Kompresi Sinyal EKG menggunakan Teknik Parameter Extraction

CINTHIA ALIWARGA, ALOYSIUS ADYA PRAMUDITA, MARIA ANGELA KARTAWIDJAJA

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ABSTRAK

Sistem healthcare IoT menyebabkan peningkatan trafik komunikasi dan jumlah penyimpanan data. Elektrokardiogram (EKG) adalah salah satu alat yang berperan penting dalam healthcare IoT. Pasien yang mengalami kelainan jantung perlu dipantau oleh EKG dalam periode waktu lama sehingga menghasilkan data dalam jumlah yang sangat besar. Kompresi data mampu menjadi solusi masalah di atas. Penelitian ini melakukan kompresi sinyal EKG menggunakan metode parameter extraction untuk satu siklus sinyal dari dua belas pasien yang dipilih secara acak. Hasil penelitian menunjukkan bahwa kinerja kompresi baik, ditunjukkan oleh nilai Compression Ratio (CR) 6,24 dan Mean Square Error (MSE) 0,0018.

Kata kunci: IoT, EKG, kompresi data, parameter ekstraction.

 

ABSTRACT

Healthcare IoT causing higher data communication traffic and storage. Electrocardiogram (ECG) is one of the important device in healthcare IoT. Patient whose have heart abnormality needs ECG monitoring for long period of time, this causing a big data size. Data compression become one of the solutions for this problem. This research focused on data compression using parameter extraction method for one cycle ECG signal from twelve patients.This research has a good result with Compression Ratio (CR) 6,24 and Mean Square Error (MSE) 0,0018.

Keywords: IoT, ECG, data compression, parameter extraction


Kata Kunci


IoT; EKG; kompresi data; parameter ekstraction

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Referensi


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DOI: https://doi.org/10.26760/elkomika.v7i2.308

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