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Happy Hypoxia Early Detection Tool in IoT Based for COVID-19 Patients Using SpO2 Sensor, Body Temperature and Electrocardiogram (ECG)

This research was aims to design a prototype and application for early detection of Happy Hypoxia symptoms in COVID-19 patients based on the Internet of Things (IoT). The experimental board consists of a microcontroller integrated with a pulse oximetry sensor, a heart rate sensor and a body temperature sensor. To determine the feasibility of the tool, an accuracy test is carried out. Accuracy shows the value of the proximity of the measurement results to the reference value or standard value. Accuracy is obtained by calculating the error value. The accuracy of the sensors used in this study refers to standard medical equipment that has been calibrated. In this study, the accuracy value was obtained by referring to the mean of error rate of each sensor. The sensor reading value is sent from the microcontroller to firebase as a cloud database and then displayed on the application dashboard as a user interface. From this data, it is hoped that it can help COVID-19 sufferers to detect the symptoms of Happy Hypoxia and help medical experts for prognostic or therapeutic purposes.