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All Journal Dinamik Sinkron : Jurnal dan Penelitian Teknik Informatika Jiko (Jurnal Informatika dan komputer) JURIKOM (Jurnal Riset Komputer) Jurnal Kreativitas PKM JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Riset Informatika Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) TEPIAN Journal of Electrical Engineering and Computer (JEECOM) Buletin Poltanesa Jurnal Pengabdian kepada Masyarakat Politeknik Negeri Batam Electronic Journal of Education, Social Economics and Technology The Indonesian Journal of Computer Science
Achmad Ridwan
Universitas Prima Indonesia
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Portable ECG Prototype based on Arduino and Random Forest Classification for Home Heart-Rate Monitoring R. Ferdy Akbar Nugraha; Novendy Alberto Will Tindaon; Arya Susena; Alfonso Duandes; Achmad Ridwan
Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC) Vol 7, No 3 (2025): November (Special Issue)
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/avitec.v7i3.3144

Abstract

Electrocardiogram (ECG) examination is essential for detecting heart rhythm disorders, yet limited access and high costs often prevent routine medical check-ups for many people. This study addresses these obstacles by designing and developing a portable ECG prototype capable of independent home-based heart monitoring. The system integrates an AD8232 sensor for signal acquisition, an Arduino Uno microcontroller as the main processor, and a simplified Random Forest classification algorithm to distinguish between normal, bradycardia, and tachycardia conditions. Measurement results are saved in CSV format on an SD card, then visualized and analyzed using Jupyter Notebook. The prototype was tested on 100 samples in a static and relaxed state to ensure signal stability. Its heartbeat classification achieved an accuracy of 99.0%, slightly higher than the PTB-XL reference dataset’s 98.0%, and consistent with results reported by recent TinyML- and Random Forest-based ECG studies. Unlike prior IoT-based frameworks, this work combines cost-effective microcontroller hardware with simplified offline on-device classification for practical daily monitoring without continuous cloud access. These findings confirm that the proposed system can produce reliable readings approaching clinical standards while remaining simple, affordable with a component cost under USD 31, and accessible for routine public heart health screening.
Co-Authors Abdi Dharma Agung Prabowo Agung Prabowo Agung Prabowo Ahmad Arif Alfonso Duandes Amir Saleh Andreas Tandana Arya Susena Ayu Sentia Br Sembiring Caryn Evelyn Tannesia Christin Erniati Panjaitan Debby Mutiara Br Sembiring Delima Sitanggang, Delima Dewi Sholeha Dhanny Rukmana Manday Fadhillah Azmi Fadhillah Azmi Fadhillah Azmi, Fadhillah Gibran, M Khalil Ginting, Riski Titian HS, Christnatalis Hutagalung, Elia Yose Mayal Lenny, Lenny Lewis Francolim M Khalil Gibran M. Khalil Gibran Manday, Dhanny Rukmana Meyga Fitri Handayani Nasution Mhd. Raihan M. Manurung Natasya Aulia Angkat Novendy Alberto Will Tindaon Nurul Safira Othman, M.A. Perangin Angin, Despaleri Putri Puspa Sari R. Ferdy Akbar Nugraha Ridho Maulana Siregar Rivanco Winson Rizka Azizah Rosa Englina Silaban Sau Dohot Siregar Saut Dohot Siregar Seftia Angelina Segono, Yohandres Sihombing, Yehezkiel Simangunsong, Putra Torang Simbolon, Harly Gumanti Siregar, Saut Dohot Sri Hayyu Fajhalika Tan Della Angelica Togar Timoteus Gultom Togar Timoteus Gultom Us, Nurul Iman Violyn, Violyn Yennimar Yennimar Yennimar, Yennimar Yoga Tri Nugraha Yudi Aditia