Articles
<![CDATA[A Modified Electrosurgery Unit Based on High Frequency Design with Monopolar and Bipolar Method ]]>
<![CDATA[Edo Rafsanzani]]>;
<![CDATA[Tri Bowo Indrato]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Shengjie Yan]]>;
<![CDATA[Sergey A. Bogavev]]>
<![CDATA[ Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 4 (2021): November ]]>
Publisher : <![CDATA[Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia ]]>
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DOI: 10.35882/ijeeemi.v3i4.1
<![CDATA[Electrosurgery Unit is some machine to human body surgery. Electrosurgery Unit is uses a high frequency to human body tissue surgery, that causes blood who came out can be dicrease during surgery. When using a conventional scalpel is something that is highly avoided because it will cause contraindications to lack of blood which will be very dangerous for the patient. The purpose of this study is to design a tool that is used to replace a conventional scalpel with a tool that utilizes high frequency (400 KHz) generated by the oscillator circuit. In this study. The researches used Monopolar method and used two modes Cutting and Coagulation in order to eliminate faradic effects on body tissues causes high frequency, there is the high frequency will be adjusted to the duty cycle which aims to obtain various types of surgery required by doctor which is cutting 100% on and coagulation 6% on 94% off where is set it with arduino program. In this study, the researchers took advantage of the type of heat effect produced by high frequencies which were concentrated at one point so that it could be used to carry out the process of surgery on body tissues so as to minimize the occurrence of large blood loss. The result of this study is will be centered at one point on an object there is show up the depth difference of the cutting mode and the wide large difference of the coagulation mode. The module design resulted the power lowest at 300Ohm ESU Analyzer setting is 30Watt and the highest at 300Ohm setting too is 68Watt. The module design resulted the power lowest at 300Ohm ESU Analyzer setting is 30Watt and the highest at 300Ohm setting too is 68Watt at mode Cutting and the highest and lowest Coagulation mode using impedance setting the same there is 300 Ohm is constant 3Watt power result’s. The weaknesses at this research is the power still lower then the Electrosurgery Unit where is in the hospital. It can be fix for the next research using increase the final amplifier and maybe increase the frequency where is gonna make the voltage of the final amplifier be much better then this research]]>
<![CDATA[Analysis of Changes in Flow Setting Against Rise Time Using Gas Board 7500E Sensor on Bubble CPAP ]]>
<![CDATA[Andjar Pudji]]>;
<![CDATA[Farid Amrinsani]]>;
<![CDATA[Sari Luthfiyah]]>;
<![CDATA[Lusiana Lusiana]]>;
<![CDATA[Shubhrojit Misra]]>;
<![CDATA[Nur Hasanah Ahniar]]>;
<![CDATA[Yenda Mita Barus]]>;
<![CDATA[Lamidi Lamidi]]>
<![CDATA[ Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): May ]]>
Publisher : <![CDATA[Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia ]]>
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DOI: 10.35882/ijeeemi.v4i2.8
<![CDATA[Respiratory distress in neonates is one of the biggest problems encountered on a daily basis. Respiratory distress looks like rapid breathing in a newborn. CPAP Bubble is the right treatment in this case. Rise time is the time for airway pressure to reach the maximum standard value. A fast time value can make it possible to bring the breath pressure to a standard level. This study aims to analyze changes in setting flow to rise time using a gasboard sensor 7500E on a CPAP bubble device. The main advantage of this proposed method is that the results are displayed in the form of graphics, portable and there is data storage. This design uses a Gasboard 7500E sensor as a detector of oxygen concentration, a TFT LCD as a graphic display and an SD Card as data storage. The data collection is in the form of the average rise time of oxygen concentration followed by changes in its rate. Data were taken five times with three different CPAPs. The results showed that the increase in the rate affect the rise time of the CPAP oxygen concentration.]]>
<![CDATA[Analysis of Temperature Stability and Accuracy on the Design of Thermometer Calibrator Based on Fuzzy Logic And On/Off Control ]]>
<![CDATA[Yunik Pujiastuti]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Singgih Yudha Setiawan]]>;
<![CDATA[Farid Amrinsani]]>;
<![CDATA[Khongdet Phasinam]]>
<![CDATA[ Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 3 (2022): July ]]>
Publisher : <![CDATA[Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI ]]>
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DOI: 10.35882/jeeemi.v4i3.244
<![CDATA[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.]]>
<![CDATA[ECG Simulator Based on Microcontroller Equipped with Arrhythmia Signal ]]>
<![CDATA[M. Ridha Mak'ruf]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Bedjo Utomo]]>;
<![CDATA[I Dewa Gede Hari Wisana]]>;
<![CDATA[Torib Hamzah]]>;
<![CDATA[Lamidi Lamidi]]>;
<![CDATA[Denis Kurniar Wicaksono]]>;
<![CDATA[Sedigheh Ashgari Baighout]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 2 (2022): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
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DOI: 10.35882/jteknokes.v15i2.244
<![CDATA[Electrocardiograph (ECG) is one of the diagnostic sciences that is often studied in modern medicine, used to detect damage to the components of the heart or disorders of the heart rhythm called arrhythmias. The purpose of this research is to develop an Electrocardiograph simulator that is equipped with arrhythmia. The main design consists of an Arduino Mega 2560 microcontroller, MCP4921 DAC (Digital to Analog Converter) circuit, a network resistor, and a sensitivity selection circuit. The MCP4921 type DAC converts the digital signal data into analog data which will then be forwarded to the resistor network circuit as a signal formation for each lead. The basic signal image data used for the formation of normal Electrocardiograph and arrhythmias were taken from the Electrocardiograph recorder using Phantom Electrocardiograph. Based on the readings on the Beat Per Minute setting of the module to the Beat Per Minute printout on the Electrocardiograph recorder, the error rate value for the Normal Sine Rhythm parameter is 0.790% for Beat Per Minute 30, 0.383% for Beat Per Minute 60, 0.535% for Beat Per Minute 120, 0.515% for Beat Per Minute 180 and 0.593% for Beat Per Minute 240. The error rate for the Arrhythmia parameter is 2.076% for ventricular tachycardia Beat Per Minute 160 and 0.494% for Supraventricular Tachycardia Beat Per Minute 200. The design of the Electrocardiograph simulator can simulate the signals of the human body and it can be used as a medium in the learning process in the world of health]]>
<![CDATA[The Effect of Lost Data on the IoT Platform on the Formation of Fetal Heart Rate Graphs for Remote Diagnostic Purposes ]]>
<![CDATA[Boy Pribowo]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Muhammad Ridha Mak’ruf]]>;
<![CDATA[Vugar Abdullayev]]>
<![CDATA[ Jurnal Teknokes Vol 15 No 4 (2022): December ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
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DOI: 10.35882/teknokes.v15i4.489
<![CDATA[FHR is the fetal heart rate from bpm recording detected by doppler, FHR monitoring is very important to monitor fetal health to avoid fetal distress or fetal death, FHR provides more in-depth information about how the baby is doing compared to traditional monitoring of the baby. IoT media is a medium for monitoring remote sensor values using internet connections, but there are several obstacles, namely there are doubts about the data displayed by IoT media, namely the risk of missing or unsent data, this will be very dangerous if the data that is should be monitored by doctors as a reference for medical diagnosis and treatment is lost or not displayed on the IoT, because if there is missing data it will cause inaccurate diagnosis or health treatment decisions by doctors. The aim of this study to analyze the effect of lost data on the formation of the Fetal Heart Rate graph on the IoT platform as a medium for remote diagnosis. In addition, FHR data can be saved for further diagnosis by a doctor if needed. This study uses an ESP32 microcontroller which will also be used to send data to IoT (Thinger.io). The independent variable used in this study is FHR data before it is uploaded to the IoT, and the dependent variable is FHR data when it is uploaded to the IoT. The greatest data loss is at the farthest distance of 30 meters with a value of 62.47%. Based on the research that has been done, this study has the advantage that the results obtained from Doppler are close to the BPM value in humans. And also this research has developments that can be done in the future such as adding storage to the website that is used for monitoring, and placing the right position on Doppler so that the results are more stable.]]>
<![CDATA[QRS Complex Detection On Heart Rate Variability Reading Using Discrete Wavelet Transform ]]>
<![CDATA[Arga Wihantara]]>;
<![CDATA[I Dewa Gede Hariwisana]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Sari Luthfiyah]]>;
<![CDATA[Vijay Anant Athavale]]>
<![CDATA[ Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 4 (2022): November ]]>
Publisher : <![CDATA[Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia ]]>
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DOI: 10.35882/ijeeemi.v4i4.236
<![CDATA[Heart Rate Variability or heart rate in humans is used to monitor the heart rate in humans, the function of the heart rate monitor is to monitor the human heart rate. The purpose of making this tool is to compare the results of heart rate readings using the discrete wavelet transform method to facilitate the detection of R peak. This can be learned by evaluating and studying each decomposition result from level 1 to level 4 on Discrete Wavelet Transform processing using Haar mother wavelets. This study uses a raspberry pi 3B as a microcontroller as a data processor that is obtained from the ECG module. From this study, it can be concluded that in heart rate readings, level 2 decomposition details coefficient has the best value as data processing that helps for heart rate readings with an error value of 0.531%, HRV readings of 0.005 in comparison with phantom tools and a standard deviation of 0.039. The advantage of this tool is a good precision value in HRV and BPM readings. In reading the HRV of the respondent, it was found that each initial condition of the patient's HRV would be high due to the respondent's unstable condition. The disadvantage of this tool is that there is a delay in running the program, there is no display in the form of a signal in real time.]]>
<![CDATA[A Analysis of The Capture Result of Flat Panel Detector Design with Arduino-Based BPW34 Photodiode Sensor against mA and kV Settings ]]>
<![CDATA[Muhammad Rois Amin]]>;
<![CDATA[Muhammad Fajar Wahyudi]]>;
<![CDATA[Muhammad Ridha Makruf]]>;
<![CDATA[Tri Bowo Indrato]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Satheeshkumar Palanisamy]]>
<![CDATA[ Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 3 (2022): August ]]>
Publisher : <![CDATA[Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia ]]>
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DOI: 10.35882/ijeeemi.v4i3.242
<![CDATA[The exposure factor is the factor that determines the intensity and quality of X-rays received by the patient. Exposure factors that can be controlled are: tube voltage (kV), tube current (mA), irradiation time (second), and distance of the X-ray tube to the film (FFD). The purpose of this study was to capture X-rays at a relatively affordable manufacturing price and to obtain a difference in value from the detector's catch between dark and light by utilizing the response of the BPW34 photodiode sensor. The contribution of this study is that the system can display grayscale and numerical on an 8x8 pixel matrix using the Matrix Laboratory (MATLAB) Application. This study was able to convert images taken from analog data after taking measurements on X-rays. The measurements are carried out by 2 methods, there are range used was 32-63mA, with a tube voltage of 50 kV at an irradiation duration of 1 second and 50 - 70 kV, with a tube current of 40 mA and an irradiation duration of 1 second. From the measurement results, it shows that the Flat Panel Detector Design Tool after being compared with the Philips brand DR is able to respond to differences in dose and object thickness. The results of this study indicate that this tool can be used to capture X-rays so that the degree of blackness of the film can be known.]]>
<![CDATA[Analysis of Stability and Accuracy of Gas Flow in High Flow Nasal Canule for COVID-19 Patients ]]>
<![CDATA[Muhammad Ridha Mak'ruf]]>;
<![CDATA[Novella Lasdrei Anna Leediman]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Erwin L. Rimban]]>
<![CDATA[ Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 1 (2023): January ]]>
Publisher : <![CDATA[Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI ]]>
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DOI: 10.35882/jeeemi.v5i1.277
<![CDATA[In December 2019, the world was introduced to a new coronavirus, severe acute respiratory syndrome (COVID-19).The primary strategy for COVID-19 patients is supportive care, using high-flow nasal oxygen therapy (HFNC) reported to be effective in improving oxygenation. Stability is the ability of a medical device to maintain its performance [1]. Medical equipment must have the stability necessary to maintain critical performance conditions over a period of time. Accuracy is the closeness of agreement between the value of a measuring quantity, and the value of the actual quantity of the measuring quantity[2].The purpose of this study is to ensure that the readings of the HFNC device are accurate and stable so that it is safe and comfortable when used on patients. The development of the equipment that will be used by the author adds graphs to the TFT LCD to help monitor stable data in real time so that officers can monitor the flow and fraction of oxygen in the device to be stable. This study uses Arduino Nano while the sensor used is the GFS131 sensor, then the results are displayed on the Nextion TFT LCD. The test is carried out with comparing the setting value of the HFNC tool that appears on the TFT LCD with a gas flow analyzer with a measurement range of 20 LPM to 60 LPM 5 times at each point. Based on measurements on the gas flow analyzer, the HFNC module has an average error (error (%)) of6.40%. Average uncertainty (Ua) 0.05. Conclusion from these results that the calibrator module has a relative error (error value) that is still within the allowable tolerance limit, which is ±10%, the tool is precise because of the small uncertainty and good stability of the stability test carried out within a certain time.]]>
<![CDATA[Monitoring the Occurrence of Alarms in High Flow Nasal Cannula (HNFC) Using IoT-Based Thinger.io Platform for COVID-19 Isolation Room ]]>
<![CDATA[Sapty Taurisita Fauziah]]>;
<![CDATA[Muhammad Ridha Mak'ruf]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Levana Forra Wakidi]]>;
<![CDATA[Faraz Masood]]>
<![CDATA[ Jurnal Teknokes Vol 16 No 1 (2023): March ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
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DOI: 10.35882/teknokes.v15i4.496
<![CDATA[Covid-19 has become a virus that has become a world pandemic and this virus has caused mass deaths because medical personnel have difficulty treating patients when oxygen levels in the blood have fallen to critical levels. HFNC (High Flow Nasal Cannula) is a method of administering additional oxygen to patients with acute respiratory failure. The use of HFNC in recent years has been highly recommended as a solution to provide supplemental oxygen to patients. Administration of HFNC to COVID-19 patients begins at a flow range of 30-60 LPM.Unfortunately, HFNC, which used to exist, can only be monitored manually, resulting in the transmission of HFNC-produced aerosols between patients and staff. So this study aims to analyze errors in HFNC that cause a decrease in flow to HFNC using a flow sensor as a sensor to detect leaks or other flow errors from the HFNC output hose and monitor if there is a blockage through IoT in the form of notifications.This research method uses the Pre-experimental with the After Only Design type. In this design, the researcher only used one group of subjects and only looked at the results without measuring and knowing the initial conditions, but there was already a comparison group. The independent variable in this study was the HFNC error condition. While the dependent variable in this study is the data flow read by the sensor, where IoT notifications and device status show error leaks. The sensors used in this research are MPX5700GP pressure sensors and SEN0343 Differential Pressure sensors as flow sensors. The benefit of this research is that in addition to reducing the burden on medical staff in handling Covid-19 patients, it can also minimize transmission between staff and patients caused by high aerosol production by this HFNC device, this is because HFNC device alarm monitoring can be monitored in the nurse's room via internet technology. In conclusion, to obtain maximum benefits from this research, it is necessary to select a sensor that truly has a high enough resistance to humidity produced by this HFNC humidifier's water vapor.]]>
<![CDATA[Monitoring the Occurrence of Alarms in IoT-Based HFNC With Analysis of Signal Increase Before Blockages Error Occurs (Pressure Parameters) ]]>
<![CDATA[Dwi Widyaningtyas]]>;
<![CDATA[Andjar Pudji]]>;
<![CDATA[Muhammad Ridha Mak'ruf]]>
<![CDATA[ Jurnal Teknokes Vol 16 No 2 (2023): June ]]>
Publisher : <![CDATA[Jurusan Teknik Elektromedik, POLTEKKES KEMENKES Surabaya, Indonesia ]]>
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DOI: 10.35882/teknokes.v16i2.456
<![CDATA[The workload of medical personnel in handling COVID-19 is quite high due to limited personnel so that medical personnel who are resting are assigned the task of always being ready to carry out clinical monitoring of the use of HFNC. HFNC (High flow Nasal Cannula) is a method of giving supplemental oxygen to patients experiencing acute respiratory failure. The use of HFNC in recent years is highly recommended as a solution to provide additional oxygen to patients. The administration of HFNC to COVID-19 patients begins in the flow range of 30-50 LPM with an oxygen concentration of 92%. This study aims to analyze the error in HFNC which causes a decrease in the flow of HFNC. This study used data collection 10 times by modifying the HFNC output interval. The independent variable in this study is the HFNC error condition. While the dependent variable in this study is the pressure data read by the pressure sensor. In this study using a temperature setting of 34oC with a flow setting of 30-60 LPM. At the flow setting of 30 LPM, the average pressure value before error is 0, in process 2 and after error 0, where the IoT notification and the condition of the tool show a Blockage error. At the flow setting of 30 LPM, the average pressure value before error is 0, in process 1 and after error 0, where the IoT notification and the condition of the tool show a leaking error. In this study, the average error in the conditions of Blokage 3.8 and Leaking 1.5 The shortcomings in this study are can be a pressure sensor which has more sensitive results and also a pressure sensor that has a medical grade standard.]]>
