joinssr Journal of Smart Systems Research 2757-6787 Sakarya University of Applied Sciences Artificial Intelligence Yapay Zeka Real-Time Arrhythmia Detection Using NI LabVIEW and Sending Notification via SIM800L GSM Module Ay Ayşe Nur SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ Yuksel Esat Egemen SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ Yılmaz Akın Yiğit SAKARYA UYGULAMALI BİLİMLER ÜNİVERSİTESİ Dolukan Yaşar Barış OSTİM TEKNİK ÜNİVERSİTESİ 12 31 2020 1 1 25 29 10 14 2020 11 12 2020 Copyright © 2020, Journal of Smart Systems Research 2020 Journal of Smart Systems Research

It is well-known that in case of cardiovascular diseases an early diagnosis is one of the vital role to prevent the deaths. Although there are many devices and applications to diagnose the diseases, most of them are either too expensive or an expert is required to use it. The aim of the current study is measuring the Electrocardiogram (ECG) signals from the human-body in real-time, processing these signals simultaneously via LabVIEW and by calculating heart rate of a patient using Teager Energy method, detecting tachycardia and bradycardia arrhythmias. Therefore, using an Arduino UNO and SIM800L GSM module, the information of a patient regarding abnormality of his/her heart beats could be sent to a his/her relative or a doctor. With this new low cost and simple application, an arrythmia could be immediately detected and one can intervene the patient on time.

 Electrocardiogram (ECG) Arrhythmia ArduinoUNO SIM800L [1] W. H. Federation, Global Atlas on Cardiovascular disease prevention and control, 2011. [2] T. Padma, M. M. Latha and A. Ahmed, "ECG comparison and labview implementation.," Journal of Biomedical Science and Engineering, vol. 2, no. 3, pp. 177-183, 2009. [3] I. A. AL-QARAGHULI, Labview based simulation and automatic analysis of ECG signals using FPGA, University of turkish aeronaurical association, 2017. [4] M. Muruggapan, R. Thirumani, M. I. Omar and S. Murugappan, "Development of cost effective ECG data Acquisiton system for clinical applications," in IEEE 10th International Colloquium on Signal Processing& its Applications (CSPA2014), 2014. [5] S. N. Ilker, Ekg sinyalleri için aritmi sezimi ve mobil ağlar üzerinden iletim., İstanbul: Istanbul University, 2018. [6] P. Kanani and M. Padole, "Recognizing Real Time ECG Anomalies Using Arduino, AD8232 and Java," in International Conference on Advances in Computing and Data Sciences, Singapore, 2018. [7] A. R. Satani, D. R. Damodar and B. R. Satani, "Heart arrhythmia detection using labview GUI based approach," International Journal of Advanced Technology and Engineering Exploration, vol. 5, no. 48, 2018. [8] N. Ahmed and Y. Zhu, "Early Detection of Atrial Fibrillation Based on ECG Signals," Bioengineering, vol. 7, no. 1, p. 16, 2020. [9] S. Rege, T. Barkey and M. Lowenstern, "Heart arrhythmia detection," in 2015 IEEE Virtual Conference on Applications of Commercial Sensors (VCACS), Raleigh, NC, USA, 2015. [10] S. Das, S. Pal and M. Mitra, "Arduino-based noise robust online heart-rate detection," JOURNAL OF MEDICAL ENGINEERING & TECHNOLOG, vol. 41, no. 3, pp. 170-178, 2017. [11] "Guide U.," National Instruments myDAQ, 2016. [12] A. N. Ay, M. Z. Yildiz and B. Boru, "NI Labview kullanılarak EKG Sinyallerinin Gerçek Zamanlı Özellik Çıkarımı," SAU Fen Bilimleri Enstitüsü Dergisi, 2017. [13] S. Butterworth, "On the Theory of Filter Amplifiers," Experimental Wireless& the wireless Engineer, vol. 7, pp. 536-541, 1930. [14] F. Holmqvist, P. G. Platonov, R. Havmöller and J. Carlson, "Signal-average P wave analysis for delineation of interatrial conduction-Further validation of the method," BMC Cardiovascular Disorders, 2007. [15] H. Beyramienanlou and N. Lotfivand, "An Efficient Teager Energy Operator-Based Automated QRS," Journal of Healthcare Engineering, vol. 11, 2018. [16] A. N. Ay, B. Dolukan and M. Z. Yildiz, "The Effect of Attentional Focus Conditions on Performer's EMG Activity," Academic Perspective Procedia, vol. 1, no. 1, pp. 240-247, 2018.