• International Journal of Technology (IJTech)
  • Vol 14, No 4 (2023)

Baby Incubator with Overshoot Reduction System using PID Control Equipped with Heart Rate Monitoring Based on Internet of Things

Baby Incubator with Overshoot Reduction System using PID Control Equipped with Heart Rate Monitoring Based on Internet of Things

Title: Baby Incubator with Overshoot Reduction System using PID Control Equipped with Heart Rate Monitoring Based on Internet of Things
Bambang Guruh Irianto, Anita Miftahul Maghfiroh, Moh Sofie, Abd Kholiq

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Published at : 28 Jun 2023
Volume : IJtech Vol 14, No 4 (2023)
DOI : https://doi.org/10.14716/ijtech.v14i4.5678

Cite this article as:
Irianto, B.G, Maghfiroh, A.M., Sofie, M., Kholiq, A., 2023. Baby Incubator with Overshoot Reduction System using PID Control Equipped with Heart Rate Monitoring Based on Internet of Things. International Journal of Technology. Volume 14(4), pp. 811-822

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Bambang Guruh Irianto Departement of Electromedical Enginering, Politeknik Kesehatan Kemenkes Surabaya, Jalan Pucang Jajar Tengah No.56, Surabaya 60282, Indonesia
Anita Miftahul Maghfiroh Departement of Electromedical Enginering, Politeknik Kesehatan Kemenkes Surabaya, Jalan Pucang Jajar Tengah No.56, Surabaya 60282, Indonesia
Moh Sofie STIKES Semarang, Jalan kolonel warsito sugiarto km 2,5 Sadeng GunungPati, Semarang 50222, Indonesia
Abd Kholiq Departement of Electromedical Enginering, Politeknik Kesehatan Kemenkes Surabaya, Jalan Pucang Jajar Tengah No.56, Surabaya 60282, Indonesia
Email to Corresponding Author
Abstract
Baby Incubator with Overshoot Reduction System using PID Control Equipped with Heart Rate Monitoring Based on Internet of Things

Factors causing premature infant mortality include the lack of simple care and inadequate equipment such as a baby incubator. Premature babies are very susceptible to heart disorders, including congenital heart defects. Congenital heart defects can cause a fetus to be born prematurely. The current research related to this matter was further conducted, aiming to develop a baby incubator with an overshoot reduction system specifically for babies with heart defects that can be monitored remotely using an IoT system. In this study, the AHT 10 sensor was used for room temperature sensing in the baby incubator. Temperature control was achieved using a closed-loop PID system. In this case, the monitoring of the baby's heart rate employed leads II to tap the heart's electrical signal. Data transmission consisted of temperature readings, ECG signals, and heart rate. The microdata was processed into digital data, which were then sent via the Raspberry Pi, then sent via the internet to access the cloud firebase. After that, the firebase data were downloaded from an Android system. The performance results showed that in the temperature test, the error value was below 5%, and the PID control made can reduce the overshoot temperature by no more than 5%. In addition, it was also determined that the steady-state error value was 2%. T-Test statistical test on the ECG signal further obtained a p-value > 0.05. Furthermore, the data transmission test using IoT did not find data loss when sending the data, and the minimum speed required for data transmission was 5 kbps. This research further implied that the user or the patient's family could easily monitor the baby's development anywhere and anytime.

Baby incubator; ECG signal; Heart rate; IoT; Temperature

Introduction

    Approximately 15 million and one million premature babies died yearly (Lawn et al., 2013) because of the gap in survival between high and low-income countries. In this case, premature babies are born before 34 weeks of gestation (Kvalvik et al., 2020). According to UNICEF, premature births in Indonesia ranked fifth with 13,370 premature babies on January 18, 2018 (Utomo et al., 2021). Many premature babies died due to a lack of simple care and adequate equipment, such as incubators (Shaib, Hamawy, and Majzoub, 2017). The incubator is a medical treatment tool for premature babies that provides warmth, humidity, and oxygen as newborns require in controlled conditions (Janney et al. 2018). In addition, premature babies are also very susceptible to heart disorders, and even congenital heart defects can cause the fetus to be born prematurely (Kanalikova 1990).
    The heart condition of premature babies has also been studied by several researchers, as described previously (Hubsher, 1961). Stoermer found that the interval for various components of the ECG time is somewhat shorter, and the P waves are higher and sharper. In this case, the frequently small waves and deviations were from the S-T segment. This explanation indicates that premature babies do not only need a controlled room but also need monitoring of heart conditions to detect congenital abnormalities or not (Sattar and Lovely, 2021). Therefore, there is a great need for equipment that can treat premature babies and those with heart defects efficiently and non-invasively. Premature babies are placed in a special room called the Neonatal Intensive Care Unit (NICU). The treatment provided in the NICU room is adjusted to the needs of the baby, including the need for incubators, blue light therapy, infusions, and heart and lung monitors.
    In addition, the room temperature in the baby incubator must be controlled according to the specified standard  so that the baby still gets warmth, moisture, and oxygen as what they get in the womb. Several researchers have made a temperature control system for baby incubators using PID control (Maghfiroh et al., 2022; Kirana et al, 2021; Theopaga, Rizal, and Susanto, 2014). This system is considered to control the temperature well and suppress excessive temperature overshoot levels so that premature babies get warm according to standards. Widhiada et al. (2019a) made a baby incubator using a fuzzy logic control system with two measurement conditions. The first measurement is without load, and the second measurement uses a baby simulation with a load of 2 kg. The resulting overshoot value was less than 5% (Widhiada et al., 2019a). However, in using this fuzzy system, the variables entered were only based on the researcher's experience, so further system testing is necessary. (Sinuraya and Pamungkas, 2019) further used the DHT11 sensor for sensing elements using a fuzzy-PI adaptive control system, resulting in its ability to suppress overshoot according to the setpoint within 200 seconds with an error of 5% (Sinuraya and Pamungkas, 2019). However, the computation of this system was quite heavy. A closed-loop control system was further designed and implemented by Mathew and Gupta et al. to regulate temperature, humidity, light level, and oxygen in infant incubators (Mathew and Gupta, 2015). This system was quite effective in maintaining the temperature from the threshold value limit. However, the threshold value was still set manually using the potentiometer.
    Another research project applied the principle method of natural circulation and natural convection in the baby incubator, whose main components were a lamp as a heater and a digital thermostat as a temperature control (Zaelani et al., 2019). This system was quite good and stable only if the baby incubator was at ambient temperature. Along with the needs of premature babies, several researchers have also developed a baby incubator design with several functions. Fadilla et al. (2020) has made a baby incubator with a multi-function system that could warm and treat jaundiced babies and can soothe crying babies, and could be reached remotely using the IoT system (Fadilla et al., 2020; Agresara, Vyas and Bhensdadiya, 2017). Luthfiyah et al. (2021) also applied the telemedicine system to monitor the temperature of the baby incubator using a WiFi network (Luthfiyah et al., 2021). In addition, the IoT system has also been created by several researchers to monitor babies remotely (Muosa, 2017; Nachabe et al., 2015). The use of the IoT system for nurses makes it easier to monitor the temperature of the baby incubator (Koli et al., 2018). However, in this study, the temperature sensor used was less accurate, so it needed a more accurate sensor for sensing heat in the baby incubator room.
    Based on several previous studies that have been mentioned, researchers have not found the development of a baby incubator specifically for babies who have heart defects and an overshoot reduction system at the temperature of the baby incubator. Therefore, this study aimed to meet the needs of premature babies with heart problems by combining several systems with lower costs and more efficiency. The system worked on in this research was temperature control with a PID control using an AHT10 sensor. This PID control was chosen because it was considered capable of suppressing the temperature overshoot value of less than 5% (Widhiada et al., 2019b). Several researchers have also tried another several control methods (Abdurrakhman et al., 2020), and the test results obtained could also be used as a reference for the researcher to develop a control method (Rahman, Ihsan, and Hassan, 2022). The designed baby incubator was also equipped with baby heart rate monitoring with a telemedicine system using the internet of things. It was expected that by combining the system, the costs incurred by patients would be lower because the baby incubator used was equipped with a premature baby heart rate monitoring system. The IoT system used was also expected to monitor the baby's condition anywhere and anytime. So that doctors, nurses, and parents of patients were easier and more efficient in finding out the baby's condition and the temperature in the baby incubator in real-time (Ashish, 2017).

Experimental Methods

2.1. System Design and System Control

    The overall system is described in Figure 1. In this study, the AHT 10 sensor was used for room temperature sensing in the baby incubator. The temperature control used a PID control with a closed loop that was given interference in the baby incubator, which was likened to when the temperature of the incubator room was stable. In this case, the new baby was put by the nurse, so the door of the baby incubator box opened for a few minutes which resulted in a disturbance in temperature reading.



Figure 1 The design of baby incubator. The input ECG signal is amplified by an instrument amplifier circuit so that it can be read by the microcontroller, the instrument output is filtered with HPF and LPF filters with a bandwidth frequency of 0.05 Hz-100Hz. The signal output will be displayed on the LCD display and sent via android
    The block diagram of the PID control is described in Figure 2. In this case, monitoring the baby's heart rate used lead II as the heart's electrical signal tapping (Utomo, Nuryani, and Darmanto, 2017). The electrode output from lead II was amplified with an instrument amplifier with a gain of 100 times to eliminate noise interference or other artifacts. A filter was made according to the heart signal frequency, namely 0.05Hz-100Hz. The microcontroller output in the form of an electrocardiogram signal and the room temperature of the baby incubator sent via Resbery Pi from Resbery Pi will be received by the web server using a firebase. Furthermore, the data were sent to the Android phone. In this case, the Android display used the MIT App application, which must be installed first on a cellphone with an android system.


Figure 2 The design of PID control, setting the temperature as an input to the microcontroller then a closed loop system is used in this method to control the room temperature on the baby incubator by using the AHT10 sensor to sense the room
The PID control is based on Equation 1 and Equation 2 (Ang, Chong, and Li, 2005):


Where Kp is the proportional gain, Ki is the integral gain and Kd is the derivative gain, Ti is the integral time constant, and Td is the derivative time constant.
For a PID control with disturbances described in Equation 3 (Ogata, 2005). 

Where CD(s) is the response to disturbance, D(s) is the interference effect test.

The response to the reference input R(s) was assumed to be a zero disturbance. Then the response CR(s) to the reference input R(s) was obtained based on Equation 4 (Ogata, 2005).

Simultaneous application of the responses of the reference and perturbation inputs was obtained by adding up the two individual responses. Due to the application of the simultaneous C(s) response of the reference input R(s) and the disturbance D(s), it was obtained according to Equation 5 (Ogata, 2005).


In the PID system, the control system control process applied the appropriate selection of Kp, Ki, and Kd in order to provide satisfying closed-loop performance. These parameters must be chosen properly so that the system's stability is satisfactory, including the response speed and the right level of overshoot. The system's transfer function was based on Equation 6 (Nayak and Singh, 2015).

Where the selection of Kp, Ki, and Kd was applied to the proper control for closed-loop performance.
2.2. Data Acquisition ECG Signal 
      The ECG signal was obtained from the heart's electrical leads on Lead II. In this study, an ECG instrument was designed with a filter that was adjusted to the frequency of the heart signal, namely 0.05 Hz - 100 Hz. The designed ECG instrument is described in Figure 3. The amplitude of the ECG signal at the electrode output was still very small, namely 0.1 mV – 0.3 mV, so an instrument amplifier was needed. In this study, ICAD620 was used with 100 times the gain based on Equation 7 (Maghfiroh, Arifin, and Sardjono, 2019).

Figure 3 ECG instrumentation. Output electrode is amplified by instrument amplifier (100x) gain then filtered to remove noise with a bandwidth of 0.05-100Hz

As for getting the ECG signal in this study, a filter was designed with an HPF cut-off frequency of 0.05Hz and an LPF cut-off frequency of 100Hz. As for getting the cut-off frequency bandwidth value for HPF was based on Equation 8 (Maghfiroh, Arifin, and Sardjono, 2019).

The Sullen-Key topology method was used for order 2 LPF circuits. Value a1 = 1.8478; b1 = 1.0000; a2 = 0.7654; and b2 = 1.0000 were Butterworth coefficients for order 2. The first-order low pass filter can be calculated by Equations 9 and 10 with a value of C1 = 47 nF.

2.3. Data Collection
    In this study, the temperature test process used the INCU analyzer INCU 2 of the Fluke brand as a comparison of temperature readings with five temperature measurement points placed at points T1, T2, T3, T4, and T5, as described in Figure 4. In this case, the measurements were taken at a temperature setting of 35oC, 36oC, and 37oC. Each point was measured 6 times so that the error value of the baby incubator was obtained. Meanwhile, to test the ECG signal in this study, the Fluke Phantom ECG brand was used as a simulation of the baby's heartbeat, as described in Figure 5.

Figure 4 Temperature test using the Incu Analyzer type INCU 2 Brand Fluke, with five temperature parameters namely T1, T2, T3, T4 and T5 which are placed as shown in the picture