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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Green Intelligent Systems and Applications
Nurbadriani, Cut Nanda
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Literature Review: Biomedical Information of Animal Treadmill Speed Control Using Proportional Integral Derivative Controller Nurbadriani, Cut Nanda; Melinda, Melinda; Roslidar, Roslidar
Green Intelligent Systems and Applications Volume 4 - Issue 2 - 2024
Publisher : Tecno Scientifica Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53623/gisa.v4i2.526

Abstract

The use of treadmill exercise in cardiovascular research played a vital role in assessing heart health and determining appropriate exercise regimens for patients. Before applying these regimens to humans, experiments on animals, such as white rats or mice, were conducted to simulate human cardiovascular responses. A specialized treadmill designed for experimental animals was required to determine exercise doses based on individual abilities. This process involved controlling the treadmill speed, which was generated by a conveyor driven by a DC motor. The motor speed was regulated through PID (Proportional Integral Derivative) control, while encoder sensors monitored the motor’s rotation speed, and limit switch sensors determined the exercise duration. This article reviewed the design and implementation of treadmill systems used for animal-based cardiovascular research, focusing on the control of DC motor speed using PID controllers. Previous studies that contributed to the development of such systems were discussed, with an emphasis on the precise control mechanisms required to simulate exercise conditions tailored to the subject's abilities. The treadmill system also incorporated sensors to accurately adjust motor speed and track exercise duration, ensuring alignment with the physiological capabilities of the test subjects. Furthermore, this review explored the potential for advancing research on treadmill control systems, offering insights into how this technology could support medical experts in determining optimal exercise regimens for white rats. These developments helped bridge the gap between animal-based studies and human applications, facilitating improved cardiovascular research outcomes.
PID Controller Implementation on Animal Experimental Treadmill for Heart Medicine Purpose Melinda, Melinda; Ridwan, Muhammad; Nurbadriani, Cut Nanda; Yunidar, Yunidar
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 4, November 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i4`.1762

Abstract

Experimental animals such as rats are often used for medical research and therapy, such as cardiologists who use a special treadmill to measure the heart health of rats by training walking or running in order to determine the appropriate dose for individuals before being applied to their patients. This research designed a system that is operated by the speed of a DC motor. To control the system, it is proposed to implement a Proportional Integral Derivative (PID) control that is able to stabilize the rotation of the DC motor based on the BPM value recorded by the encoder sensor. The value is used as feedback to the PID control, so that it can control the speed of the DC motor and work optimally and stably under load or no load. Adding a limit switch as a fatigue zone to determine the final duration. This system was tested on several objects, namely 4-month-old rats with a mass of 211 grams, 224 grams, 230 grams, and 240 grams and 2-month-old rats with a mass of 24 grams, 27 grams, 28 grams, and 30 grams. The results show that the speed reading using PID control is in accordance with the constants Kp = 17, Ki = 7, and Kd = 1. This test has a percentage overshoot (%) of 5% and an average rise time value of 0.14 seconds. System performance with a percentage accuracy of 90% starting from a setpoint of 35 m/min.
Classification of Arrhythmic and Normal Signals using Continuous Wavelet Transform (CWT) and Long Short-Term Memory (LSTM) Yunidar, Yunidar; Melinda, Melinda; Azmi, Ulul; Bashir, Nurlida; Nurbadriani, Cut Nanda; Taqiuddin, Zulfikar
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 2, May 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i2.1917

Abstract

An electrocardiogram (ECG) can detect heart abnormalities through signals from the rhythm of the human heartbeat. One of them is arrhythmia disease, which is caused by an improper heartbeat and causes failure of blood pumping. In reading ECG signals, a common problem encountered is the uncertainty of the prediction results. An accurate and efficient heart defect classification system is needed to help patients and healthcare providers carry out appropriate therapy or treatment. Several studies have developed algorithms that are more effective in Machine Learning (ML) in automatically providing initial screening of patients' heart conditions. This study proposed the Long Short-Term Memory (LSTM) method as a classifier of heart conditions experienced by humans and Continuous Wavelet Transform (CWT) as a feature extractor to eliminate noise during data collection. CWT and LSTM methods are believed to perform well in feature extraction and classification of ECG signals. The dataset used in this study was taken from the MIT-BIH Arrhythmia Database. The results of this study successfully extracted ECG signals using CWT, thus improving the understanding of ECG characteristics. This research also succeeded in classifying ECG signals using the LSTM method, which obtained an accuracy training value of 98.4% and an accuracy testing value of 94.42 %.
Co-Authors . Roslidar Bashir, Nurlida Melinda Melinda Muhammad Ridwan Ulul Azmi Yunidar Zulfikar Taqiuddin