A Human Health System Based on Raspberry Pi and Deep Learning Models

Abstract

This design uses Raspberry Pi to control the sensors to measure physiological indicators, avoiding the measurement results to be affected by subjective factors. This system design chooses to use a simple sensor, the overall system in the hardware design and production is simple and easy to implement, with low cost, low power consumption, easy to operate and other advantages. This Raspberry Pi based human health monitoring system can basically realise the human body temperature, heart rate and blood oxygen saturation monitoring, and when the above health data exceeds the human body health standard value, it will carry on the alarm reminder. At the same time, the health information can be transmitted to the computer of relatives and family doctors through the network data, so that when the health data is abnormal, you can get the help of relatives and family doctors. Deep learning algorithms can also be used to predict human health trends and identify potential health problems.