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All Journal Signal and Image Processing Letters
Sari, Nurjanah Arvika
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Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Journal : Signal and Image Processing Letters

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Direct Current Processing in DC Motor Using Arduino and Peak Value Method Ma'arif, Alfian; Sari, Nurjanah Arvika; Prasetya, Wahyu Latri; Feter, Muslih Rayullan; Saputra, Dodi; Setiawan, Muhammad Haryo
Signal and Image Processing Letters Vol 3, No 3 (2021)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v3i3.79

Abstract

The research proposes about monitoring current of Direct Current (DC) Motor using microcontroller, current sensor and peak value method. The device is Arduino Uno R3 microcontroller, current sensor INA 219, motor driver L298, DC motor JGA25-370 and computer. The algorithm detects the inrush of the DC Motor Current. In the experiment result, the device can measurement the current sensor by varying the Pulse Width Modulation (PWM) such as 50-150. The method can avoid the zero current value. Thus, the proposed method could be implemented for monitoring the direct current of DC Motor.
Implementation of Heart Rate System using AD8232 and Arduino Microcontrollers Setiawan, Muhammad Haryo; Sari, Nurjanah Arvika; Prasetya, Wahyu Latri; Feter, Muslih Rayullan; Saputra, Dodi; Ma'arif, Alfian
Signal and Image Processing Letters Vol 2, No 1 (2020)
Publisher : Association for Scientific Computing Electrical and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/simple.v2i1.84

Abstract

The human heart's pivotal role in maintaining overall health by ensuring oxygen and nutrient delivery to tissues and waste elimination highlights the global importance of cardiac health. Electrocardiography (ECG) is a fundamental tool for assessing cardiac conditions, capturing intricate electrical signals during each heartbeat. ECG sensors are instrumental in this process, finding extensive applications in personal health monitoring, disease management, and medical research. This article emphasizes the significance of ECG sensors, particularly the AD8232 ECG sensor paired with the Arduino Nano microcontroller. It outlines their operational principles, measurement methods, and signal-processing techniques. The research aims to enhance the accuracy and efficiency of ECG data capture, contributing to advanced cardiac monitoring systems. Intelligent systems employing biopotential sensors and electrocardiographs enhance diagnostic precision, minimizing interpretational errors. ECG sensors, which record and translate the heart's electrical activity into interpretable data, are integral to modern medicine. They are used in diverse settings, from clinical environments to personal health monitoring. Ensuring ECG sensor accuracy is critical, as the data directly impacts diagnosis and treatment. This article offers insights into fundamental principles, measurement procedures, and programming techniques for ECG sensors, facilitating efficient data capture and processing. These findings promise user-friendly cardiac monitoring systems advancements, significantly contributing to medical technology and healthcare.
Co-Authors Alfian Ma’arif Dodi Saputra Feter, Muslih Rayullan Prasetya, Wahyu Latri Setiawan, Muhammad Haryo