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Journal of Electronics, Electromedical Engineering, and Medical Informatics
Published by Polilteknik Kesehatan Kemenkes Surabaya
ISSN : -     EISSN : 26568632     DOI : https://doi.org/10.35882/jeeemi
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering
The Journal of Electronics, Electromedical Engineering, and Medical Informatics (JEEEMI) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics which covers three (3) majors areas of research that includes 1) Electronics, 2) Biomedical Engineering, and 3)Medical Informatics (emphasize on hardware and software design). Submitted papers must be written in English for an initial review stage by editors and further review process by a minimum of two reviewers.
Arjuna Subject : Teknik (semua kategori) - Teknik Biomedis
Articles 270 Documents
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Artificial Intelligence: A Review of Progress and Prospects in Medicine and Healthcare Saurav Mishra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 1 (2022): January
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i1.1

Abstract

Andrew NG, a leading philosopher in the field of Artificial Intelligence (AI) once quoted “AI is the new electricity” which has the potential to transform and drive every industry. The most important driving factor for the AI transformation will be data. Clive Humby, a data science entrepreneur was once quoted saying “data is the new oil” and data analytics being the “combustion engine” will drive the AI led innovations. The rapid rise of Artificial Intelligence technologies in the past decade, has inspired industries to invest in every opportunity for integrating AI solutions to their products. Research, development, and innovation in the field of AI are shaping various industries like automobile, manufacturing, finance, retail, supply chain management, and education among others. The healthcare industry has also been adopting the ways of AI into various workflows within the domain. With the evolution in computing and processing powers coupled with hardware modernizations, the adoption of AI looks more feasible than ever. Research and Innovations are happening in almost every field of healthcare and hospital workflows with the target of making healthcare processes more efficient & accessible, increase the overall state of healthcare, reduce physician stress levels, and increase the patient satisfaction levels. The conventional ways in which healthcare and clinical workflows have been operating are now starting to see the change with the integration of many data driven AI solutions. The digital innovations are making life easy for healthcare professionals allowing them to spend more time listening to the problems of patients and consequently increasing the patient satisfaction levels. However, there are limitations and concerns on security of Protected Health Information which have to be addressed for a seamless amalgamation of AI systems into the healthcare domain. Many papers have been published which mostly talk about one particular field/problem in the healthcare domain. No publications have covered the opportunities provided by AI technologies to the entire healthcare domain. This review paper discusses in detail about the progress AI has been able to make in the healthcare domain holistically and what the future of AI looks like. The paper also discusses about the implementation opportunities various AI technologies like Machine Learning, Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision provide in different fields of healthcare and clinical workflows and how Artificial Intelligence systems will boost the capabilities of healthcare professionals in restoring the human touch in patient-physician encounters. A physician’s intuition and judgement will always remain better suited since each case, each health condition, and each person is unique in its own way, but AI methods can help enhance the accuracy of diagnosis, assist physicians in making improved and precise clinical decisions.
Analysis of X-Ray Beams Irradiation Accuracy Using Collimation Test Tools as Well as Illumination Measurement on the Collimator to the Radiographic X-Ray Machine Conformity Test Results M Roziq; Tri Bowo Indrato; M. Ridha Mak’ruf
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.8

Abstract

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.
Effect of Irradiation Distance on Tube Voltage Measurement and X-Ray Device Time Using Scintillator All Adin Nurhuda; M. Ridha Mak'ruf; Tri Bowo Indrato; Sari Luthfiyah
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.7

Abstract

The results of the output of the X-ray device are very important to know how much the correct value, whether it is in accordance with the arrangements made by radiology personnel or there is a difference even deviation of the value out of the arrangement. This conformity test activity needs a testing tool that is often used by BAPETEN personnel to find out how much the output value of KV, Time, Dose, Room leak, mA and mAs from an X-ray device unit. The purpose of this study was to analyze the effect of irradiation distance on tube voltage measurements and X-ray device time using Scintillators. The study used scintillator sensors to detect radiation, arduino as a programming source, bluetooth HC-05 as digital communication between hardware and PC, PC / Delphi as display. This research design is Pre-Experimental with After Only Design research type. Where the author takes data compared to standard tools then analyzes the data. The results showed the largest error at a distance of 120cm with a 90 KV setting of 43.52%. And the smallest error is at a distance of 120cm with a 50 KV setting of 0.07%.
Comparison of Air Pressure Control Between Discrete and PID Control Applied in the Calibration Process in Blood Pressure Meter Harisha Avin Nurcahyana; Tri Bowo Indrato; Triana Rahmawati; Wahyu Caesarendra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.6

Abstract

In performing the calibration of the sphygmomanometer, the officer needs to first reset the installation and pump the bulb slowly until it reaches the set point in accordance with the calibration settings where this does not provide convenience to the calibration officer. So the author wants to do research on making additional devices to support DPM calibration instruments that have been commercialized to speed up the pump process in Sphygmomanometer calibration. The purpose of this research is to make an Automatic Pump module with PID control to analyze the stability of the pressure achievement in accordance with the set point when using the smoothing program or not. This study used set points of 50, 100, 150, 200, and 250 mmHg. Data retrieval was carried out within 260 seconds at each set point at the Campus of the Department of Electrical Engineering Poltekkes Kemenkes Surabaya. The results of this study indicate that the tool testing using the smoothing program experienced small oscillations compared to the program without smoothing. The data obtained are at setting 50 the average overshoot is 54 and the average undershoot is 49; at setting 100 the average overshoot is 109 and the average undershoot is 99; at setting 150 the average overshoot is 156 and the average undershoot is 149; at setting 200 the average overshoot is 206 and the average undershoot is 196; at setting 250 the average overshoot is 253 and the average undershoot is 247. The importance of this device was made in order to make it easier and faster for the calibration officer to calibrate the Sphygmomanometer.
Mechanical Fetal Simulator for Fetal Doppler Testing Arum Triwerdani; Syaifudin Syaifudin; Bedjo Utomo; Abdul Basit
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.5

Abstract

The continuous use of fetal Doppler allows for discrepancies in values ​​that lead to misdiagnoses in patients. This study aims to determine the effect of sound source distance on the fetal simulator with the measurement point. The contribution of this research is that the mechanical fetal heart system has 4 distances so that later it can be analyzed whether there is an influence of the location of the sound source on the accuracy of measurements using a fetal simulator. To get the desired distance, a solenoid is used which ends with a pipe of 2 cm, 5 cm, 10 cm, and 50 cm respectively. The solenoid used in the fetal simulator functions as a producer of the fetal heart. There is a rotary switch that functions for solenoid selection, namely 2 cm, 5 cm, 10 cm and 50 cm solenoids. Data collection was carried out on each solenoid and by placing the Doppler probe perpendicular and tilted. On the solenoid with a distance of 50 cm all measurement results exceed the allowable tolerance limit. The results showed that the BPM value of the two Doppler brands did not have a significant difference in value. When measuring fetal Doppler, the largest error value was 2.67%. The results of this study can be used as a reference when conducting an examination
Use of a Portable Particle Counter to Analyze Particle Stability Time in a Biological Safety Cabinet (BSC) Herlina Candra Putri; Priyambada Cahya Nugraha; Endro Yulianto; Ashish Bhatt
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.4

Abstract

Biological Safety Cabinet (BSC) is a laboratory work area with air ventilation that has been engineered to protect workers working with material samples, the environment and material samples from the possible danger of contamination or causing the spread of pathogenic bacteria or viruses. The purpose of this study is to analyze the stability of the time required for the BSC to reach the condition of no particles in the BSC space. This is done by making a module using the PMS7003 sensor to detect the number of particles. This study uses the Arduino Mega system for data processing and then displays it in the form of graphs and numbers. In the condition of the number of particles of 162,965, the time required for the BSC is 29 seconds, while in the condition of the number of particles of 186,408, the time required is 38 seconds. So it is known that if the number of particles in the BSC space is more and more particles in the BSC space, the longer it takes for the BSC to reach the no-particle condition. BSC that uses a single fan blower cannot achieve a stable number of particles simultaneously.
Measurement of Vital Signs Respiratory Rate Based on Non Contact Techniques Using Thermal Camera & Web Camera with Facial Recognition Raden Duta Ikrar Abadi; Endro Yulianto; Triwiyanto Triwiyanto; Sandeep Kumar Gupta; Vugar Abdullayev
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.3

Abstract

Examination of the respiratory rate is included in the calculation of vital sign parameters used by the medical team to determine whether a person's condition is good or not. Researchers want to develop a method of checking the respiratory rate that is easy to use by the general public and can display fast and precise results. During this pandemic, we are forced to reduce direct human-to-human contact with the aim of suppressing the exchange of viruses. From this condition, the researcher wants to develop a measuring instrument to measure the respiratory frequency with the non-contact method. This method is expected to reduce direct contact between humans and still get the results of the respiratory rate value which can be used as a parameter to determine a person's condition. To get the value of the respiratory rate, researchers have an idea by monitoring changes in temperature using a thermal camera. For the respiratory rate parameter, the researcher observed the nose area by detecting changes in expiratory and inspiration temperatures and then calculating the respiratory rate. To get these results, the researcher uses a method of detecting the face area or called face recognition and then detecting the ROI point in the area of interest in the nose area. In observing the respiratory rate, the temperature value during expiration is 31.05 °C while at the time of inspiration is 30.01 °C. This temperature difference will be carried out in the process of calculating the respiration rate value by the system made by the researcher. In the results of this study, it was found that the respiration rate module can be used as a reference with a normal use range of 60-120 cm with an error value of 1% if the distance is above 100 cm, then the results of this study are that this research can be implemented on a breathing frequency measuring instrument with a non-standard method. - contact
Heating and Cooling Rate Study on Water Cooling Thermal Cycler using Aluminium Block Sample Nugroho Budi Wicaksono; Sukma Meganova Effendi
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.1

Abstract

Temperature measurement has many applications in medical devices. In recent days, body temperature become the main screening procedure to justify people infected by SARS-CoV-2. Related to pandemic situation due to SARS-Cov-2, Polymerase Chain Reaction (PCR) method become the most accurate and reliable detection method. This method employs a device named PCR machine or Thermal Cycler. In this research, we focus to build a Thermal Cycler using a low-cost material such as aluminium and using a liquid coolant as the cooling system. We use 2 types of coolant solution: mineral water and generic liquid coolant. Peltier device in thermal cycler serves as heating and cooling element. In heating rate experiments, generic liquid coolant shows a better result than using mineral water due to specific heat capacity and thermal conductivity of water. In the cooling rate experiments, the water pump is activated to stream the liquid solution, the flow rate of liquid solution is influenced by viscosity of the liquid. Generic liquid coolant has approx. 4,5 times greater viscosity than water. The higher flow rate means better performance for cooling rate. Using 2 pieces of 60-Watt heaters and a 60-Watt chiller and aluminium material as block sample, our research shows a heating and cooling rate up to approx. 0,1°C/s. Compared to commercially thermal cycler, our thermal cycler has a lower wattage; this lower wattage performance has been tradeoff with lower ramping rate. Some factors are suspected become the source of contributors of lower ramping rate.
Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor Sunil Sharma; Lokesh Tharani
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i2.2

Abstract

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.
A Comparative Study for Time-to-Event Analysis and Survival Prediction for Heart Failure Condition using Machine Learning Techniques Saurav Mishra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 3 (2022): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v4i3.225

Abstract

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.

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