Rancang Bangun Sistem Deteksi Hipoksia berdasarkan Detak Jantung dan Saturasi Oksigen menggunakan Low Power Mode dengan Metode Naive Bayes - Ahmad Haris Wahyudi; Edita Rosana Widasari; Hurriyatul Fitriyah (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2022)
Hypoxia is a condition when the tissues in the body lack oxygen so that their functionality is disrupted and can be fatal, such as organ damage and even death. One of the causes of hypoxia is environmental factors such as being at high altitudes with minimal oxygen. Therefore, hypoxia is also a frightening specter for mountain climbers, where there are minimal medical facilities to check the condition of climbers. Therefore, in this study designed a portable system to detect hypoxia in climbers. Hypoxia detection was carried out using heart rate (BPM) and blood oxygen saturation (SpO2) parameters whose data were acquired using the MAX30102 sensor. After that, the data was processed and classified using the naive Bayes method on the Arduino Mega 2560 microcontroller. This system uses a battery for its power source so that it is more portable and can still be used in mountain areas where there is no power source. Due to very limited battery power, a low-power mode is implemented in the form of sleep mode so that it can save battery power consumption. In testing the BPM and SpO2 readings with the MAX30102 sensor, an accuracy of 98.03% and 97.62% was obtained. In the naive Bayes classification test results obtained an accuracy of 93.33% with a computation time of 829.2 Âµs. As well as for power efficiency with low power mode, a decrease in current consumption reaches 70.13%.