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Department of Electromedical Engineering, Poltekkes Kemenkes Surabaya Jl. Pucang Jajar Timur No. 10, Surabaya, Indonesia
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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 6 Documents
 1 
Search results for , issue "Vol 3 No 3 (2021): October" : 6 Documents clear
Design of an Electromyograph Equipped with Digital Neck Angle Elevation Gauge Ahmad Kamil Solihin; Endro Yulianto; Her Gumiwang Ariswati; K. K. Mujeeb Rahman
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.4

Abstract

The development of technology also affects human health, including body posture due to poor human position when using gadgets, both smartphones, and laptops. This study is design a tool that can measure the elevation of a person's neck angle equipped with electromyography, to help health workers, medical rehabilitation doctors to diagnose and provide treatment to patients with a bent head posture or forward head posture. In this research, an electromyography module is designed which consists of a series of instruments, a pre-amplifier circuit, a high pass filter, a low pass filter, and a dc offset regulator to be converted to digital so that it can be displayed on a laptop. In this study, the tapped muscle was the upper trapezius muscle using disposable electrodes. Meanwhile, to measure the angular elevation, the MPU 6050 sensor is used to measure the movement of the head forward. The frequency of the electromyography signal is 20-500 Hz. For software or display readings from this tool is Delphy. Meanwhile, the microcontroller used for ADC communication is Arduino Uno. From the research, it was found that the neck angle elevation gauge has a 0,597% error rate, for conditioning conducted on respondents, all respondents experienced a decrease in amplitude on the same frequency spectrum in the last ten minutes. Meanwhile, a drastic decrease occurred at the neck angle of 60°. Thus, it can be concluded that the forward position of the head affects the frequency spectrum of the neck muscles.
A Two Channels Wireless Electrocardiograph System Using Bluetooth Communication RAHMA DIAH ZUHROINI; Dyah Titisari; Torib Hamzah; T. K Kho
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.3

Abstract

Health problems with cardiovascular system disorders are still ranked high, according to data from the WHO reported that there are about 31% of causes of death globally are cardiovascular diseases. The purpose of this study was to develop a 12 lead electrocardiograph with 2 displays and the HC-05 as a real-time transmitter of heart signal data. The electrocardiogram signal is obtained from the wiretapping by attaching the electrode cable to the Lead I, Lead II, Lead III, aVR, aVL, and aVF leads, then processed on IC AD620, HPF and LPF filters and non-inverting amplifiers and then processed using Arduino UNO for further display. in the form of a signal on the Delphi 7 application. The research method is to measure the heart signal on the ECG Simulator, by testing several BPMs, namely 30, 60, 120 and 240 on each lead. After testing the signal equation at the 0.5mV setting by calculating the error rate, the highest error value is obtained in lead I, lead aVL and aVF of 7.14% and the smallest error is 3.57% error in lead III. Then at the 1mV setting by calculating the error rate, the highest error value in lead aVL is 7.14% and the smallest error is 2.36%. at the 2mV setting by calculating the error rate, the highest error value is obtained in leads aVL and aVF of 5.71% and the smallest error is obtained by an error of 2.1% in lead II. the results of this study are implemented so that in the future an ECG examination can be carried out and then monitored remotely like a doctor's room because the data communication uses bluetooth.
A comparative Evaluation of Swarm Intelligence Algorithm Optimization: A Review Shahab Wahhab Kareem; Shavan Askar; Roojwan Sc. Hawezi; Glena Aziz Qadir; Dina Yousif Mikhail
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.1

Abstract

Swarm intelligence (SI), an important aspect of artificial intelligence, is increasingly gaining popularity as more and more high-complexity challenges necessitate solutions that are sub-optimal but still feasible in a fair amount of time. Artificial intelligence that mimics the collective behavior of a group of animals is known as swarm intelligence. Attempting to survive. It is primarily influenced by biological systems. The main aim of our article is to find out more about the guiding principle, classify possible implementation areas, and include a thorough analysis of several SI algorithms. Swarms can be observed in ant colonies, fish schools, bird flocks, among other fields. During this article, we will look at some Swarm instances and their behavior. We see many Swarm Intelligence systems, like Ant colony Optimization, which explains ant activity, nature, and how they conquer challenges; in birds, we see Particle Swarm Optimization is a swarm intelligence-based optimization technique, and how the locations must be positioned based on the three concepts. The Bee Colony Optimization follows, and explores the behavior of bees, their relationships, as well as movement and how they work in a swarm. This paper explores some of the methods and algorithms.
Malaria Parasite Detection using Efficient Neural Ensembles Saurav Mishra
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.2

Abstract

Caused by the bite of the Anopheles mosquito infected with the parasite of genus Plasmodium, malaria has remained a major burden towards healthcare for years with an approximate 400,000 deaths reported globally every year. The traditional diagnosis process for malaria involves an examination of the blood smear slide under the microscope. This process is not only time consuming but also requires pathologists to be highly skilled in their work. Timely diagnosis and availability of robust diagnostic facilities and skilled laboratory technicians are very much vital to reduce the mortality rate. This study aims to build a robust system by applying deep learning techniques such as transfer learning and snapshot ensembling to automate the detection of the parasite in the thin blood smear images. All the models were evaluated against the following metrics - F1 score, Accuracy, Precision, Recall, Mathews Correlation Coefficient (MCC), Area Under the Receiver Operating Characteristics (AUC-ROC) and the Area under the Precision Recall curve (AUC-PR). The snapshot ensembling model created by combining the snapshots of the EfficientNet-B0 pre-trained model outperformed every other model achieving a f1 score - 99.37%, precision - 99.52% and recall - 99.23%. The results show the potential of model ensembles which combine the predictive power of multiple weal models to create a single efficient model that is better equipped to handle the real world data. The GradCAM experiment displayed the gradient activation maps of the last convolution layer to visually explicate where and what a model sees in an image to classify them into a particular class. The models in this study correctly activate the stained parasitic region of interest in the thin blood smear images. Such visuals make the model more transparent, explainable, and trustworthy which are very much essential for deploying AI based models in the healthcare network.
FinFET Towards Nano-Transistor: A Review Yasir Naif
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.5

Abstract

This paper review the FinFET structure as a future transistor for analog and digital electronic circuits, and present its electrical characteristics depending on the important parameters for evaluating the MOSFETs structures like DIBL and Ion/Ioff.
A Smart System to Ease Occurrence of Bedsores Benjamin Kommey
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 3 No 3 (2021): October
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA and IKATEMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v3i3.6

Abstract

The occurrence of bedsores in Ghanaian hospitals, elderly homes or care homes is especially high among patients or people who are incapacitated and cannot move or turn on their own, and who happen to remain in a particular posture for a very long time. Patients in coma, those operated on and for that matter in critical state, and patients confined to wheelchairs are primary examples. Constant pressure on some parts of the body leads to the occurrence of pressure sores or ulcers. This paper seeks to implement a Bedsore Easing System (BeSoSys) that integrate several embedded hardware components, a database and software to reduce the occurrence of bedsores. These embedded hardware components include the Bed Device Unit (BDU), the Pocket Device Unit (PDU), a pressure or weight sensor, a temperature sensor, and an inflation-deflation device. The BDU is fitted into the bed of the patient or on the surface of skin contact of the patient. The PDU is assigned to nurses or caretakers to serve as an alarm system for patient repositioning depending on situation. All activities in the Bedsore Easing System are logged into a database for future references. A bedridden patient exerts constant pressure on the bony protrusions of the body, and this causes bedsores. It was found out during the research that in Ghana, the nurses or caretakers used to turn and massage patients at some random time intervals as a way of preventing bedsores. This traditional way of turning and massaging patients is not only tedious but also ineffective. This paper seeks to provide easy, better, and effective solution to ease bedsores. The BeSoSys intends to prevent the occurrence of bedsores hence the alleviation of bedsore complications

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