Implementasi Sistem Pendeteksi Premature Ventricular Contraction (PVC) Aritmia Menggunakan Metode K-NN - Sulthan Ghiffari Awdihansyah; Rizal Maulana; Hurriyatul Fitriyah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2020)
The condition when the heart beats early is called the Premature Ventricular Contraction (PVC) Arrhythmia. Arrhythmia PVC conditions occur in the left ventricle of the heart. Almost every human will experience PVC arrhythmia during his lifetime. Arrhythmia PVC conditions that occur in a long time span can increase the risk of heart disease that leads to death. Examination of arrhythmia PVC conditions cannot be done independently and is quite expensive. AD8232 ECG Sensor Module, LCD 16x2, and Arduino Mega Microcontroller are used to detect PVC arrhythmia conditions. The K-NN classification method is used to classify 1 heartbeat cycle signal. The results of the K-NN classification are in 2 classes, namely the "Normal" class and the "PVC" class. The QRS Complex and Gradient R values of 1 heartbeat cycle signal will be used as parameters. heart conditions "Normal", "Bigeminy", "Trigeminy" are the output produced by the system. A total of 46 data were used as training data and as many as 23 data were used as test data in the classification of the K-NN method. The average value of program computation time is obtained by performing 10 times of program computation time testing. An accuracy value of 91.3% was generated from the results of the K-NN method classification accuracy testing. Testing the computational time of the program produces an average value of computing time of 1988.9ms.