Deteksi Gelombang P, QRS, T Pada Sinyal EKG Berbasis Edge Device

Napitupulu, Benjamin Aldrin Marlidang (2025) Deteksi Gelombang P, QRS, T Pada Sinyal EKG Berbasis Edge Device. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Elektrokardiogram (EKG) adalah alat diagnostik penting untuk menganalisis aktivitas listrik jantung, khususnya deteksi gelombang P, QRS, dan T yang berhubungan dengan berbagai kondisi kardiovaskular. Namun, pengolahan sinyal EKG secara tradisional sering memerlukan perangkat komputasi besar dan infrastruktur yang kompleks, sehingga kurang ideal untuk aplikasi di lapangan atau penggunaan real-time. Dalam penelitian ini, dikembangkan sebuah sistem berbasis komputasi edge untuk mendeteksi gelombang P, QRS, dan T pada sinyal EKG. Sistem ini memanfaatkan algoritma pemrosesan sinyal digital dan pembelajaran mesin CNN yang dioptimalkan untuk perangkat edge dengan daya komputasi terbatas. Pengujian dilakukan menggunakan dataset sinyal EKG standar pada perangkat edge Raspberry Pi. Penelitian ini diharapkan dapat mendukung aplikasi klinis yang lebih portabel dan efisien, serta mendorong inovasi dalam pengawasan kesehatan berbasis komputasi edge.
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Electrocardiogram (ECG) is an important diagnostic tool for analyzing the electrical activity of the heart, especially the detection of P, QRS, and T waves associated with various
cardiovascular conditions. However, traditional ECG signal processing often requires large computing devices and complex infrastructure, making it less than ideal for field applications or real-time use. In this study, an edge computing-based system is developed to detect P, QRS, and T waves in ECG signals. This system utilizes digital signal processing algorithms and CNN machine learning optimized for edge devices with limited computing power. Testing was carried out using a standard ECG signal dataset on a Raspberry Pi edge device. This study is expected to support more portable and efficient clinical applications, as well as encourage innovation in edge computing-based health monitoring

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Elektrokardiogram, Gelombang P QRS T, Komputasi Edge, Electrocardiogram, P QRS T Waves, Edge Computing
Subjects:	R Medicine > RC Internal medicine > RC683.5.E5 Electrocardiography
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Benjamin Aldrin Marlidang Napitupulu
Date Deposited:	31 Jul 2025 03:14
Last Modified:	31 Jul 2025 03:14
URI:	http://repository.its.ac.id/id/eprint/123411

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