Pengembangan Sistem ECG Portable Berbasis Internet of Things (IoT) untuk Pemantauan Kesehatan Jarak Jauh

Hermawan, William Kester (2024) Pengembangan Sistem ECG Portable Berbasis Internet of Things (IoT) untuk Pemantauan Kesehatan Jarak Jauh. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pemantauan kesehatan jarak jauh semakin penting dengan meningkatnya kebutuhan layanan kesehatan yang efisien dan mudah diakses. Sistem ECG berbasis Internet of Things (IoT) penting karena memungkinkan pemantauan kesehatan secara real-time tanpa perlu pasien datang ke fasilitas kesehatan, memberikan kemudahan akses bagi mereka yang berada di daerah terpencil atau dengan mobilitas terbatas. Dalam penelitian ini, dikembangkan sistem ECG portable berbasis IoT menggunakan IC pengkondisian sinyal AD8232, mikrokontroler STM32, dan modul Bluetooth Low Energy HM-10. Data ECG disampling dengan frekuensi sampling 150 Hz dan ditransmisikan oleh modul BLE ke Raspberry Pi 4. Kemudian data tersebut dikirimkan ke cloud database untuk disimpan. Selain itu, data juga disimpan ke kartu microSD sebagai tempat penyimpanan sekunder. Pengujian menunjukkan bahwa alat pada sistem ini memiliki ukuran yang relatif kecil dan dapat mentransmisikan data electrocardiogram yang terdiri atas gelombang PQRST yang terfilter secara analog ke Firestore Database. Didapatkan hasil perbandingan nilai BPM sistem dengan oximeter menunjukkan Mean Absolute Error (MAE) sebesar 2.9492 dan P-value (paired t-test) sebesar 0.00175
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Remote health monitoring is increasingly important with the increasing need for efficient and accessible healthcare services. An Internet of Things (IoT)-based ECG system is important because it allows real-time health monitoring without the need for patients to come to a healthcare facility, providing easy access for those in remote areas or with limited mobility. In this study, a portable IoT-based ECG system was developed using the AD8232 signal conditioning IC, STM32 microcontroller, and Bluetooth Low Energy HM-10 module. ECG data is sampled at a sampling frequency of 150 Hz and transmitted by the BLE module to the Raspberry Pi 4. Then the data is sent to the cloud database for storage. In addition, the data is also stored on a microSD card as a secondary storage. Tests show that the device in this system has a relatively small size and can transmit electrocardiogram data consisting of analog filtered PQRST waves to the Firestore Database. The results of the comparison of the BPM system value with the oximeter showed a Mean Absolute Error (MAE) of 2.9492 and a P-value (paired t-test) of 0.00175

Item Type:	Thesis (Other)
Uncontrolled Keywords:	electrocardiogram, internet of things, bluetooth low energy
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7878 Electronic instruments
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	William Kester Hermawan
Date Deposited:	01 Aug 2024 12:53
Last Modified:	12 Sep 2024 07:26
URI:	http://repository.its.ac.id/id/eprint/110698

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