Design and Implementation of Health and Risk Level Assessment for Socially Disadvantaged Patients

Abstract

The platform developed in this study provides users with mental and physical health status monitoring services. Recently, it has been difficult for people with various respiratory diseases and mental health conditions to receive regular examinations/observation from specialized medical institutions. Therefore, in this study, because the need for the continuous health status measurement/monitoring of subjects was recognized, a device for constantly monitoring trends and changes in blood oxygen saturation was developed to ensure safety. Oxygen saturation below 90 indicates an emergency. In addition, we conducted a hypothesis test for analyzing the relationship between sensor data and depression and anxiety. The sensor data used in the research were location, gyroscope metrics, touch, data usage, and sleep mode from a smartphone. Correlation analysis and multiple regression analysis were conducted to analyze the relationship between the collected sensor data and depression and anxiety. As a result of the research, it was found that among the general characteristics, income, location, sleep duration, and gyroscope were found to have a negative effect on depression and anxiety, whereas touch was shown to have a positive (+) effect. It was confirmed that sensor data measured over runtime can be used as information that can explain users’ depression and anxiety.

Keywords

• health analysis
• IoT
• sensor data
• risk level analysis