between mother and child. Meanwhile, the latest technological developments, the method is already based on electrical-Internet of Things (IoT) engineering. This research proposes the design of an IoT-based prototype known as a smart incubator. This prototype has been equipped with a real-time monitoring system and system settings using the mamdani fuzzy inference system control method and combined using the Genetic Algorithm (GA) method. The results showed that the ideal temperature range in the smart incubator was 33° C with an accuracy of 99.97% and was in accordance with the fuzzy membership degree in the range of 29° C ≤x≤ 37° C. Furthermore, the ideal relative humidity range in the smart incubator was 60% with an accuracy of 98.60% and was in accordance with the fuzzy membership degree in the range of 59 ≤x≤ 65. Then, the noise range in the smart incubator is 37.9dB to 56.8dB with an accuracy of 96.44% and has been appropriate at the fuzzy membership degree. At a maximum distance of 50cm, it takes 8 seconds for the prototype to detect movement as a safety measure.

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“…A baby incubator is specifically designed to protect premature or underweight newborns by creating a stable environment with a temperature similar to that of the womb, thus ensuring the baby's body temperature remains constant. Besides temperature regulation, it is also essential to carefully monitor and maintain the humidity levels within the baby incubator [11].…”

Section: Introductionmentioning

confidence: 99%

Design of Incu Analyzer for IoT-Based Baby Incubator Calibration

Maulani,

Syaifudin,

Maghfiroh

et al. 2024

j.teknokes

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An incubator analyzer, serving as a calibration tool, is utilized to measure diverse parameters such as temperature, mattress temperature, humidity, airflow, and noise in infant incubators. The present study focuses on the development of the Design Incubator Analyzer for IoT (Mattress Temperature and Humidity) with LCD and ThingSpeak display, specifically designed for calibrating baby incubators. The primary objective is to design and develop an Incubator Analyzer as a calibration device for assessing various parameters in infant incubators, encompassing temperature, mattress temperature, humidity, airflow, and noise. The design of this calibration device incorporates a Thermocouple Type-K sensor for baby incubator mattress temperature parameters, a DHT22 sensor for humidity parameters, and an ESP32 microcontroller. The ESP32 processes data from the Thermocouple Type-K and DHT22 sensors to generate values for mattress temperature (TM) and humidity (RH), which are then displayed on LCD and ThingSpeak displays. The device underwent rigorous testing against an established measuring device, the INCU II. In the study, the TM parameter or mattress temperature exhibited the smallest error of -0.0140% at 35°C and the largest error of 0.0584% at 36°C. Concerning the humidity parameter, the largest error was 0.0570% at 32°C, while the smallest error was 0.0207% at 35°C. Overall, the Incubator Analyzer Design for IoT-Based Baby Incubator Calibration device, or IoT-based Incubator Analyzer, demonstrates potential usability following the planning and execution phases, including a thorough review of existing literature. To enhance user experience during the calibration process, an IoT system was developed for data transmission over Wi-Fi, presenting results on the ThingSpeak platform in real-time

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A Low Cost Baby Incubator Design Equipped with Vital Sign Parameters

Cited by 11 publications

References 5 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

An enhancement to the FLC-based baby incubator system using genetic algorithm

Design of Incu Analyzer for IoT-Based Baby Incubator Calibration

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