Klasifikasi Obstructive Sleep Apnea (OSA) Berdasarkan Fitur Statistik Interval RR pada Sinyal ECG

Authors

  • Desanti Nurma Risalah Dept. Teknik Komputer Institut Teknologi Sepuluh Nopember Surabaya, Indonesia
  • Yoyon K. Suprapto Dept. Teknik Komputer Institut Teknologi Sepuluh Nopember Surabaya, Indonesia
  • Diah Puspito Wulandari Dept. Teknik Komputer Institut Teknologi Sepuluh Nopember Surabaya, Indonesia

DOI:

https://doi.org/10.59378/jcenim.v2i2.50

Keywords:

ECG, OSA, RR interval, Support Vector Machine

Abstract

Obstructive sleep apnea (OSA) adalah gangguan umum di mana seseorang berhenti bernapas saat tidur yang dapat menyebabkan penyakit kardiovaskular jika tidak ditangani dengan baik. Sebagian besar kasus sleep apnea diuji menggunakan polisomnografi (PSG), yang merupakan prosedur standar untuk diagnosis semua gangguan tidur. Namun, sebagian besar kasus sleep apnea masih tidak terdiagnosis karena prosedur pengujian yang mahal dan tidak praktis, mengingat polisomnografi (PSG) dilakukan di laboratorium tidur dan memerlukan pengamat manusia ahli yang harus bekerja semalaman. Penelitian ini mengusulkan suatu metode untuk mendeteksi OSA berdasarkan sinyal ECG menggunakan klasifikasi. Sinyal ECG dapat dimanfaatkan untuk membuat sistem deteksi menjadi lebih sederhana dan lebih cepat dibandingkan PSG. Sinyal ECG diperoleh dari dataset PhysioNet menggunakan 10 subjek perekaman yang berbeda. Data direkam selama 2 malam berturut-turut menggunakan perekaman ECG satu kanal. Fitur statistik diekstraksi berdasarkan interval RR yang memproses epoch berdurasi pendek dari data ECG. Hasil ekstraksi fitur digunakan sebagai masukan klasifikasi dengan metode Support Vector Machine untuk dilatih dan diuji pada rekaman tidur dari subjek dengan dan tanpa OSA. Kinerja sistem ditentukan dengan memperoleh nilai Akurasi, Sensitivitas, dan Spesifisitas. Hasil penelitian menunjukkan bahwa sistem mampu mengenali epoch gangguan tidur dengan tingkat akurasi yang tinggi, yaitu sekitar 83,67%. Di masa depan, sistem yang dibuat diharapkan dapat dikembangkan dan digunakan sebagai dasar pengembangan alat skrining OSA.

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Published

2024-07-15

How to Cite

Desanti Nurma Risalah, Yoyon K. Suprapto, & Diah Puspito Wulandari. (2024). Klasifikasi Obstructive Sleep Apnea (OSA) Berdasarkan Fitur Statistik Interval RR pada Sinyal ECG. Journal of Computer Engineering, Network, and Intelligent Multimedia, 2(2), 67–77. https://doi.org/10.59378/jcenim.v2i2.50

Issue

Vol. 2 No. 2 (2024)

Section

Articles

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Copyright (c) 2026 Desanti Nurma Risalah, Yoyon K. Suprapto, Diah Puspito Wulandari

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