Early Detection of Social Anxiety Disorder by using Screening Tools and Wearable Sensors

Abstract

Social Anxiety Disorder (SAD) is one of the mental health problems that occurs when people experience an intense fear for being criticized or humiliated even in everyday situations. It is very important to detect SAD in its initial stages to prevent severe mental health condition. This study aims at proposing an alternative method to detect the SAD in initial stages and to ensure that the method is more effective and easier to conduct. There are two steps analyzing the collected data in order to understand whether the subject is having SAD behavior or not. Firstly, the data was collected with the help of questionnaires, for instance, Diagnostic and Statistical Manual of Mental Disorder, 5th Edition (DSM-5), and Liebowitz Social Anxiety Scale (LSAS). These questionnaires are normally used to diagnose people with mental health conditions. To verify the data obtained from the questionnaire, the subject will undergo the activity to record the physiological signals to stimulate the responses of SAD behavior by wearing the wearable sensor device. The physiological signals that were measured for this experiment include heart rate and skin temperature. Heart rate was measured using Electrocardiography (ECG) sensor and also photoplethysmography (PPG) sensor while skin temperature was measured with the help of temperature sensor. The parameters measured include heart rate and skin temperature, are analyze using K-Nearest Neighbor, and Decision Tree. These methods are chosen based on their criteria of high accuracy and easy to understand.