Rancang Bangun Sistem Pendeteksi Central Sleep Apnea menggunakan K-NN berbasis Arduino Bluetooth Module - Qonita Luthfiyani; Edita Rosana Widasari; Fitri Utaminingrum (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2022)
Sleep apnea is a major problem with sleep disorders that cause partial or complete cessation of breathing during sleep. Detection of Central sleep apnea disease is considered important because this condition causes the body difficulty breathing in a short time at bedtime which will wake up the patient's sleep so that it will be difficult to sleep well and experience excessive drowsiness during the day. The National Sleep Foundation (NSF) suggests that about 20 percent of people experience excessive daytime sleepiness, which is caused by a person not getting enough sleep. However, central sleep apnea screening with polysomnography is ineffective because it requires a lot of sensors and must go to the hospital. The goal of the study was to create a system that could effectively detect central sleep apnea using recording physical activity only from the heart with ECG signals connected to a smartphone with bluetooth because people with Central sleep apnea correlate with cardiovascular disease. The system uses arduino UNO, ECG AD8232 sensor to record ECG signals, and HC-05 bluetooth module for wireless communication with smartphones. The system detects by taking the signal through the electrode then the signal result will be extracted using the RR interval feature and QRS duration and classified using the K-NN method. The results of the classification display are displayed on LCD and smartphone via bluetooth. The results shown are in the form of classes "Normal" or "Central sleep apnea". The resulting accuracy in testing with K-NN was 83.33% and the average K-NN compute time was 78,7 ms.