Implementasi Metode K-Nearest Neighbors Pada Sistem Pendeteksi Sleep Apnea - Dony Satrio Wibowo; Rizal Maulana; Fitri Utaminingrum (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Sleep apnea is a medical problem that has a sustained impact and has a high mortality rate, which is a burden on public health services. There are two main types of sleep apnea, that is central sleep apnea and obstructive sleep apnea. In this study I developed a system related to obstructive apnea because it is the most common form of apnea. To help medical staff or someone who has indicated sleep apnea to monitoring this disease, we need a system that can be used as an early detection is. This system uses the K-Nearest Neighbor method as the signal type determination algorithm. The acquisition of ECG signals by AD8232 sensor will acquire R-peak and R-interval data that used as parameters for determining sleep apnea. This system uses Arduino Uno as a microcontroller, AD8232 as an input and Buzzer as an output. The AD8232 sensor has an accuracy rate of 94.56%, the accuracy rate of the K-Nearest Neighbor method which is carried out as many as 15 experiments is 86.6%. And generated a time of 1281.1 ms for the average processing time of the system.