Journal of Electronics, Electromedical Engineering, and Medical Informatics

Journal Information
ISSN / EISSN : 2656-8632 / 2656-8632
Published by: Poltekkes Kemenkes Surabaya (10.35882)
Total articles ≅ 77
Current Coverage

Latest articles in this journal

Arrum Sekarwati, Syaifudin Syaifudin, Torib Hamzah, Shubhrojit Misra
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 135-143;

Infant incubators are equipment to maintain a stable body temperature for premature babies. Premature babies need room conditioning that is close to conditions in the womb. Room conditioning is carried out in a baby incubator by providing a stable temperature, relative humidity, and measured air flow. This parameter must be controlled so as not to exceed the threshold that will harm the baby. Periodic calibration should be applied to the infant incubator to monitor its function. To ensure the availability of baby incubators according to service standards, it is necessary to conduct test (calibrate) using an incubator analyzer. The purpose of this study is to conduct further research on the incubator analyzer that focuses on discussing the accuracy of noise and airflow sensors with the gold standard. In this study, an experiment was carried out for the sensitivity level of several sensors that had been treated by giving treatment to sensors to choose sensors with good sensitivity to be assembled into one in the incubator analyzer module. The noise sensors (KY-037 and Analog Sound Sensor V2.2) were further compared with the values ​​on the sound level meter and the airflow sensor (D6F-V03A1) was compared with the anemometer. Sensors whose values ​​are close to the comparison values ​​were selected to be integrated into the incubator analyzer module. The incubator analyzer module used Arduino Mega2560 as a data processor and was equipped with an SD Card for the data storage. The built incubator analyzer module was also compared to the Fluke INCU II gold standard for data analysis. The results showed that the Analog Sound Sensor V2.2 had the highest error value (-4.6%) at 32°C and the D6F-V03A1 had the ability to measure sensitivity, where the results were more accurate than INCU II. Based on the error value of the noise sensor, the V2.2 sensor can be applied to measure noise in the baby incubator and the D6F-V03A1 airflow sensor produced an accuracy of up to 3 digits behind the comma which is more accurate than the standard module. The results of the INCU analyzer from this study can be used to calibrate the baby incubator, so that the certainty of the feasibility of the baby incubator is guaranteed. This research can be used as a reference for other researchers who will develop research on incubator analyzers in the future.
Yunik Pujiastuti, Andjar Pudji, Singgih Yudha Setiawan, Farid Amrinsani, Khongdet Phasinam
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 144-153;

A thermometer is a medical device used to measure body temperature. To maintain the accuracy of the thermometer measurement results, periodic calibration is required. Calibration is an activity to determine the conventional correctness of the indicator values of measuring instruments and measuring materials by comparing them with measurement standards that can be traced to national and international standards for units of measure and/or international and certified reference materials. Based on the results of the identification of chronological problems that have been observed, a body thermometer that measures body temperature is needed so and a calibrator is needed to maintain the accuracy of the thermometer. The purpose of this study was to analyze the Temperature Stability and Accuracy of the Body Thermometer Calibrator Based on on-Off Control and Fuzzy Logic Control. The contribution of this research to this tool will use the development of a fuzzy logic control method to produce temperature stability in the Body Thermometer Calibrator (Digital). The method used in this study used fuzzy control and on-off control. The results of this study from the suitability test obtained a maximum error of 0.2% in the fuzzy control and 0.6% in the On-Off control. The average rise time difference for the two controls was 13.53 Seconds. The average settling time difference is 130.46 seconds. The results of this study can be concluded that the Fuzzy System is better than the On / Off system so the Fuzzy system is more suitable for thermometer calibration media.
Anggara Trisna Nugraha, Reza Fardiyan As'Ad, Adianto, Vugar Hacimahmud Abdullayev
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 170-177;

Distribution panel is equipment that functions to receive electrical energy from PLN and subsequently distributes, as well as controls the distribution of electrical energy through the main and branch panel circuits to branch Distribution Panel or directly through the final load circuit. One of the problems with the Distribution Panel is the occurrence of fluctuating voltage changes and disturbances caused by condensation due to high humidity values. Based on previous research, the solution to minimize this problem is by optimizing the temperature and humidity on the Distribution Panel. So, in this research, we examine the effect of fan and heater control on the temperature and humidity of the Distribution Panel. The aim of this research is to fabrication the prototype that can be prevent the presence of excess temperature and humidity that does not meet applicable standards. So that it is expected to minimize the occurrence of hazards due to excessive temperature and humidity. In this research, it was found that the fan control using the fuzzy method can change the temperature of the panel room from 42.06oC to 32.82oC in a period of 440 seconds. However, the fan control with simple logic can only change the temperature of the panel room which is all 42.22oC to 35.05oC in 440 seconds. So it can be concluded that the fan control with the fuzzy method can reduce the temperature faster than the fan control with simple logic. Based on the graph on the panel room temperature stability test, it was found that the level of temperature stability in the room could be better controlled with fan control with the fuzzy method than using fan control with simple logic. Heater control system can reduce humidity levels from 95.14%RH to 55.25%RH within 160 seconds.
Wahyu Pratama, Muhammad Ridha Mak'Ruf, Tri Bowo Indrato, Endro Yulianto, Lamidi Lamidi, Maduka Nosike, Sambhrant Srivastava
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 161-169;

Radiation cannot be felt directly by the five human senses. For the occupational safety and security, a radiation worker or radiographer is endeavored to receive radiation dose as minimum as possible, which is by monitoring the radiation using a radiation measuring device. The purpose of this study was to analyze the effect of collimation area and irradiation distance on x-ray dose measurement using Geiger Muller. In this case, the author tried to make a dosimeter by using the Muller Geiger module and displayed it on a personal computer. This research employed Muller Geiger sensor to detect X-ray dose and velocity, Arduino for data programming, Bluetooth HC-05 for digital communication tool between hardware and personal computer, and personal computer to display the reading. Current research was conducted using Pre-Experimental research design. Based on the results of data collection and comparison with the standard tool, it can be concluded that the greater the tube current setting (mA), the greater the dose and rate of radiation exposure at a distance of 100cm with 50KV and 70KV settings, and a distance of 150cm with 50KV settings. However, it is inversely proportional to the measurement results at a distance of 150cm with a 70KV setting. The results of this study are further expected to determine the ability of Geiger Muller to measure the dose to the irradiation distance or collimation area and can be used as a reference for further research in this field.
Irgi Achmad, Anggara Trisna Nugraha
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 154-160;

Electricity is one of the basic needs of modern human life and is already so integrated into everyday life. This is understandable given the coal's ample resources. Another factor that influences the growth of coal use is that coal plants are designed asa basic burden because the price of coal is relatively cheaper. However, coal's existence as fuel for power plants is on the decline and is not renewables. One of the applications of renewable energy potential is solar power generation technology. On this system using solar panels using 30 wp power. Solar dependence on the environment affects the change in output values in hybrid plant systems, resulting in easy damage to both domestic and industrial appliances or in battery storage systems, so a mechanism is needed to stabilize the output voltage supplied to the battery or load. So, out of this renewable energy potential, it creates innovation Implementation of Voltage Stabilizers on Solar Cell System Using Buck-Boost Converter. Aided by current and voltage sensors controlled by arduino uno so that they can insulate input and output from buck-boost converter. Results from the testing of this device indicate that the buck-boost converter is able to stabilize output output from solar panels with a 14.4 volt set of points. The average efficiency obtained at buck-converter converter testing at buck mode is 85.4 %. On boost mode is 80%. On buck-boost mode is 79.2%.
Abdi Wibowo, Triana Rahmawati, Priyambada Cahya Nugraha, I Dewa Gede Hari Wisana, Honey Honey, Mansour Asghari
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4;

Calibration is an activity to determine the conventional correctness of the value of measuring instrument designation and measuring material by comparing against the measuring standards that are traced to national or international standards. A sphygmomanometer is a device used to measure blood pressure. Suction pump is a tool to suck various types of fluid formed from the body's secretion process that under certain conditions need to be cleaned. DPM (Digital Pressure Meter) is a tool for calibrating sphygmomanometers and suction pumps. Therefore, it takes a calibrator device to calibrate both tools. The purpose of this study was to determine the sensor response and analyze the accuracy of the design of a dual pressure calibrator (+ and -) that can be used for two devices at once (sphygmomanometer and suction pump) using one sensor (pss-C01V-R18 autonics). The research was conducted at the Campus of the Department of Electrical Engineering Of The Ministry of Health Surabaya, first the data was taken from three different brands of sphygmomanometer and suction pump, the second data was taken using module calibrators, and the third data collection from modules and comparison tools (DPM). In this study successfully measured positive and negative pressure with autonics sensors, the results obtained are accurate in accordance with the results of standard tools. The result of this tool can be used for dual pressure calibrators using autonics sensors.
Fahmi Ivannuri, Anggara Trisna Nugraha
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 178-182;

Energy needs in Indonesia in particular and in the world in general continue to increase. One of the sources of electricity supply, PLTA together with steam power plants (PLTU) and gas power plants (PLTG) indeed play an important role in the availability of electricity. Indonesia, which is an archipelagic country and one of the countries located on the equator, is a factor that Indonesia has abundant wind energy potential. The electrical energy needs of remote communities can be met. Turbine ventilator is a device that functions to circulate air which is placed on the roof of the building that functions as ventilation in residential and industrial buildings. Based on previous research, there are those who examine the use of turbine ventilators as power plants, but there are still many shortcomings that need to be fixed. turbine ventilator that is used to catch the wind and drive the generator, by connecting the wind turbine using a v-belt so that the rotation produced by the generator is maximized. Then the generator produces electrical energy.
Saurav Mishra
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 115-134;

Heart Failure, an ailment in which the heart isn’t functioning as effectively as it should, causing in an insufficient cardiac output. The effectual functioning of the human body is dependent on how well the heart is able to pump oxygenated, and nutrient rich blood to the tissues and cells. Heart failure falls into the category of cardiovascular diseases - the disorders of the heart and blood vessels. One of the leading causes of global deaths resulting in an estimated 17.9 million deaths globally every year. The condition of heart failure results out of structural changes to the cardiac muscles majorly in the left ventricle. The weakened muscles cause the ventricle to lose its ability to contract completely. Since the left ventricle generates the required pressure for blood circulation, any kind of a failure condition results in the reduction of cardiac power output. This study aims to conduct a thorough survival analysis and survival prediction on the data of 299 patients classified into the class III/IV of heart failure and diagnosed with left ventricular systolic dysfunction. Survival analysis involves the study of the effect of a mediation assessed by measuring the number of subjects survived after that mediation over a period of time. The time starting from a distinct point to the occurrence of a certain event, for example death is known as survival time and the corresponding analysis is known as survival analysis. The analysis was performed using the methods of Kaplan-Meier (KM) estimates and Cox Potential Hazard regression. KM plots showed the survival estimates as a function of each clinical feature and how each feature at various levels affect survival over the period of time. Cox regression modelled the hazard of death event around the clinical features used for the study. As a result of the analysis, ejection fraction, serum creatinine, time and age were identified as highly significant and major risk factors in the advanced stages of heart failure. Age and rise in level of serum creatinine have a deleterious effect on the survival chances. Ejection Fraction has a beneficial effect on survival and with a unit increase in the in the EF level the probability of death event decreases by ~5.2%. Higher rate of mortality is observed during the initial days post diagnosis and the hazard gradually decreases if patients have lived for a certain number of days. Hypertension and anemic condition also seem to be high risk factors. Machine learning classification models for survival prediction were built using the most significant variables found from survival analysis. SVM, decision tree, random forest, XGBoost, and LightGBM algorithm were implemented, and all the models seem to perform well enough. However, the availability of more data will make the models more stable and robust. Smart solutions, like this can reduce the risk of heart failure condition by providing accurate prognosis, survival projections, and risk predictions. Technology and data can combine together to address any disparities in treatment, design better care plan, and improve patient health outcomes. Smart health AI solutions would enhance healthcare policies, enable physicians to look beyond the conventional practices, and increase the patient satisfaction levels not only in case of heart failure conditions but healthcare in general.
M Roziq, Tri Bowo Indrato, M. Ridha Mak’Ruf
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4;

In the Suitability Test Method there is the Illumination and Collimation Test still using the manual method. This test aims to ensure that the light from the collimator lamp can be seen clearly so that the area of ​​the irradiation field can be identified when irradiating, as well as ensuring that the area of ​​the collimator lamp matches the X-ray beam so that it meets the needs and ensures that the patient does not get an excessive dose. The purpose of this research is to develop the simplest way by which the illumination measurement is carried out simultaneously at four points and the measurement data is directly stored. The contribution of this research is expected to be more testing tools and the data will be stored until the effective time of the next test. This module is designed using the HC-SR04 sensor as a distance meter and the TSL2561 sensor as a lux meter. The TSL2561 sensor allows for precise Lux calculations and can be configured for different gain/timing ranges to detect light ranging from 0.1-40,000+ Lux on the fly. This module is equipped with a display facility in the form of TFT Nextion to display measurement results. In addition, there is also data storage using an SD Card to store display measurement results. In this research, the module has been tested and compared with the suitability test value of the X-ray plane and got an error value of 2.0% with a module efficiency of 98.0% in the illumination test, and an error of 2.2% with a module efficiency of 97.8% in the collimator test. From this research, it can be concluded that the light sensor TSL2561 can be used to measure the illumination area of ​​the collimator lamp.
Sunil Sharma, Lokesh Tharani
Journal of Electronics, Electromedical Engineering, and Medical Informatics, Volume 4, pp 62-69;

Tumors can cause severe problem to human beings. Sometime it can be a cause of death. Earlier there were lack of treatment and technological deficiency, due to which it was unable to detect tumor cells and even unable to offer proper treatment for these diseases. This study aims to use Photonic crystal (PhC) due to their ample choice of structures and litheness to endure with every sphere of influence has been utilized them twenty decade back to now a day and have extremely huge prospects in imminent future also. They have revealed their incidence in the field of imaging, sensing, fabricating industries, automation, medical, mechatronics, computronics, mechanochromic, underwater acoustic detection, pharma industries and nanoimprinting etc. If we are discussing about current and impending applications of PhC then it comprises smart sensing and detection of disunite diseases, anonymous viruses and a range of tumors. Artificial intelligence (AI) is also playing incredibly essential role in analyzing and creating entities equivalent to the change in human behavior. AI tools and techniques are utilizing to create intelligent entities through which it is accomplishing countless feats. The PhC along with the artificial intelligence are utilizing as Optical Neural Network (ONN), Artificial Neural Network (ANN), Cellular Computing, Plasma Technology, Parallel Processing, Image Processing etc. Here in this study designated photonic crystal has been used for the detection of infected cell in human body. Sometimes these infected cells are unable to trace by normal pathological investigations and slowly they take a shape of Tumors. But thanks to Photonics crystal sensors that they have made it true not only for detection but we can say for early detection of such tumors in human body. These early detection and proper investigation is possible only because of AI impacts on photonics crystal. This study focuses on detection and observation of bio molecules for selectivity, sensitivity, reflectivity and concentration. By change in wavelength i.e. from 1.5 μm to 4 μm the refractive index (RI) of tumor cell can be measured which is observed by measuring sensitivity between 11258 nm/RIU to 32358 nm/RIU. Tumors have refractive indices varies between 1.3342 to 1.4251. It is observed that sarcoma level is directly proportional to the RI of tumor. Various AI algorithms like support vector machine (SVM) obtained accuracy as 96%, K- nearest neighbor (KNN) shows as 70%, logistic regression (LR) shows as 88%, random forest (RF) show it as 90%, fuzzy logic (FL) and artificial neural network (ANN) observed accuracy as 93% and 95% respectively.
Back to Top Top