SISTEM MONITORING SINYAL ELEKTROKARDIOGRAM (EKG) MENGGUNAKAN THINGSPEAK CLOUD COMPUTING
-
Amin Ajaib Maggang(1*)
Universitas Nusa Cendana
-
Beby H. A. Manafe(2)
Universitas Nusa Cendana
-
Sarlince O. Manu(3)
Universitas Nusa Cendana
-
Johanis F. M. Bowakh(4)
Universitas Nusa Cendana
(*) Corresponding Author
Abstrak
Perkembangan dalam bidang elektronika dan software memunculkan banyak aplikasi cloud computing yang dapat diintegrasikan dengan arduino uno untuk membangun suatu sistem monitoring kesehatan jantung yang murah. Olehkarena itu, penelitian ini bertujuan untuk membangun suatu sistem monitoring kesehatan jantung berbasis internet of things dengan memanfaatkan akun tak berbayar ThingSpeak server dan sensor EKG AD8232. Hasil nya menunjukan bahwa sistem yang dibangun dapat mengrim data EKG dan ditampilkan pada ThingSpeak server, meskipun hanya segment QRS dan RR dari sinyal EKG yang dapat di tampilkan dengan baik dan sesuai dengan Standar normalnya. Selain itu, sistem ini juga mampu secara otomatis menghitung dan menampilkan nilat Heart Rate pada output ThingSpeak server setiap 15 detik, sehingga kesehatan jantung dapat dimonitor secara realtime.
##plugins.generic.usageStats.downloads##
Referensi
WHO. (2021, 1 Maret 2021). Cardiovascular Diseases. Available: https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1
M. Naazneen, S. Fathima, S. H. Mohammadi, S. I. L. Indikar, A. Saleem, and M. Jebran, "Design and Implementation of ECG monitoring and heart rate measurement system," International Journal of Engineering Science and Innovative Technology (IJESIT), vol. 2, pp. 456-465, 2013.
R. D. Anderson, S. Kumar, R. Parameswaran, G. Wong, A. Voskoboinik, H. Sugumar, et al., "Differentiating right-and left-sided outflow tract ventricular arrhythmias: classical ECG signatures and prediction algorithms," Circulation: Arrhythmia and Electrophysiology, vol. 12, p. e007392, 2019.
S. Das, S. Pal, and M. Mitra, "Arduino-based noise robust online heart-rate detection," Journal of medical engineering & technology, vol. 41, pp. 170-178, 2017.
M. C. T. Manullang, J. Simanjuntak, and A. L. Ramdani, "Implementation of AD8232 ECG Signal Classification Using Peak Detection Method For Determining RST Point," Indonesian Journal of Artificial Intelligence and Data Mining, vol. 2, pp. 61-66, 2019.
N. K. Jumaa, "Survey: internet of thing using FPGA," Iraq J. Electrical and Electronic Engineering, vol. 13, 2017.
A. A. Mohamad, N. K. Jumaa, and S. H. Majeed, "Thingspeak Cloud Computing Platform Based ECG Diagnose System," International Journal of Computing and Digital Systems, vol. 8, pp. 11-18, 2019.
ThingSpeak. (2020, 01 Maret 2021). ThingSpeak™ Licensing FAQ. Available: https://thingspeak.com/pages/license_faq
B. E. Jin, H. Wulff, J. H. Widdicombe, J. Zheng, D. M. Bers, and J. L. Puglisi, "A simple device to illustrate the Einthoven triangle," Advances in physiology education, vol. 36, pp. 319-324, 2012.
A. L. Goldberger, "Goldberger’s clinical electrocardiography," ECG basics: waves, intervals, and segments, vol. 2, pp. 8-14, 2013.
F. Roberto, "Automatic heartbeat monitoring system," 2019.
This work is licensed under CC BY-SA 4.0
