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INDONESIA
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Published by Polilteknik Kesehatan Kemenkes Surabaya
ISSN : -     EISSN : 26568624     DOI : https://doi.org/10.35882/ijeeemi
Core Subject : Health, Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Health Professions Materials Science & Nanotechnology
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics (IJEEEMI) publishes peer-reviewed, original research and review articles in an open-access format. Accepted articles span the full extent of the Electronics, Biomedical, and Medical Informatics. IJEEEMI seeks to be the world’s premier open-access outlet for academic research. As such, unlike traditional journals, IJEEEMI does not limit content due to page budgets or thematic significance. Rather, IJEEEMI evaluates the scientific and research methods of each article for validity and accepts articles solely on the basis of the research. Likewise, by not restricting papers to a narrow discipline, IJEEEMI facilitates the discovery of the connections between papers, whether within or between disciplines. The scope of the IJEEEMI, covers: Electronics: Intelligent Systems, Neural Networks, Machine Learning, Fuzzy Systems, Digital Signal Processing, Image Processing, Electromedical: Biomedical Signal Processing and Control, Artificial intelligence in biomedical imaging, Machine learning and Pattern Recognition in a biomedical signal, Medical Diagnostic Instrumentation, Laboratorium Instrumentation, Medical Calibrator Design. Medical Informatics: Intelligent Biomedical Informatics, Computer-aided medical decision support systems using heuristic, Educational computer-based programs pertaining to medical informatics
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 199 Documents
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The Impact of Using Digital Filter and Analog Filter on EMG Signal Setioningsih, Endang Dian
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 1 No. 2 (2019): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v1i2.254

Abstract

Many cases of accidents which resulted in humans having to surgery to save them, then performend muscle therapy to help the patient’s recovery after going through the post-surgery. This therapy has a purpose, so that the patient’s body is expected to return to normal. An exoskeleton is a tool like an additional clothing that aims not only to protect, but also to increase the wearer's abilities. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles. The purpose of this study was to analyze the differences in the use of analog and digital filters on EMG, as well as the effect on the exoskeleton simulation. The method used in the main design consists of the myoware module, notch circuit, low pass filter, arduino uno, DAC module, teraterm software, and matlab. The intercepted signal is taken from the biceps using a disposable electrode (AG/AGCL.). The EMG signal tapped by the myoware module will continue to another circuit, then recorded on the Teraterm software, and analyzed in MATLAB. The voltage value on the analog filter is 1.541 Volt during relaxation and 2.086 Volt during contraction, while the digital filter that has passed through the DAC has a value of 41.8 mVolt during relaxation and 269.1 mVolt during contraction. The results of this study obtained that digital and analog filter values ​​have an average difference of 5 to 30. The conclusion of this research tool can detect changes in the use of analog and digital filters, in the future research can be developed by comparing other types of digital filters along with replacement to wireless systems. The benefit or purpose of this research is as a simulation of exoskeleton skeletal motion and can see the difference between the use of digital and analog filters
Use Chest Vibrator to Prevent Pulmonary Infection in Patients with COPD Luthfiyah, Sari; Utomo, Bedjo; Ariswati, Her Gumiwang
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 1 No. 2 (2019): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v1i2.255

Abstract

Chest infection is an infection that affects your lungs, either in the major respiratory tract (bronchitis) or in small air sacs (pneumonia). There is an accumulation of pus and liquid (mucus), and the respiratory tract becomes swollen, making breathing difficult. Chronic obstructive pulmonary disease (COPD) is a serious cause of death globally. This disease is characterized by episodes of acute exacerbations or aggravation that are superimposed upon a gradual decrease in pulmonary function. The study developed a device for vibratory techniques in chest physiotherapy. Vibration is a pressure applied to the chest during exhalation to move the secret into the large respiratory tract. Measurements of the mechanical impedance of the respiratory system in frequencies from about 5 Hz to about 70 Hz in the higher frequency range should be evaluated on the basis of the lung model. In this device, using frequencies that are often used in the field: 30, 40, 50 Hz and a timer of 3 to 5 minutes. This device uses a 12V DC motor as a vibration medium that will be connected to the engine inside the paddle. It uses IC NE 555 as an important component of the conductor circuit. This module uses an LCD screen of 16x2 characters as screen. The result was found that by using IC NE 555 as an important driver in showing acceptable system accuracy, only a minimum error value of ± 0.008% and a maximum error value of ± 0.02%. The advantage of this module is that it is equipped with a 3-5 minutes timer so that it can provide efficient therapy according to the time needed and is equipped with an LCD display to make it easier to observe the time
Development of Wireless Central Monitor Using X-bee Pro S2C (Electrocardiogram and Heart Rate) Ulumiddiniyah, Bariroh Izzatul; Irianto, Bambang Guruh; Hamzah, Thorib
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 2 No. 1 (2020): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.256

Abstract

Centralized monitoring of the condition of patients with serious conditions that are carried out continuously and in real-time is very important. in the development of previous researchers have some shortcomings, namely sending data still using cable, completeness of parameters that are still small, close delivery distance, not real-time, and continue. The purpose of this study is that the thick system is done wirelessly, more parameters, longer delivery distance, and can monitor electrocardiogram and heart rate in real-time and continue. the contribution of this research is that the wireless system can send ECG and bpm in real-time, long-distance, and continuously. To make deliveries in real-time, this study uses 2 transmitters and 2 receivers. Electrocardiogram signal obtained from tapping Lead II, then processed using a microcontroller circuit and the results in the form of a heart signal will be. Data is sent using X-Bee Pro. Data is displayed in the form of a patient's heart and BPM signals. In measuring BPM values ​​obtained error values ​​in module 1 0.1388% for BPM 240 and 0.093% for BPM 180, in module 2 0.1388% for BPM 240 and 0.185% for BPM 180, data transmission can be done well at a distance of 8 meters, 10 meters, and 25 meters with a barrier. The results of this study indicate that sending wirelessly can be done at a certain distance and in real-time. This research can be implemented in a central monitor in a hospital with more patients
Design of Vital Sign Monitor with ECG, BPM, and Respiration Rate Parameters Oka, Gede Aditya Mahendra; Pudji, Andjar; Mak’ruf, Muhammad Ridha
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 2 No. 1 (2020): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.257

Abstract

Vital sign monitor is a device used to monitor a patient's vital sign, in the form of a heartbeat, pulse, blood pressure, temperature of the heart's pulse form continuously. Condition monitoring in patients is needed so that paramedics know the development of the condition of inpatients who are experiencing a critical period. Electrocardiogram (ECG) is a physiological signal produced by the electrical activity of the heart. Recording heart activity can be used to analyze how the characteristics of the heart. By obtaining respiration from outpatient electrocardiography, which is increasingly being used clinically to practice to detect and characterize the abnormal occurrence of heart electrical behavior during normal daily activities. The purpose of this study is to determine that the value of the Repiration Rate is taken from ECG signals because of its solidity. At the peak of the R ECG it has several respiratory signals such as signals in fluctuations. An ECG can be used to determine breathing numbers. This module utilizes leads ECG signals to 1 lead, namely lead 2, respiration rate taken from the ECG, BPM in humans displayed on a TFT LCD. This research module utilizes the use of filters to obtain ECG signals, and respiration rates to display the results on a TFT LCD. This module has the highest error value of 0.01% compared to the Phantom EKG tool. So this module can be used for the diagnosis process.
Central Monitor Based Personal Computer with SpO2 and Body Temperature Parameters Via Wireless Xbee Pro Oka, I Komang Yogi Mahardika; Pudji, Andjar; Mak’ruf, Muhammad Ridha
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 2 No. 1 (2020): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.258

Abstract

Central patient monitor that is not real-time and continues will cause inaccuracies monitoring results and also sending data that is still using cable will cause limited distance. The purpose of this research is to design a central monitoring based personal computer via Xbee Pro. The contribution of this research is, the system works in real-time and continues, more parameters, using wireless, longer transmission distances. So that monitoring can be done in real-time and continue via wireless with more distance, then the wireless system uses the Xbee Pro module which has larger output power and uses the same number of wireless modules between transmitter and receiver. Body temperature was measured using the LM35 sensor and oxygen saturation in the blood was measured using the MAX30100 sensor. Data is sent using Xbee Pro and displayed on a personal computer. At the distance of receiving data approximately 25 meters with a wall divider, obtained results of smooth monitoring without any loss of data. The results showed that the average SpO2 error value was 0.34% in module 1 and 0.68% in module 2. The average value of body temperature error was 0.46% in module 1 and 0.72% in module 2. The results of this research can be implemented in a centralized patient monitoring system at the hospital, making it easier for health workers to monitor multiple patients, with the results of monitoring in real-time and continue, more parameters, via wireless with greater distance.
Modification of Infant Warmer with PID Temperature Controlled with Apgar Monitoring and Respiration Rate Mahendra, Reynaldi Krisna; Lamidi, Lamidi; Kholiq, Abd.
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 2 No. 1 (2020): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.259

Abstract

Newborns, both healthy and premature babies, have a difficult problem, newborns withstood the environment with new ones that previously depended on the mother's uterus and also as a place for initial examination in nayi after just being discussed. The purpose of this study was to add a baby warmer with PID temperature control and add respiration parameters and APGAR. The contribution in this study is the PID control system which is used to control temperature and is also a sensor of respiration rates to determine respiration in infants. So that the values ​​of the temperature sensor and Respiration Rate sensor can be stable it is necessary to adjust the sensor's reading time. The LM35 sensor can activate temperature in the body, the Flex Sensor is used to read respiration values ​​in infants. Based on data collection of respiration rates taken from adults, an average value of 18.5 times per minute was obtained in the first attempt, and 21 times per minute in the second trial. Respiratory rate values ​​that have not been stable take data because there are still external factors, such as changes from respondents and others. The results of this research can be implemented on baby warmers to improve the application of updates to the baby.
Design of Instrument Measurement for X-Ray Radiation with Geiger Muller Barends, Georgia Kusmiran; Utomo, Bedjo; Indrato, Tri Bowo
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 2 No. 1 (2020): February
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v2i1.260

Abstract

Radiation monitoring aims to know firsthand the rate of radiation exposure in a work area to ensure the safety and health of workers who will work in the radiation emitting area in accordance with the principle of ALARA (As Low As Reasonably Achievable). This study developed a nature X-ray radiation measuring device using a Geiger Muller tube detector and can display the results of the measurement of numbers in microSievert units and Counter Per Minute to the LCD Character display and Android which have function to reduce the radiation exposure received by the radiation workers. The output of the detector is processed using Arduino Uno. Comparison of the results of the module with a calibrated standard survey meter measures the reference that the module can be used. The radiation detection system testing of this module is carried out to adjust the current condition of the Covid-19 pandemic, so that the module tests the background radiation (natural radiation). Based on module testing and experiments, it was obtained that data from 10 times data collection showed the accuracy value of the radiation measuring device using a Geiger Muller detector was 90.71% for the measurement of background radiation in a closed room. The Geiger Muller detector is not accurate for measuring small radiation exposures, the module can be used to measure background radiation and fluoroscopy X-ray radiation
Classification Of Cyber Attack And Anomaly In Web Server Using Transformer and Transfer Learning Prasetyo, Edi Dwi; Rahmat, Basuki; Sari, Anggraini Puspita
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 4 (2025): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i4.119

Abstract

Cybersecurity is a crucial aspect in maintaining the integrity and availability of information systems, especially on web servers which are vulnerable to various types of attacks and anomalies. This research aims to investigate the application of transfer learning in the classification of cyber attacks and anomalies on web servers. Transfer learning, a powerful deep learning approach, enables pre-trained models to adapt to new tasks with limited data, offering an efficient solution for detecting malicious activities and unusual patterns in web server logs. The goal is to improve detection accuracy while reducing the time and resources required to train models from scratch. This study uses a bi-layer classification approach with pre-trained Transformer models, RoBERTa and BERT, through transfer learning to detect cyber attacks and anomalies in web server log data. The process includes preprocessing the log data, extracting relevant features, and fine-tuning BERT to classify known attacks in the first layer, followed by RoBERTa in the second layer to detect unusual or unknown behaviors. Model performance is evaluated using accuracy, precision, recall, and F1-score, and results are compared with traditional deep learning methods like RoBERTa and BERT to highlight the advantages of this bi-layer transfer learning approach. The result of this proposed bi-layer classification method is improved performance in detecting cyber attacks and anomalies compared to using RoBERTa and BERT individually. By combining both models, the system is anticipated to achieve higher accuracy, better precision in identifying true threats, improved recall for detecting a wider range of attacks, and a more balanced F1-score. This layered approach leverages the strengths of both RoBERTa and BERT, enabling more robust and reliable threat detection, with reduced false positives and false negatives compared to single-model implementations. 
Gait Variability and Phase Segmentation in Obese and Normal Individuals Using Multi-Location IMUs and Hidden Markov Models Supervised Marginal Setiyadi, Suto; Muktar, Husneni; Cahyadi, Willy Anugrah; Widiyasari, Diyah; Ramadhani, Mohamad; Tang, Nigel Bryan
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 7 No. 4 (2025): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v7i4.269

Abstract

Obesity is known to disrupt motor control and biomechanics; however, detailed gait alterations in individuals with obesity remain underexplored, particularly in dynamic and real-world walking conditions. This study aims to quantitatively characterize gait differences between individuals with obesity and those of normal weight by analyzing postural and temporal gait parameters. The investigation focuses on pitch, roll, and cadence dynamics using body-worn inertial sensors, with phase transition modeling via Hidden Markov Models. This work proposes a novel framework that integrates multi-location Inertial Measurement Unit (IMU) sensors and a Hidden Markov Model–Supervised Marginal (HMM-SM) approach to detect and classify gait phases with high accuracy, offering practical value for clinical gait assessment and personalized rehabilitation. IMU sensors were placed on the waist, thigh, calf, and heel to record gait data from participants in both obese and normal-weight groups. Gait segmentation and phase modeling were conducted using 4-, 5-, and 8-state HMMs. Quantitative analysis revealed significantly greater postural variability in the obese group during slow walking, with standard deviations in roll and pitch reaching 20.68° and 9.23°, respectively—much higher than the normal-weight group (0.60° and 0.26°). Hidden state transitions from 5-state pitch HMMs showed a very strong effect size for the obese group (Cramér’s V = 0.72) compared to a moderate effect for the normal-weight group (V = 0.33). Similar patterns were observed for roll and cadence. In terms of segmentation accuracy, the 4- and 5-state HMMs outperformed the 8-state model, achieving accuracy levels above 99%, while the 8-state model reached only ~93%. The findings demonstrate that obesity significantly alters gait dynamics, particularly in postural stability and gait phase transitions. The proposed IMU-based HMM-SM framework effectively captures these changes, offering a reliable tool for gait analysis in clinical and biomechanical applications.

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