Implementation and Evaluation of Prototype Photoplethysmography for Healthy Person-Based Internet of Things

A decrease in the oxygen rate of blood flow will lead a human to death because it affects the oxygen supplied to the heart and its pumping. A normal heart rate ranges from 60 to 100 BPM and a normal oxygen saturation ranges from 95 to 100%. This study aimed to develop a heart rate and oxygen saturation monitoring device with non-invasive method and linear regression modeling. Photoplethysmography is developed using the MAX30100 sensor. The NodeMCU ESP8266 V3 acts as a microcontroller with a Wi-Fi module to transmit data. Firebase is used as a web server, and MIT App Inventor is used to create a monitoring application. Some features are embedded in the monitoring application and sent heart rate and oxygen saturation data to Firebase. After several tests, it was found that linear regression improves heart rate reading from 95.06 to 96.30% and oxygen saturation reading from 95.74 to 96.81%. Data are sent to the database through the Internet connection. After retrieval of 20 data, the connection (network) test obtained an average throughput of 108.157, an average delay of 96.168 ms, and an average packet loss of 0.44%. Finally, it is concluded that the proposed device can be used to monitor heart rate and oxygen saturation for a healthy person.