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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Journal of Electronics, Electromedical Engineering, and Medical Informatics Indonesian Journal of electronics, electromedical engineering, and medical informatics
Wahyu Caesarendra
Faculty of Integrated Technologies, Universiti Brunei Darussalam, Brunei Darussalam
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Long Distance Dual SpO2 Monitoring System for Premature Babies Using Bluetooth Communication Priyambada Cahya Nugraha; Muhammad Ridha Mak'ruf; Lusiana; Sari Luthfiyah; Wahyu Caesarendra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 2 (2021): 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.v3i2.7

Abstract

Monitoring the baby's health status is very important, especially for babies born prematurely. Oxygen saturation levels in newborns are very important to know because when the oxygen saturation levels in newborns are low, it is necessary to watch out for hemodynamic abnormalities in the baby. Measurement of oxygen saturation levels in newborns can help detect congenital abnormalities in infants early. This study aims to design an equipment system to continuously monitor the condition of oxygen saturation in newborns. Where in this discussion a monitoring tool is used to monitor 2 premature babies in a baby incubator simultaneously using a Neonatal Fingertip sensor. The system will display the oxygen saturation (SpO2) value and signal. Monitoring on this tool is done wirelessly using the HC-05. Based on the results of tests and measurements in 5 different patients with a pulse oximeter comparison, the difference value of 1% in each patient's results was obtained. The results of this study will greatly help facilitate the work of paramedics in monitoring the vital conditions of newborn babies.
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.
Analysis of the Effect of Red LED and Infrared Flip Flop Frequency on SpO2 Measurement Accuracy Moch Prastawa Assalim T P; Dyah Titisari; Wahyu Caesarendra; Bagas Angger Prakoso
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 4 No 2 (2022): May
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

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

Abstract

Oxygen saturation is a vital parameter for the early detection of advanced oxygen deficiency. Spo2 is a tool that measures the amount of oxygen in the blood non-invasively. This equipment consists of ophotodiodeiode as a sensor as well as red and infrared LEDs with a flip flop driver circuit that has a certain frequency. In this case, several research projects and equipment on the market have various flip flop frequencies. This research aims to find the best frequency setting value for red and infrared led drivers on SpO2 devices. In this research, a SpO2 that can be adjusted with a flip flop frequency of 400 Hz to 1400 Hz was designed. The SPO2 reading from the sensor is presented on the OLED LCD panel using Arduino Mega as a data processor from the driver frequency output controller. Frequency adjustment for sensor drivers is also at 400 Hz to 1400 Hz. This tool was further used to measure the frequency variation of the flip flop. The measurement results on the subject's finger were then compared with the results of the standard SpO2 tool to see the effect of the frequency value on the level of accuracy of the tool. The results of the comparison data processing showed that the largest error of 0.35% occurred in the SPO2 measurement using the 600 Hz sensor frequency driver, and the smallest error value of 0.07%, occurred in the use of the driver frequency at 1400Hz. These results can be used in the initial design of the production of SpO2 equipment, the higher the frequency, the more accurate it will be. This study only discusses the frequency, whereas the intensity parameters of the red and infrared LEDs also vary. In future research, it would be better to involve the LED light intensity parameter to determine its effect on the accuracy of the tool.
Analyzing the Relationship between Dialysate Flow Rate Stability and Hemodialysis Machine Efficiency Baharudin Adi Baharsyah; Endang Dian Setioningsih; Sari Luthfiyah; Wahyu Caesarendra
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 2 (2023): May
Publisher : Department of electromedical engineering, Health Polytechnic of Surabaya, Ministry of Health Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v5i2.276

Abstract

Chronic kidney disease (CKD) is a condition characterized by impaired kidney function, leading to disruptions in metabolism, fluid balance, and electrolyte regulation. Hemodialysis serves as a supportive therapy for individuals with CKD, prolonging life but unable to fully restore kidney function. Factors influencing urea and creatinine levels in hemodialysis patients include blood flow velocity, dialysis duration, and dialyzer selection. This research aims to establish a standard for calculating the dialysate flow rate, thereby enhancing dialysis efficiency. The study employs a pre-experimental "one group post-test" design, lacking baseline measurements and randomization, although a control group was utilized. The design's weakness lies in the absence of an initial condition assessment, making conclusive results challenging. Measurement comparisons between the module and the instrument yielded a 5.30% difference, while the difference between the hemodialysis machine and standard equipment was 4.02%. Furthermore, six module measurements against three comparison tools showed a 0.17% difference for the hemodialysis machine with standard equipment, and a 0.18% difference for the module with standard equipment, with a 0.23% discrepancy between the two. Further analysis is necessary to understand the clinical significance and implications of these measurement variations on overall dialysis efficacy
Implementation of Supervised Machine Learning on Embedded Raspberry Pi System to Recognize Hand Motion as Preliminary Study for Smart Prosthetic Hand Triwiyanto Triwiyanto; Sari Luthfiyah; Wahyu Caesarendra; Abdussalam Ali Ahmed
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4397

Abstract

EMG signals have random, non-linear, and non-stationary characteristics that require the selection of the suitable feature extraction and classifier for application to prosthetic hands based on EMG pattern recognition. This research aims to implement EMG pattern recognition on an embedded Raspberry Pi system to recognize hand motion as a preliminary study for a smart prosthetic hand. The contribution of this research is that the time domain feature extraction model and classifier machine can be implemented into the Raspberry Pi embedded system. In addition, the machine learning training and evaluation process is carried out online on the Raspberry Pi system. The online training process is carried out by integrating EMG data acquisition hardware devices, time domain features, classifiers, and motor control on embedded machine learning using Python programming. This study involved ten respondents in good health. EMG signals are collected at two lead flexor carpi radialis and extensor digitorum muscles. EMG signals are extracted using time domain features (TDF) mean absolute value (MAV), root mean square (RMS), variance (VAR) using a window length of 100 ms. Supervised machine learning decision tree (DT), support vector machine (SVM), and k-nearest neighbor (KNN) are chosen because they have a simple algorithm structure and less computation. Finally, the TDF and classifier are embedded in the Raspberry Pi 3 Model B+ microcomputer. Experimental results show that the highest accuracy is obtained in the open class, 97.03%. Furthermore, the additional datasets show a significant difference in accuracy (p-value <0.05). Based on the evaluation results obtained, the embedded system can be implemented for prosthetic hands based on EMG pattern recognition.
Co-Authors Abdussalam Ali Ahmed Bagas Angger Prakoso Baharudin Adi Baharsyah Dyah Titisari Harisha Avin Nurcahyana Indrato, Tri Bowo Lusiana Lusiana Luthfiyah, Sari Muhammad Ridha Mak'ruf Priyambada Cahya Nugraha Rahmawati, Triana Sari Luthfiyah Setioningsih, Endang Dian Tetra Putra, Moch Prastawa Assalim